Search

Argumentation structure within the content of scientific paper is the fundamental for proving scientific findings. Constructing the argumentation graph is an effective way to realize the visualization of argumentation structure and help users quickly understand the logical of papers. This study presents the method for constructing argumentation graph of scientific papers, includes an ontology for describing the scientific papers' argumentation structure, a process for deep semantic annotation and a mapping protocols for transforming the annotation results into graph structure by using Neo4J. The method was applied to construct an argumentation graph and the argumentation process retrieval was also realized. The result suggest that the argumentation graph could be benefit for the argumentation visualization and strategic reading of scientific papers. [ABSTRACT FROM AUTHOR]

In scientific research, laboratory (lab) notebooks have traditionally been used to record experiments and their results. Lab notebooks also act as an important record of the generation, processing and analysis of data over the research data lifecycle. As research data becomes increasingly digitized and voluminous, it becomes harder to record and describe research data, especially in paper lab notebooks (PLNs). This paper addresses the challenges of recording contemporary research data in lab notebooks and discusses the requirements in lab notebooks for describing research data. Two basic requirements of lab notebooks are the completeness of the data description and the ability to link the experiment records with their corresponding research datasets. Descriptions of research data should also document the provenance of the research data so that the original data can be retrieved. Guidelines for consistent file naming and systematic directory structures for saved research data can support efficient research data retrieval. [ABSTRACT FROM AUTHOR]

What is the thermal conductivity of copper? This straightforward question leads to a fascinating instance of the production of scientific facts through documentation practices. Ho, Powell and Liley's 1974 The Thermal Conductivity of the Elements: A Comprehensive Review is examined as an artifact of scientific reference data production, and its answer to the initial question is traced to modern‐day search engine results. A short history of the Center that produced the book and some initial research into its authors is provided. Kuhn's concepts of normal science and normic lexical structures are utilized to clarify the Comprehensive Review's functioning within the broader scientific fields in which it is utilized. Bowker's concepts of memory practices and the jussive Archive help identify the forgetting embedded in the production of reference data, producing what Star called global certainty. Far from impugning the internal validity of these scientific facts, this forgetting is shown to be licensed by scientific rigor. This paper presents a novel historically informed investigation of how documentation practices produce scientific facts, and connect these activities to modern‐day knowledge graph information retrieval. The theoretical analyses provided show how scientifically licensed forgetting is a key mechanism of fact production, what Hayles termed constrained constructivism. [ABSTRACT FROM AUTHOR]

ABSTRACT The purpose of this study is to investigate (a) the current established institutional repositories of the most excellent universities worldwide, (b) the total amount of contents in the individual institutional repositories, and (c) the correlation between the total amount of contents in institutional repositories and the scores of university ranking performance indicators. [ABSTRACT FROM AUTHOR]

ABSTRACT Prior studies have identified a need for engaging researchers in providing and curating their identity data. This poster reports preliminary findings of a qualitative study exploring how researchers use and engage in online research identity management (RIM) systems. The findings identify nine activity or task related motivations of using RIM systems. This study also identified three levels of participation in RIM systems: Readers, Personal Record Managers, and Community Members. Most participants of this study fell into the category of Personal Record Managers, who may maintain their own profiles in a RIM system. This suggests that a majority of researchers may be willing to maintain their research identity profiles. Institutional repository managers may consider recruiting researchers as not only research information and data providers, but also curators of their own research identity data. [ABSTRACT FROM AUTHOR]

Common Bean (Phaseolus vulgaris L.) an essential nutrition source for protein and is quite common in the Indian subcontinent, China, Brazil, and the USA. Common Bean contains nutritional component which will contribute to the reduction of food scarcity worldwide in the coming years (Nadeem et al. 2021). In recent years, the research trends applying informatics techniques have given opportunities to harness genomic level information for better sequencing, generating a large volume of data. The data is generally being utilized for better crop production and improved varieties. The generated data are stored and developed as databases, web servers, publications, and patents. However, managing data in a helpful way is a challenge. This paper proposes a model for developing an integrated platform that comprehends various Common bean information. The proposed model shall provide curated information resources about Common Bean, facilitating the single platform access. The intended benefits can be visualized as the researcher can find all information in one place to showcase the progress of research taking place in this field. [ABSTRACT FROM AUTHOR]

As an integral part of research activities, scholars frequently interact with bibliographic information retrieval systems to acquire scholarly information. With the dramatic increase of scientific literature, there is the pressing need of building effective and efficient bibliographic information retrieval systems that support more granular and complex bibliographic information needs. Investigating users' interaction with these systems plays an important role in understanding the systems' features and usability issues, which contributes to better system design and implementation. In this paper, we evaluate three interactive bibliographic information retrieval systems proposed in our previous studies using a user‐centered approach, including form‐, natural language‐, and visual graph‐based systems. This study recruits 20 participants to evaluate the three systems from the aspects of success rate, search time, query size, usefulness, ease of use, ease of learning, and satisfaction. Results showed that: the form‐based system needed the least time to formulate simple bibliographic queries and allowed the participants to make the least mistakes; the natural language‐based system needed the least time to formulate high‐complexity bibliographic queries and was rated as the most useful, easy‐to‐use, and easy‐to‐learn system; and the visual graph‐based system's strengths lie in the support of complex queries as shown that it got better ratings of usefulness and satisfaction by the high‐complexity task group. [ABSTRACT FROM AUTHOR]

Knowledge elements are the basic unit of knowledge. Extracting knowledge elements from literatures enables granular knowledge organization and retrieval. This paper proposes a rule‐based framework for extracting method Knowledge Elements (KEs) in scientific literature aiming to improve the accuracy and complete extraction of method KEs. The method is divided into two stages: semi‐automated extraction of initial description rules of method KEs and automated derivation of additional description rules. In a preliminary evaluation on 415 papers, the precision and recall for the method KEs extraction are 0.77 and 0.84, respectively, indicating the effectiveness of our method. [ABSTRACT FROM AUTHOR]

The Repository of Assigned Search Tasks (RepAST) is a searchable repository created through a systematic review of the interactive information retrieval (IIR) research literature. It currently contains bibliographic details for approximately 750 articles, including empirical studies that employ assigned search tasks and a smaller number of conceptual papers on task-based searching. When available, the search task types, definitions and the task descriptions themselves are included. RepAST makes several contributions to the field. By bringing together examples of search task descriptions used in actual studies, RepAST provides a platform for studying practices within the research community and promoting greater conceptual clarity and consensus in the use of search tasks. To this end, the authors have published several studies based on analyses of the search tasks in the repository. In addition, researchers can use RepAST in a practical way, as a source of search task descriptions for reuse in new studies or in order to replicate prior research. In this interactive demo session, participants will have the opportunity to use the live RepAST system and provide feedback to the system designers. [ABSTRACT FROM AUTHOR]

This paper brings together and enriches the heretofore dispersed literature on information work and information practices. It does so under the auspices of Critical Race Theory (CRT), intersectionality, and care work. Using the COVID‐19 pandemic in the United States as the context for an exploratory, qualitative case study, we propose the concept of intersectional information work practices (IIWP) to denote the cluster of information‐centric tasks in which Black women carers engaged. Seeking, scanning, searching, monitoring, finding, receiving, retrieving, using, and sharing information—Black women carers performed each of these IIWPs in dealing with health care providers, tests, illness and treatment, wellness, logistics, and avoiding misinformation. An IIWP lens sheds light on the too often invisible labor of Black women carers. Such a lens also brings into high relief the importance of scrutinizing power and (in)equity, race, gender, and class in exploring foundational Information Science concepts. [ABSTRACT FROM AUTHOR]

The proposing of an accurate and efficient model for automatic keyword extraction of scientific literature is conducive to promoting the development of academic text mining research, such as literature retrieval optimization, research topic discovery, topic evolution analysis, emerging trend detection and so on, with the continuous expansion of digital academic resources. A keyword extraction method is proposed called NER‐RAKE which combines Named Entity Recognition (NER) process with Rapid automatic keyword extraction (RAKE), Bidirectional Long Short‐Term Memory Network Conditional Random Field (BiLSTM‐CRF) is used to recognize the domain entities in the scientific literature so as to enrich the list of candidate keywords divided by RAKE, and the frequency threshold is set to ensure the validity of candidate keywords. NER‐RAKE is better than RAKE in accuracy and recall rate through the keyword extraction experiment in the computer science field. It is effective to combine the process of NER with RAKE, which can improve the efficiency of keyword extraction. [ABSTRACT FROM AUTHOR]

As typically conceived, the goal of information retrieval is to help people find what they seek. However, when sensitive content is intermixed with what is sought, it can be equally important to help protect what should not be seen. This paper focuses on one such case, the protection of content that is subject to a claim of attorney-client privilege when sharing evidence incident to civil litigation, a process called e-discovery. Although lawyers have been quick to embrace text classification techniques for finding relevant evidence, the stakes involved in inadvertent disclosure of privileged content create reluctance to trust any fully automated technique to accurately recognize content that can properly be withheld. Rather than starting with privilege classification as a goal, this paper proposes a modest first step for building tools that can help lawyers to make faster and more accurate privilege judgments by scoring the importance of specific email addresses to determine their propensity to engage in privileged communication. Both recursive and heuristic techniques are used to estimate that propensity score, ultimately resulting a coverage of 94% of the email addresses. [ABSTRACT FROM AUTHOR]

ABSTRACT Searchers today are often faced with searching in a language that is not their native language. Searching in a foreign language will necessarily differ from searching in a native language. In this paper we examine one step of the foreign-language searching process: selection decisions about web search results. We report the results of an analysis of participant statements about why a certain web result was selected by 15 Hungarian and 15 Chinese native language speakers who searched in English. Our results confirm selection criteria from the literature and identify new selection criteria that foreign-language searchers pay attention to when selecting search results. [ABSTRACT FROM AUTHOR]

Short Text Conversation (STC) is the task of retrieving comments made to a post and reuse them as appropriate comments to a later post. Large vocabulary variations and very limited length of posts and comments pose great challenges to traditional retrieval techniques of matching terms. To address these problems, we propose a new technique of re‐ranking comments initially retrieved through explicit term matching by using evidence of implicit topic matching gained from topic models of large collections of posts and comments. The key of our technique lies in (1) combining each post with the comments responding to it into a longer pseudo‐document for topic modeling purposes, and (2) carrying out implicit topic matching by comparing the most probable topics contained in the topic composition of a comment and that of the query post. Experiments using the NTCIR‐13 STC Chinese WeiBo collection showed that with properly tuned parameters, our technique can lead to improved retrieval effectiveness. The paper analyzes and discusses the results and outlines future work. [ABSTRACT FROM AUTHOR]

This study aims to explore the transition of the term "digital library" through a thematic mapping of published literature. To reach this purpose, we conducted a network analysis on the retrieved bibliographic dataset from the Scopus database. From 985 documents total of 77 high‐frequency keywords have been selected. Co‐occurrence of the top 20 keywords has been identified to get indicative themes. Among the top 20 high‐frequency keywords, the term "human" is identified as an emerging term based on the average publication year 2017. The terms from the blue‐colored cluster are "human", "disease" "diagnosis" and many more to support information resiliency due to expanding areas in the context of the digital library. [ABSTRACT FROM AUTHOR]

Task design in interactive information retrieval (IIR) research, including IIR systems evaluation and IIR behavior research, is critical. Currently, a simple search request and a simulated work task situation design are used most widely, especially the latter. This paper attempts to examine the possible differences between simulated and real work task situations in a digital library evaluation, with respect to task characteristics, the influence of the tasks on users' interactive information search behavior, and interaction performance. An experiment was conducted. One simulated work task situation was assigned to forty-two participants and they were also asked to bring one real work task to the experiment. A set of questionnaires, including an entry questionnaire, a pre- and a post-search questionnaire were administered to the participants. An exit interview was conducted before the experiment ended. The results indicate that simulated and real work task situations are significantly different in some sub-facets of task, but not all sub-facets examined in this study. However, the influence of the two tasks on users' interactive information search behavior and interaction performance is not significant, though the subfacets of the real and simulated work task situation are correlated to interaction performance differently. Therefore, simulated work task situations could be a supplement of real work task situations in IIR evaluation if well designed. Also, the study found that for some participants, they assessed the simulated one in fact easier, but the real one in fact harder after the search. Moreover, it should be taken into account to control some critical sub-facets of task when designing simulated work task situations. The paper concludes with suggestions on designing simulated work situations in IIR research and future studies. [ABSTRACT FROM AUTHOR]

This paper presents a conceptual model for geobrowsing of text collections. The model integrates elements and principles from the existing models and adds a unique perspective on the design of representations and interactions with geographic, semantic, and cognitive spaces in geospatial visualizations. It is illustrated with examples from GeoPubMed prototype which is designed to support creative geobrowsing. [ABSTRACT FROM AUTHOR]

Query is a key component of the information retrieval process. It is a complex, multi-faceted and vague term that has been subject to a broad range of definitions. Both user-centred and system-centred models of information retrieval stress the importance and role of query in successful information retrieval experience. However, there is a lack of a rich, consistent and well-defined terminology for query. This paper proposes a new faceted classification of query in the context of interactive information retrieval and conceptualizes the many facets, aspects, characteristics and features of query based on a comprehensive analysis of the literature. The resulting classification provides a useful framework for understanding query and its various aspects for research and learning purposes. Specifically, it provides a conceptual foundation for operationalizing the many aspects and facets of query as variables for research purposes. [ABSTRACT FROM AUTHOR]

Within many domains, such as news, medicine and patent, documents contain a variety of fields such as title, author, body, source, etc. As such fielded retrieval models that query across these fields are often employed. It is largely presumed that fielding provides a better representation of the document and offers more control when querying and that this will lead to improved retrieval performance. However, depending on how the fields are weighted and if the fields are populated, the retrieval algorithm may unduly favour certain documents over others. This is known as algorithmic bias and it can be detrimental to retrieval systems performance. In this paper, we explore the impact of fielding on retrieval bias and performance across a variety of TREC News Test Collections. We perform an extensive large‐scale analysis on two types of fielded retrieval model variations that are based on the popular BM25 retrieval algorithm where either: fields are scored independently and then combined (Model 1), or fields are first combined and then scored (Model 2). Our findings show that for Model 1 fielding, a strong correlation exists between retrieval bias and performance such that as title fields are weighted more heavily, bias increases, while retrieval performance decreases. When weighting is applied to content‐based fields, performance increases as bias decreases, showing that relying more on content may be favourable in terms of fairness and performance. On the other hand, for Model 2 fielding, the relationship between retrieval bias and performance is more complex. But, crucially we show that Model 2 fielding results in lower retrieval bias and greater performance than Model 1 fielding. And, we observed that under Model 1, news articles without titles are substantially less retrievable (i.e. more susceptible to algorithmic bias). These findings have serious ramifications as many popular Open Source Information Retrieval frameworks, commonly used by professional searchers, use the default implementation of Model 1 for their fielded search capability. This research shows the importance of analysing retrieval algorithms with respect to both bias and performance to ensure they minimize any unwanted or unintended biases when maximising performance. Further work is required to examine this phenomenon in more detail and to design fielded retrieval models that have the advantages of control and performance without detrimental biases. [ABSTRACT FROM AUTHOR]

In a search process, searchers review documents to gather information relevant to their information need (IN). During this process, searchers may experience the satisfaction of their IN, indicating they have gathered adequate relevant information to answer their need. This complex concept of satisfaction is the ultimate goal of search systems. Most studies in Information Retrieval (IR) have been attempted to understand how searchers' needs are satisfied based on behavioural observation. However, the psychophysiological manifestation during the moment of satisfaction still remains unclear. Here, we use functional Magnetic Resonance (fMRI) to investigate which brain regions are involved during the moment of satisfaction. Twenty‐six participants participated in the experiment, designed to represent a search process while being scanned. Our result shows the human brain regions involved during the moment of satisfaction. These findings provide an important step in unravelling the concept of satisfaction in a search process. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, I discuss an alternative to information literacy and technical fixes for fake news and other such misleading information: the education and self-interrogation of the subject who needs information. Information has many different forms, types of truth claims and criteria for truth. Much of our daily information intake has nothing to do with true or untrue knowledge, but rather, involves tastes and opinions. If we confuse the conditions for public or learned knowledge with these, or even if we do not recognize how such knowledge also has its own institutional senses of taste, we will mislead ourselves based on false assumptions about what it is that different documents can inform us of. The subject-of-(information)-need, or the 'user,' is the bedrock notion of the subject in information retrieval, but it is constructed by the information environment it finds itself within. If the user cannot judge this environment before using it, then information literacy cannot be of enough help. [ABSTRACT FROM AUTHOR]

ABSTRACT Drawing upon research and current development work at Europeana, this paper discusses search functionality in the Cultural Heritage sector, focusing in particular on the question of 'inspiration-oriented' search, in which users seek out previously-unknown items to serve as creative stimulus. Inspiration-oriented search is identified as a variant of the more widely-studied problem of serendipitous retrieval, and defined as an information-seeking behavior in which users consciously search for items that are related to known items in ways that are recognizable once seen, but that are nevertheless unpredictable at search-time. Various strategies for the maximization of both the recognisability and unpredictability of related items are then described, including user-interface and user-experience changes and the reconceptualization of datastores as knowledge graphs. Directions for further research are then outlined - including, most importantly, possible metrics for inspiration-oriented search and their potential for use in machine-learning ranking frameworks. [ABSTRACT FROM AUTHOR]

ABSTRACT Although researchers have grappled with conceptualizations of time in relation to information behavior, the effect of time on information practices has been a challenge to study and theorize. Longitudinal naturalistic methods provide an opportunity to observe information practices in context over time, but have infrequently been used in information research. This paper presents a qualitative ethnographic exploration of the changes over time in the information practices of a group of young parents in Canada, a population experiencing substantial life changes as young adults and new parents both. Using grounded theory, this analysis explores time-related processes in the lives of young parents and they ways these processes affect information practices such as seeking, sharing, and use of information. Three case examples illustrate the interplay over time of individual characteristics, setting, and events, and the impact on an individual's information practices. Based on these findings, a theoretical model to inform future investigations of information practice evolution over time is presented. [ABSTRACT FROM AUTHOR]

ABSTRACT This paper reports the findings of research into young people's experiences of political information. We used a phenomenographic approach to identify variations in experiences of political information. The research explores how young people use information and technology to mediate political information to develop knowledge to become informed citizens. It focuses on how processes of discovery, production, retrieval, manipulation, dissemination, use, and evaluation of information are utilised in different ways by young people through a range of information behaviour techniques. 23 interviews and 3 focus groups were conducted with pupils aged 14-15 at a secondary school in England. The interviews and focus groups were recorded and transcripts and notes taken during the data collection sessions formed the data for analysis. Phenomenographic analysis was carried out, utilising manual coding and NVivo software. A phenomenographic outcome space represents the six qualitatively different ways in which the participants experienced political information, and identifies a range of political information sources, including social media and online news sources, which inform young people's political knowledge and attitudes. The outcome space illustrates the differences in ways young people experience political information and suggests potential for development to more complex ways of understanding the information they encounter. This represents a contribution to understanding the variation in information experiences and is of theoretical and practical value. [ABSTRACT FROM AUTHOR]

ABSTRACT Controlled topical vocabularies (CVs) are built into information systems to aid browsing and retrieval of items that may be unfamiliar, but it is unclear how this feature should be integrated with standard keyword searching. Few systems or scholarly prototypes have attempted this, and none have used the most widely used CV, the Library of Congress Subject Headings (LCSH), which organizes monograph collections in academic libraries throughout the world. This paper describes a working prototype of a Web application that concurrently allows topic exploration using an outline tree view of the LCSH hierarchy and natural language keyword searching of a real-world Science and Engineering bibliographic collection. Pilot testing shows the system is functional, and work to fit the complex LCSH structure into a usable hierarchy is ongoing. This study contributes to knowledge of the practical design decisions required when developing linked interactions between topical hierarchy browsing and natural language searching, which promise to facilitate information discovery and exploration. [ABSTRACT FROM AUTHOR]

ABSTRACT In this paper, we describe a quantitative study of personality aspects and their relationship with web search information behavior. We start with introducing personality and give an overview of information behavior research concerning personality aspects. In our study of 30 participants, their personality traits were operationalized by using a version of the Big 5, the B5T, a psychometric questionnaire that maps personality on different dimensions. The participants performed search tasks in a web context and data concerning their information behavior was collected via search logs as well as questionnaires. We show that there are selective correlations of slight and intermediate strength between the variables of information behavior and the personality dimensions. Finally, we discuss possible explanations and implications as well as new impulses for information behavior and retrieval research. [ABSTRACT FROM AUTHOR]

Voice search enables users to issue spoken information requests and retrieve desired information on web/mobile search interfaces. We conducted a literature review to examine the extent to which existing studies have addressed voice search behavior, with a focus on the employed methodologies and the focused topics in these studies. Fourteen relevant studies conducted since 2008 were identified from four publication databases. These studies were mainly focused on three aspects of search behavior: voice query characteristics, reformulation strategies, and users' perception/satisfaction. Our results provide a snapshot of how users perform and perceive voice search in order to inform future research and design of voice search systems. [ABSTRACT FROM AUTHOR]

Along with the massive increase of academic full texts, users now have a growing need for fine‐grained academic literature retrieval. However, few studies have attempted to build domain knowledge retrieval system for academic literature in information science. Compared with other disciplines, information science pays more attention to the domain knowledge entities sequence including data resources, models and software. To fill the gap, this paper use academic full texts from JASIST. Using SVM, Text‐CNN, Bi‐LSTM and BERT to extract the knowledge entities sequence including data resource, model, software. The highest Precision, Recall and F1 are 92.45%, 93.86% and 93.14%, respectively. And the knowledge entity sequence indexing system is built based on the extracted knowledge entities sequences. It was found that the MRR score of the knowledge entities sequence retrieval system was higher by 13% as compared with the full text retrieval system. [ABSTRACT FROM AUTHOR]

To optimize the term hierarchy in the manual e‐government thesaurus, we combine the mainstream knowledge organization technology to form a complete set of ontology automation construction scheme. We build an e‐government knowledge base by using subject words in the Comprehensive E‐government Thesaurus as the term set and encyclopedia text as the corpus. The specific work includes the extraction of semantic features from the bag‐of‐words model, determination of the number of clusters by linear and nonlinear dimensionality reduction, division of terms by spectral clustering, social network analysis to determine the class label, and storing knowledge ontology via OWL. The recall rate of term hierarchy in the ontology is excellent, indicating the ontology has good knowledge extensibility, and also proving the efficiency of the scheme proposed in this work. Besides, the application model of a term hierarchy in information retrieval can show a richer semantic relation than the original thesaurus to guide the retrieval extension of government information resources. [ABSTRACT FROM AUTHOR]

Considering the value of dates in the life cycle of the digital resource, capturing and storing dates metadata in a structured way can have a significant impact on information retrieval. There are a number of format conventions in common use for encoding the date and time values; the Extended Date/Time Format (EDTF) is one of the most expressive. This paper presents results of an exploratory analysis of representation of dates in over 8 million metadata records from one of the largest digital aggregators, Digital Public Library of America (DPLA), and compares it to EDTF specifications. This benchmark study provides empirical data - at both the individual provider level and the group level (content hubs or service hubs) - about the overall level and patterns of application of date metadata in DPLA metadata records in relation to EDTF. [ABSTRACT FROM AUTHOR]

In this paper we report results of our investigation of temporal patterns in the publication activity of authors in a research specialty. We base our analysis on Web of Science data for a field in the physical and chemical sciences from 1991-2012. We determine the research groups in the field by clustering the co-author network and generate our sample for this analysis by selecting the most productive author of each co-author cluster to represent the activity of that group. Whereas a statistical time series analysis did not reveal any specific patterns, a time series clustering approach generated a grouping of time series that correlates with the structural network position ('node role') of the respective authors in the clustered co-author network. This work is part of a long-term research project employing a mix of qualitative and network analytic methods to investigate field-specific differences in collaborative patterns. [ABSTRACT FROM AUTHOR]

Helping students better understand scientific publications is one of the essential tasks of higher education. This paper presents a novel learning/reading environment that incorporates innovative scaffolding methods that aim to enable students to readily access open educational resources (OER) and read and comprehend the paper in a collaborative reading environment within a course. The new system, OER-based Collaborative PDF Reader (OCPR), captures and characterizes students' emerging information needs when they read a paper, while also autorecommending high quality OERs, e.g., presentation videos, slides, or Wikipedia pages, when students ask for clarifying content (OER-based Scaffolding). The study was conducted in a course for students to read an article, ask questions, and rate resources suggested by the OCPR system. The preliminary results show that the students tend to ask elementary questions and rate video resources higher than other resources. The results will inform future improvement of the OCPR system. [ABSTRACT FROM AUTHOR]

Collaboration in the information seeking and retrieval environment is common, particularly when the search task is complex and exploratory. Multiple factors such as contextual features and task type can affect users' query behavior. This paper presents a study investigating the effects of collaboration and task types on users' query behavior. The study involves two conditions: collaborative search and individual search, and the two search tasks: the recall-oriented information-gathering and the utility-based decision-making. We analyze users' query behavior in three dimensions: basic query features (e.g. the number of queries), query reformulation patterns (e.g. New, Specification, Generalization and Reconstruction) and query performance. The findings of this study reveal that queries are more diverse in collaborative search and recalloriented tasks. Users employed New and Specialization more often as query reformulation types in collaborative search while people in individual search use Reconstruction more often. Besides, the successful query rate is higher in individual search and recall-oriented tasks. [ABSTRACT FROM AUTHOR]

Searching large collections of digitized books is a relatively new area in information-seeking and retrieval research, made possible by initiatives such as Google Books and the Hathi- Trust Digital Library. The availability of large full-text book collections is transforming how users search and interact with information in books, but the characteristics of these changes are unknown. This paper aims to provide insight into the characteristics of full-text searches in a large collection of digitized books and is the first step in a broader research agenda intended to improve book retrieval. To better understand the types of queries that users are issuing to full-text-book collections, we analyzed a full year of anonymized query logs from the HathiTrust Digital Library full-text search engine. We also manually classified a random sample of 600 queries to develop a taxonomy of book search query types. We found that users are beginning to search for information in books instead of searching for books. Searches still largely follow bibliographic models, but, as expected, new types of searches are beginning to take advantage of fulltext capabilities. Additionally, comparing the results of our query log analysis to searches in other domains, we found similar search patterns including short queries, sessions with only a few queries, and users viewing only a few pages of results per query. We discuss how these findings can be used to characterize users of large full-text book collections. [ABSTRACT FROM AUTHOR]

This article tackles the task of retrieving very short documents via even shorter queries. The problem on hand may relate to the retrieval of tweets, image and table captions, short text messages (SMS) and sponsored retrieval among others. In such cases, document and/or query expansion using thesauri and other external resources (e.g., Wikipedia) usually available on the World Wide Web (WWW) are proven to be effective approaches. However, the focus of this paper is on documents that are written in lesser known languages for which the WWW is of limited use. Our experiments are based on two main corpora extracted from historical manuscripts written in Latin and Middle High German. We found that retrieving very short documents whose lengths are quite similar via short queries given that no external enrichment resources are available, the classical tf-idf model performs as satisfactorily as the more complex models do, if not better sometimes. [ABSTRACT FROM AUTHOR]

In this paper, we examined the effects of information searchers' familiarity with task topics on their search behaviors, in different task types. Data were collected in a controlled laboratory experiment, participated by 32 undergraduate journalism students. Each participant searched on four tasks varying along four task facets: task product (being factual or a mix of intellectual/factual), level (the needed information being the whole document or a segment of the document), task goal (being specific, amorphous, or a mix of specific/amorphous), and complexity (being low or high). Results show that when all task types were considered together, people with different levels of topic familiarity showed differences in some search behaviors. In task types categorized by task goal and task complexity, very few behavioral variables showed differences between searchers with different levels of topic knowledge. However, in task types categorized by task product and task level, more behavioral variables showed differences between searchers with different levels of topic knowledge. Our results suggested that search behaviors may be used as implicit indicators of searchers' topic familiarity, and that task type is an important factor to consider while doing such kind of prediction. [ABSTRACT FROM AUTHOR]

In this paper, we present results of a laboratory study in which participants completed an asynchronous collaborative search task while thinking aloud. Based on analysis of the think-aloud data and screen recordings, we present a set of collaborative search actions and rationales that our participants employed. For each, we describe the purpose and motivations, and give illustrative examples. We also present three high-level strategies (independent, parallel, and divergent) that emerged from analysis of participants' verbalizations and discuss how participants used these strategies as part of their overall search process. Our results show that collaborators' prior work influenced search strategies and behaviors, and that participants leveraged collaborators' work at various stages of the interaction including query formulation and results examination. We discuss how the observed behaviors complement existing models of interactive information seeking and suggest ways to extend current models. [ABSTRACT FROM AUTHOR]

This paper describes our different retrieval approaches conducted on a cultural heritage (CH) content test-collection. In our study, our main objective is to measure the relative merit of various query expansion and semantic enrichment techniques. To do so we considered different strategies based on blind-query expansion as well as using external resource, namely Wikipedia. In using external knowledge bases we consider different strategies in order to select the most appropriate concepts to be added to the initial query. Our results show that expansion with both pseudo-relevant documents and external resources improve the retrieval. While the impact of expansion using an external resource is more significant. [ABSTRACT FROM AUTHOR]

Finding software for reuse is a problem that programmers face. To reuse code that has been proven to work can increase any programmer's productivity, benefit corporate productivity, and also increase the stability of software programs. This paper shows that fuzzy retrieval has an improved retrieval performance over typical Boolean retrieval. Various methods of fuzzy information retrieval implementation and their use for software reuse will be examined. A deeper explanation of the fundamentals of designing a fuzzy information retrieval system for software reuse will be examined. Future research options and necessary data storage systems are explored. [ABSTRACT FROM AUTHOR]

ABSTRACT This panel brings together experts in bibliometrics and information retrieval to discuss how each of these two important areas of information science can help to inform the research of the other. There is a growing body of literature that capitalizes on the synergies created by combining methodological approaches of each to solve research problems and practical issues related to how information is created, stored, organized, retrieved and used. The session will begin with an overview of the common threads that exist between IR and metrics, followed by a summary of findings from the BIR workshops and examples of research projects that combine aspects of each area to benefit IR or metrics research areas, including search results ranking, semantic indexing and visualization. The panel will conclude with an engaging discussion with the audience to identify future areas of research and collaboration. [ABSTRACT FROM AUTHOR]

Tag quality is an important factor to the success of social tagging systems and platforms. Users' domain expertise may influence they perceive tag quality. This study aims to explore how users of different domain experience (frequent user, occasional user, and non‐user) perceive the quality of the same tags. We examined an online video community, Bilibili, which specializes in Anime, Comic and Games (ACG) subculture. We asked 60 users to watch 15 videos and rate the 95 tags of these videos, and found that: 1) Users with more domain expertise give higher ratings for tags' relevance to the videos and their retrieval value; 2) Occasional users have the lowest understandability rating, followed by non‐users, and frequent users; 3) users think high‐frequency tags are less suitable for retrieval. These results may provide insights to high quality tag selection for personalized recommendation and retrieval. [ABSTRACT FROM AUTHOR]

Discovering authoritative links between publications and the datasets that they use can be a labor‐intensive process. We introduce a natural language processing pipeline that retrieves and reviews publications for informal references to research datasets, which complements the work of data librarians. We first describe the components of the pipeline and then apply it to expand an authoritative bibliography linking thousands of social science studies to the data‐related publications in which they are used. The pipeline increases recall for literature to review for inclusion in data‐related collections of publications and makes it possible to detect informal data references at scale. We contribute (1) a novel Named Entity Recognition (NER) model that reliably detects informal data references and (2) a dataset connecting items from social science literature with datasets they reference. Together, these contributions enable future work on data reference, data citation networks, and data reuse. [ABSTRACT FROM AUTHOR]

Children and youth information behavior (CYIB) research has grown substantially in the past two decades. However, this research lacks systematic analysis of the scholarly journal literature, especially with respect to theoretical applications. This study content‐analyzed articles published in fourteen key scholarly journals covering 1999 to 2019. The findings revealed that of the 893 articles retrieved from five online databases, 22.6% were relevant to theory use. Of these, 116 articles (60%) were theoretically grounded in theories or models. There was considerable growth in the use of theories as frameworks for the 2010–2019 period, as compared to the 1999–2009 period. Five key journals contributed the highest number of articles with theories or models applied as frameworks. Authors used more models than theories to ground their work. There was a frequent mention of theories or models in various sections of the articles, especially the introduction and review of the literature. The findings make a unique contribution to our understanding of the nature of theory use in CYIB research, its applications, and evolution over time, as well as strengths, weaknesses, and trends. This study has implications for LIS education, research, and practice. It also has theoretical and methodological implications. [ABSTRACT FROM AUTHOR]

Despite the advanced information technology's impact on the extent and availability of digital information, information access is not equally attainable to everyone. The lack of cultural and linguistic diversity in information systems and infrastructure has raised concerns over limited access to digital information, which also harms the information environment. For example, a flood of misinformation and disinformation during the pandemic rendered misrepresentation of cultures and fed the fear of people from different cultures. The "deep learning" revolution has enabled advances in cross‐language search technology and in automated translation of content from one language to another, but the lowering of linguistic barriers to information access, in turn, serves to highlight the need for a comparable degree of focus on cultural differences. The proposed panel will discuss cultural and linguistic diversity as manifested in various information systems and infrastructures and review past and current information systems and practices either lacking or supporting cultural and linguistic diversity. [ABSTRACT FROM AUTHOR]

Along with the development of the data‐driven research paradigm, there are exponentially increasing datasets, which bring challenges to researchers in the efficient retrieval of relevant datasets. Previous studies mainly focused on query expansion methods based on sparse retrieval models to improve the accuracy and recall in retrieval. We investigated the use of semantically rich information to retrieve relevant datasets and the benefits of using domain‐specific dense vector representation as opposed to general representation. First, we used pairs of metadata fields that have semantic relevance to construct the domain‐specific weakly supervised training data. Then, a pre‐trained transformer‐based deep learning model is fine‐tuned on the training data using the contrastive learning method. Finally, dense vector representations of the queries and datasets are obtained based on the fine‐tuned model. The relevance of a dataset to a query is measured by the similarity between the vectors. To evaluate the performance of the proposed model, we collected 104,683 datasets from 13 research data repositories, recruited volunteers to design research‐oriented queries, and annotated the retrieval results. The experimental results show that compared with the domain‐independent fine‐tuned model, our proposed method can improve the NDCG@10 score by about 5%. [ABSTRACT FROM AUTHOR]

This paper describes the results of a large survey designed to quantify the final disposition of research data and to determine the extent that the key factors of repository technologies and data management resources influence the decisions that researchers make about their data. A total of 724 National Science Foundation awardees completed this survey. Removable media devices such as CDs, DVDs, and removable hard drives are the most common storage technologies. Less than 30% of researchers use community or reference repositories. More than half of the researchers get storage through their institutions. Institutional support for storage is significantly higher than for data management. The key finding of this research is that the availability of resources is the most significant indicator of whether the final deposition of data is in a preservationworthy manner. Resources, provided by the research institution or via grant funding, include storage technologies, repository systems, and data management personnel. When high quality data storage is offered, researchers will use it. When professional data managers are available, data is more likely to be stored in more sustainable technologies. [ABSTRACT FROM AUTHOR]

Collaborative search is concerned with how people work together to address a common information need. In this paper, we investigate two factors that may influence collaborative search behaviors: providing awareness information about collaborators' prior activities, and the orientation of the shared task. For awareness, we examined two levels: an aware condition in which participants could see their collaborators' prior activity in the system, and a non-aware condition in which they could only see their own history. For orientation, we investigated a task with an open set of goals compared to a recall-oriented task that asked participants to find as many relevant documents as possible. Forty-one participants in a laboratory study used a prototype system called Results Space to complete an asynchronous collaborative search task with three simulated collaborators. We developed a novel set of measures for examining collaborative behavior, and found that participants who were aware of their collaborators' prior actions issued more query terms in common with their collaborators and tended to avoid rating or viewing documents that collaborators had already rated as compared to the non-aware group. We also observed an interaction between awareness and task-orientation in terms of the number of unique documents found, suggesting that task orientation could change the direction of the effect of awareness on document space exploration. [ABSTRACT FROM AUTHOR]

Many websites employ social tagging to allow users to label and classify information. These tagging user interfaces use a variety of features to support efficient and consistent tag creation, including suggested tags and autocomplete for tags. This study uses a custom‐built tagging interface in a controlled experiment to determine how these features affect social tagging behavior. The study finds that suggested tags do not have a significant effect on the number of tags, number of unique tags, number of typos, or time elapsed per tagged provided. However, autocomplete significantly increases the number and consistency of tags provided, significantly decreases the rate of typos, and significantly decreases the elapsed time per tag provided. These findings for the autocomplete feature align with the priorities and constraints of social tagging folksonomies that support retrieval and site navigation and suggest that autocomplete is an important aid for text entry in social tagging user interfaces. [ABSTRACT FROM AUTHOR]

Keeping informed given rapid trend in data and resources about covid‐19 is a new challenge. Different user groups (researchers/doctors, practitioners, public) vary in linguistic expression and vocabulary so a new retrieval framework might likewise vary to improve retrieval, expose unanticipated concepts, and establish a sustainable research stream. In this project a document collection about covid‐19 was created, parsed according to ISO12620's definition of linguistic register, and retrieval sets compared. Results suggest trends from other fields parallel register‐oriented criteria; project exposes unexpected concepts across groups, uses of visualization, and warrants ling‐register as a sustainable IR research stream. [ABSTRACT FROM AUTHOR]

The search functionalities that a search tool for a digital text collection offer, will determine how a user can interact with and search in such a collection. This poster considers the search functionalities in four tools that are used to search within digital text collections. Search functionalities that are well known in information science, namely basic word searching, phrase searching, wildcards, Boolean operators, proximity searching, field searching, case sensitive searching, filtering, as well as linguistic search functions will be considered. Knowledge about search functionalities can inform and improve the design of tools for digital text collections. [ABSTRACT FROM AUTHOR]