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Death is an inevitable part of life and highly relevant to information management: its approach often requires preparation, and its occurrence often demands a response. Many works in information science have acknowledged so much, and yet death is rarely a focused topic, appearing instead sporadically and disconnected across research. As a result there is no introduction to, overview of, or synthesis across studies on death and information. We therefore conducted an extensive literature search and reviewed nearly 300 scholarly publications at the intersection of death and information (and data) management. Covering seven topics in total, we review two groups of work directly engaging information management in relation to death (digital possessions, inheritance, and legacy; information behavior, needs, and practices around death), three engaging death and technology that require information and its management (death and the Internet, thanatosensitive design and technology‐augmented death practices, and the digital afterlife and digital immortality), and two reflecting the ethical and legal dimensions unique to death and information. We then integrate the collective findings to summarize the landscape of death‐related information research, outline remaining challenges for individuals, families, institutions, and society, and identify promising directions for future information science research. [ABSTRACT FROM AUTHOR]

With the wide application of keyphrases in many Information Retrieval (IR) and Natural Language Processing (NLP) tasks, automatic keyphrase prediction has been emerging. However, these statistically important phrases are contributing increasingly less to the related tasks because the end‐to‐end learning mechanism enables models to learn the important semantic information of the text directly. Similarly, keyphrases are of little help for readers to quickly grasp the paper's main idea because the relationship between the keyphrase and the paper is not explicit to readers. Therefore, we propose to generate keyphrases with specific functions for readers to bridge the semantic gap between them and the information producers, and verify the effectiveness of the keyphrase function for assisting users' comprehension with a user experiment. A controllable keyphrase generation framework (the CKPG) that uses the keyphrase function as a control code to generate categorized keyphrases is proposed and implemented based on Transformer, BART, and T5, respectively. For the Computer Science domain, the Macro‐avgs of P@5, R@5, and F1@5 on the Paper with Code dataset are up to 0.680, 0.535, and 0.558, respectively. Our experimental results indicate the effectiveness of the CKPG models. [ABSTRACT FROM AUTHOR]

The paper reports a longitudinal analysis of the topical and methodological development of Library and Information Science (LIS). Its focus is on the effects of researchers' disciplines on these developments. The study extends an earlier cross‐sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706–1722) by a coordinated dataset representing a content analysis of articles published in 31 scholarly LIS journals in 1995, 2005, and 2015. It is novel in its coverage of authors' disciplines, topical and methodological aspects in a coordinated dataset spanning two decades thus allowing trend analysis. The findings include a shrinking trend in the share of LIS from 67 to 36% while Computer Science, and Business and Economics increase their share from 9 and 6% to 21 and 16%, respectively. The earlier cross‐sectional study (Vakkari et al., Journal of the Association for Information Science and Technology, 2022a, 73, 1706–1722) for the year 2015 identified three topical clusters of LIS research, focusing on topical subfields, methodologies, and contributing disciplines. Correspondence analysis confirms their existence already in 1995 and traces their development through the decades. The contributing disciplines infuse their concepts, research questions, and approaches to LIS and may also subsume vital parts of LIS in their own structures of knowledge production. [ABSTRACT FROM AUTHOR]

Main path analysis is a popular method for extracting the scientific backbone from the citation network of a research domain. Existing approaches ignored the semantic relationships between the citing and cited publications, resulting in several adverse issues, in terms of coherence of main paths and coverage of significant studies. This paper advocated the semantic main path network analysis approach to alleviate these issues based on citation function analysis. A wide variety of SciBERT‐based deep learning models were designed for identifying citation functions. Semantic citation networks were built by either including important citations, for example, extension, motivation, usage and similarity, or excluding incidental citations like background and future work. Semantic main path network was built by merging the top‐K main paths extracted from various time slices of semantic citation network. In addition, a three‐way framework was proposed for the quantitative evaluation of main path analysis results. Both qualitative and quantitative analysis on three research areas of computational linguistics demonstrated that, compared to semantics‐agnostic counterparts, different types of semantic main path networks provide complementary views of scientific knowledge flows. Combining them together, we obtained a more precise and comprehensive picture of domain evolution and uncover more coherent development pathways between scientific ideas. [ABSTRACT FROM AUTHOR]

This article considers the interdisciplinary opportunities and challenges of working with digital cultural heritage, such as digitized historical newspapers, and proposes an integrated digital hermeneutics workflow to combine purely disciplinary research approaches from computer science, humanities, and library work. Common interests and motivations of the above‐mentioned disciplines have resulted in interdisciplinary projects and collaborations such as the NewsEye project, which is working on novel solutions on how digital heritage data is (re)searched, accessed, used, and analyzed. We argue that collaborations of different disciplines can benefit from a good understanding of the workflows and traditions of each of the disciplines involved but must find integrated approaches to successfully exploit the full potential of digitized sources. The paper is furthermore providing an insight into digital tools, methods, and hermeneutics in action, showing that integrated interdisciplinary research needs to build something in between the disciplines while respecting and understanding each other's expertise and expectations. [ABSTRACT FROM AUTHOR]

Background: Both PubMed and Ovid MEDLINE contain records from the MEDLINE database. However, there are subtle differences in content, functionality, and search syntax between the two. There are many instances in which researchers may wish to search both interfaces, such as when conducting supplementary searching for a systematic review to retrieve a unique content from PubMed or when using a previously published search strategy from a different interface, but little guidance on how to best conduct these searches. The aim of this project is to describe differences in search functionality between Ovid MEDLINE and PubMed, provide guidance for converting search strategies between the two, and develop an easy‐to‐use, freely available web‐based tool to automate search syntax translations. Case presentation: In this paper, we present a custom‐built freely available online tool, Medline Transpose, to streamline the process of converting search strategies between Ovid MEDLINE and PubMed. With this tool, users can paste a strategy formatted for one interface into the search box and immediately retrieve an output formatted for use in the other interface, with recommendations for changes that users can make to the strategy where an exact translation does not exist. Conclusion: This novel approach has the potential to reduce time and errors that database users spend translating search strategies. [ABSTRACT FROM AUTHOR]

A highlight of the 2012 ASIS&T Annual Meeting, the pre-conference session on the History of ASIS&T and Information Science and Technology Worldwide drew presenters and attendees from around the globe. The day featured papers on four historical themes, starting with the institutional roots of ASIS&T and recognizing decades of research presented in the Annual Review of Information Science and Technology. The evolution of the field was apparent through a review of information revolutions prompted by the printing press, the post-World War II information crisis and the Internet, as well as through presentations on digital curation,ongoing work on relevance, sense-making theory and developments from Croatia to France.Discussion of the historical contexts of technology innovations and impacts consideredphotographic documentary techniques, binary computing and networking standards. The development of foundational ideas was explored through presentations on pioneering document indexing methods, the semantic challenge of term-oriented retrieval, early European perceptions of classification systems and the French view of communication and information science. Efforts to deepen the historical understanding of information science and technology will continue through oral history interviews, funded research and awards for outstanding papers [ABSTRACT FROM AUTHOR]

In 1975 Tefko Saracevic declared “the subject knowledge view” to be the most fundamental perspective of relevance. This paper examines the assumptions in different views of relevance, including “the system's view” and “the user's view” and offers a reinterpretation of these views. The paper finds that what was regarded as the most fundamental view by Saracevic in 1975 has not since been considered (with very few exceptions). Other views, which are based on less fruitful assumptions, have dominated the discourse on relevance in information retrieval and information science. Many authors have reexamined the concept of relevance in information science, but have neglected the subject knowledge view, hence basic theoretical assumptions seem not to have been properly addressed. It is as urgent now as it was in 1975 seriously to consider “the subject knowledge view” of relevance (which may also be termed “the epistemological view”). The concept of relevance, like other basic concepts, is influenced by overall approaches to information science, such as the cognitive view and the domain-analytic view. There is today a trend toward a social paradigm for information science. This paper offers an understanding of relevance from such a social point of view. [ABSTRACT FROM AUTHOR]

The amount of knowledge accumulated in published scientific papers has increased due to the continuing progress being made in scientific research. Since numerous papers have only reported fragments of scientific facts, there are possibilities for discovering new knowledge by connecting these facts. We therefore developed a system called BioTermNet to draft a conceptual network with hybrid methods of information extraction and information retrieval. Two concepts are regarded as related in this system if (a) their relationship is clearly described in MEDLINE abstracts or (b) they have distinctively co-occurred in abstracts. PRIME data, including protein interactions and functions extracted by NLP techniques, are used in the former, and the Singhal-measure for information retrieval is used in the latter. Relationships that are not clearly or directly described in an abstract can be extracted by connecting multiple concepts. To evaluate how well this system performs, Swanson's association between Raynaud's disease and fish oil and that between migraine and magnesium were tested with abstracts that had been published before the discovery of these associations. The result was that when start and end concepts were given, plausible and understandable intermediate concepts connecting them could be detected. When only the start concept was given, not only the focused concept (magnesium and fish oil) but also other probable concepts could be detected as related concept candidates. Finally, this system was applied to find diseases related to the BRCA1 gene. Some other new potentially related diseases were detected along with diseases whose relations to BRCA1 were already known. The BioTermNet is available at http://btn.ontology.ims.u-tokyo.ac.jp. [ABSTRACT FROM AUTHOR]

Research patterns could enhance understanding of the Information Systems (IS) field. Citation analysis is the methodology commonly used to determine such research patterns. In this study, the citation methodology is applied to one of the top-ranked Information Systems conferences—International Conference on Information Systems (ICIS). Information is extracted from papers in the proceedings of ICIS 2000 to 2002. A total of 145 base articles and 4,226 citations are used. Research patterns are obtained using total citations, citations per journal or conference, and overlapping citations. We then provide the citation ranking of journals and conferences. We also examine the difference between the citation ranking in this study and the ranking of IS journals and IS conferences in other studies. Based on the comparison, we confirm that IS research is a multidisciplinary research area. We also identify the most cited papers and authors in the IS research area, and the organizations most active in producing papers in the top-rated IS conference. We discuss the findings and implications of the study. [ABSTRACT FROM AUTHOR]

As retrieval set size in information retrieval (IR) becomes larger, users may need greater interactive opportunities to determine for themselves potential relevance of the resources offered by a given collection. A parts-of-document approach, coupled with an interactive graphic interface and control panel, permits end users to tailor the information seeking (IS) session. Applying the model described by the author in a previous paper in this journal, this paper explores two issues: whether a group of information seekers in the same research domain will want to use this type of IR interaction, and whether such interaction is more successful than relevancy ranked lists, based on the general vector model. In addition, the paper proposes the use of gradient space as a means of capturing end users' cognitive states-decision-making points- during a parts-of-document-based lR session. It concludes that, for a group of biomedical researchers, a parts-of-document approach is preferred for certain IR situations and that gradient space provides designers of systems with empirical evidence suited for systems analysis.

This paper revises David Ellis's information-seeking behavior model of social scientists, which includes six generic features: starting, chaining, browsing, differentiating, monitoring, and extracting. The paper uses social science faculty researching stateless nations as the study population. The description and analysis of the information-seeking behavior of this group of scholars is based on data collected through structured and semistructured electronic mail interviews. Sixty faculty members from 14 different countries were interviewed by e-mail. For reality check purposes, face-to-face interviews with five faculty members were also conducted. Although the study confirmed Ellis's model, it found that a fuller description of the information-seeking process of social scientists studying stateless nations should include four additional features besides those identified by Ellis. These new features are: accessing, networking, verifying, and information managing. In view of that, the study develops a new model, which, unlike Ellis's, groups all the features into four interrelated stages: searching, accessing, processing, and ending. This new model is fully described and its implications on research and practice are discussed. How and why scholars studied here are different than other academic social scientists is also discussed. [ABSTRACT FROM AUTHOR]

Looking for ontology in a search engine, one can find so many different approaches that it can be difficult to understand which field of research the subject belongs to and how it can be useful. The term ontology is employed within philosophy, computer science, and information science with different meanings. To take advantage of what ontology theories have to offer, one should understand what they address and where they come from. In information science, except for a few papers, there is no initiative toward clarifying what ontology really is and the connections that it fosters among different research fields. This article provides such a clarification. We begin by revisiting the meaning of the term in its original field, philosophy, to reach its current use in other research fields. We advocate that ontology is a genuine and relevant subject of research in information science. Finally, we conclude by offering our view of the opportunities for interdisciplinary research. [ABSTRACT FROM AUTHOR]

In both the popular press and scholarly research, digital information is persistently discussed in terms that imply its immateriality. In this characterization, the digital derives its power from its nature as a mere collection of 0s and 1s wholly independent from the particular media on which it is stored-hard drive, network wires, optical disk, etc.-and the particular signal carrier which encodes bits-variations of magnetic field, voltages, or pulses of light. This purported immateriality endows bits with considerable advantages: they are immune from the economics and logistics of analog media, and from the corruption, degradation, and decay that necessarily result from the handling of material carriers of information, resulting in a worldwide shift 'from atom to bits' as captured by Negroponte. This is problematic: however immaterial it might appear, information cannot exist outside of given instantiations in material forms. But what might it mean to talk of bits as material objects? In this paper I argue that bits cannot escape the material constraints of the physical devices that manipulate, store, and exchange them. Such an analysis reveals a surprising picture of computing as a material process through and through. [ABSTRACT FROM AUTHOR]

Automatic document categorization is an important research problem in Information Science and Natural Language Processing. Many applications, including, Word Sense Disambiguation and Information Retrieval in large collections, can benefit from such categorization. This paper focuses on automatic categorization of documents from the biomedical literature into broad discipline-based categories. Two different systems are described and contrasted: CISMeF, which uses rules based on human indexing of the documents by the Medical Subject Headings (MeSH) controlled vocabulary in order to assign metaterms (MTs), and Journal Descriptor Indexing (JDI), based on human categorization of about 4,000 journals and statistical associations between journal descriptors (JDs) and textwords in the documents. We evaluate and compare the performance of these systems against a gold standard of humanly assigned categories for 100 MEDLINE documents, using six measures selected from trec_eval. The results show that for five of the measures performance is comparable, and for one measure JDI is superior. We conclude that these results favor JDI, given the significantly greater intellectual overhead involved in human indexing and maintaining a rule base for mapping MeSH terms to MTs. We also note a JDI method that associates JDs with MeSH indexing rather than textwords, and it may be worthwhile to investigate whether this JDI method (statistical) and CISMeF (rule-based) might be combined and then evaluated showing they are complementary to one another. [ABSTRACT FROM AUTHOR]

This paper studies how varied damping factors in the PageRank algorithm influence the ranking of authors and proposes weighted PageRank algorithms. We selected the 108 most highly cited authors in the information retrieval (IR) area from the 1970s to 2008 to form the author co-citation network. We calculated the ranks of these 108 authors based on PageRank with the damping factor ranging from 0.05 to 0.95. In order to test the relationship between different measures, we compared PageRank and weighted PageRank results with the citation ranking, h-index, and centrality measures. We found that in our author co-citation network, citation rank is highly correlated with PageRank with different damping factors and also with different weighted PageRank algorithms; citation rank and PageRank are not significantly correlated with centrality measures; and h-index rank does not significantly correlate with centrality measures but does significantly correlate with other measures. The key factors that have impact on the PageRank of authors in the author co-citation network are being co-cited with important authors. [ABSTRACT FROM AUTHOR]

Information is often organized as a text hierarchy. A hierarchical text-classification system is thus essential for the management, sharing, and dissemination of information. It aims to automatically classify each incoming document into zero, one, or several categories in the text hierarchy. In this paper, we present a technique called CRHTC (context recognition for hierarchical text classification) that performs hierarchical text classification by recognizing the context of discussion (COD) of each category. A category's COD is governed by its ancestor categories, whose contents indicate contextual backgrounds of the category. A document may be classified into a category only if its content matches the category's COD. CRHTC does not require any trials to manually set parameters, and hence is more portable and easier to implement than other methods. It is empirically evaluated under various conditions. The results show that CRHTC achieves both better and more stable performance than several hierarchical and nonhierarchical text-classification methodologies. [ABSTRACT FROM AUTHOR]

A brief communication appearing in this journal ranked UK-based LIS and (some) IR academics by their h-index using data derived from the Thomson ISI Web of Science™ (WoS). In this brief communication, the same academics were re-ranked, using other popular citation databases. It was found that for academics who publish more in computer science forums, their h was significantly different due to highly cited papers missed by WoS; consequently, their rank changed substantially. The study was widened to a broader set of UK-based LIS and IR academics in which results showed similar statistically significant differences. A variant of h, hmx, was introduced that allowed a ranking of the academics using all citation databases together. [ABSTRACT FROM AUTHOR]

Aim: To review the literature on the positive impact of information services, or information resources, on patient care in primary care. Objectives: To identify and summarize key papers on which librarians might draw in making the case for investment, and to highlight gaps in the research evidence Methodology: A rapid literature review was conducted in the summer of 2005. Results: There is a small body of evidence to demonstrate the positive impact of library and information services on the direct care of patients as well as a beneficial impact on the care of future patients through the application of evidence to multiple patients. Conclusions: There is relatively limited research evidence of the impact of information, and library services, in primary care, in comparison with hospital settings and the research available is generally reliant on small samples. There is a lack of impact studies conducted with non-clinical staff. The review highlights the value of critical incident technique (CIT). It is possible to gather evidence of the potential for information services to deliver cost savings. [ABSTRACT FROM AUTHOR]

A new document representation model is presented in this paper. This model is based on the idea of representing a document by two or more pictures of the document taken from different perspectives. It is shown that by applying the stereo representation model, enhanced textual retrieval performance is achieved because the new model improves the capability of capturing individual features of the document. Experiments have been conducted on two standard corpora, TIME and ADI, using the standard term vector method and the latent semantic indexing (LSI) method based upon both the stereo representation model and the traditional representation model. Statistical t-tests on the experimental results have convincingly illustrated that these methods achieve significant improvements in retrieval performances with the stereo representation model over those with the traditional representation model. [ABSTRACT FROM AUTHOR]

This article describes the aims and objectives of the Text REtrieval Conference (TREC) workshops and its impact in the areas of retrieval system effectiveness, retrieval system evaluation, and support of new retrieval tasks. The first TREC workshop was held in November 1992, and there has been a workshop held annually since then. The cumulative effort represented by the TREC is significant. Approximately 250 distinct groups representing more than 20 different countries have participated in at least one TREC, thousands of individual retrieval experiments have been performed and hundreds of papers have been published in the TREC proceedings. The TREC's impact on information retrieval research has been equally significant. A variety of large test collections have been built for both traditional ad hoc retrieval and new tasks such as cross-language retrieval, speech retrieval and question answering. The TREC has standardized the evaluation methodology used to assess the quality of retrieval results and, through the large repository of retrieval runs, demonstrated both the validity and efficacy of the methodology.

In this paper, it is suggested that a number of theoretical and practical perspectives on information literacy can be obtained through the examination of tenets of cognitive psychology. One aspect of cognitive psychology-information processing theory--is applied to the development of a two-stage model of the information retrieval process. This model of information retrieval has utility along two dimensions: firstly, in the conceptualization of the information retrieval process; and secondly, in the development of teaching strategies informed by such a model. The efficacy of this model was tested in a large two-phase experimental study at the University of Canberra, Australia. Statistically significant results support the effectiveness of the concept-based teaching of information retrieval and the utility of the model as an explanation of the cognitive underpinnings of information retrieval. [ABSTRACT FROM AUTHOR]

Web citations have been proposed as comparable to, even replacements for, bibliographic citations, notably in assessing the academic impact of work in promotion and tenure decisions. We compared bibliographic and Web citations to articles in 46 journals in library and information science. For most journals (57%), Web citations correlated significantly with both bibliographic citations listed in the Social Sciences Citation Index and the ISI's Journal Impact Factor. Many of the Web citations represented intellectual impact, coming from other papers posted on the Web (30%) or from class readings lists (12%). Web citation counts were typically higher than bibliographic citation counts for the same article. Journals with more Web citations tended to have Web sites that provided tables of contents on the Web, while less cited journals did not have such publicity. The number of Web citations to journal articles increased from 1992 to 1997. [ABSTRACT FROM AUTHOR]

Type/Token-Taken informetrics is a new part of informetrics that studies the use of items rather than the items itself. Here, items are the objects that are produced by the sources (e.g., journals producing articles, authors producing papers, etc.). In linguistics a source is also called a type (e.g., a word), and an item a token (e.g., the use of words in texts). In informetrics, types that occur often, for example, in a database will also be requested often, for example, in information retrieval. The relative use of these occurrences will be higher than their relative occurrences itself; hence, the name Type/ Token-Taken informetrics. This article studies the frequency distribution of Type/Token-Taken informetrics, starting from the one of Type/Token informetrics (i.e., source-item relationships). We are also studying the average number µ[sup *] of item uses in Type/Token-Taken informetrics and compare this with the classical average number µ in Type/Token informetrics. We show that µ[sup *] ≥ µ always, and that µ[sup *] is an increasing function of µ. A method is presented to actually calculate µ[sup *] from µ, and a given α, which is the exponent in Lotka's frequency distribution of Type/Token informetrics. We leave open the problem of developing non-Lotkaian Type/TokenTaken informetrics. [ABSTRACT FROM AUTHOR]

In this paper, we present five user experiments on incorporating behavioral information into the relevance feedback process. In particular, we concentrate on ranking terms for query expansion and selecting new terms to add to the user's query. Our experiments are an attempt to widen the evidence used for relevance feedback from simply the relevant documents to include information on how users are searching. We show that this information can lead to more successful relevance feedback techniques. We also show that the presentation of relevance feedback to the user is important in the success of relevance feedback. [ABSTRACT FROM AUTHOR]

The article describes the type of paper submissions that will be accepted by the program committee of the American Society for Information Science and Technology. There are four types of paper submissions: 1) contributed papers; 2) contributed posters and short papers; 3) symposia and panels; and, 4) pre-conference sessions. For instance, contributed papers present original, recent research and design projects, and theoretical developments or innovative practical applications providing more general insight into an area of practice.

This article presents information about the articles published in this issue of the "Journal of the American Society for Information Science and Technology." Diaz and others describe Normalizer, which is a conflation or stemming algorithm that stores its prefixes and suffixes in tree structures to reduce required space and complexity. In a new bibliometric model by Huber, he assumes that the author productivity rate follows the Generalized Pareto distribution, that the author's career duration follows an exponential distribution, that productivity and career duration are related, and that publications are distributed across the career duration in a Poisson manner. An experiment conducted by Zhang in which 56 student volunteers were tested for in various categories for their effect on search performance as measured by collaborative relevance score on four questions each participant searched. A paper by Burrell calculated the probability that a paper will ever be cited assuming it has not been cited in a given time.

This article presents information on Paperbase De Luxe, a computer program. Paperbase De Luxe is a program for the storage, retrieval and presentation of bibliographic information. It is a computer equivalent of a reference card system that lists the authors, titles and publication details as well as notes and abstracts about books and journal papers that one has to read. It is a set of seven linked programs which are best described in the order in which one is most likely to use them. It is a program which is still being developed in 1987 but already in its current form can offer considerable savings in time and effort.

This article presents abstracts of research papers related to information science. A study titled "Role-Related Library Use by Local Union Officials," by M.A. Chaplan and E.J. Hertenstem, presents information on a group of library users that have not been studied in decades and relates their library use to their union roles. The study collected specific information about library use, both in order to understand their information-seeking behavior and also in order to learn how to improve library service to this group. It also proposes a possible model for union officials' information-seeking behavior with directions for further research to determine the applicability of the model. Another study "Web Citation Data for Impact Assessment: A Comparison of Four Science Disciplines," by L. Vaughan and D. Shaw, sampled 5,972 articles published in 114 journals covering four science disciplines. The researchers searched for Web citations to these articles and found that the numbers of citations correlated.

This article presents news briefs related to the American Society for Information Science and Technology's members and chapters. Special Interest Group (SIG)/International Information Issues raised over $7000 in just two months this spring for the 6th International Paper Contest on International Digital Libraries and Information Science and Technology Advances in Developing Countries. With fundraising a continuing process, SIG officials expressed pleasure and expectation for ongoing support from the information community. For its June 2005 meeting, the Los Angeles Chapter of the American Society for Information Science and Technology combined a professional development workshop on Personal Knowledge Management: Coping with Information Overload with a business meeting. Karen Fisher, Joan Durrance and Marian Bouch Hinton are the winners of ALA's 2005 Jesse H. Shera Award for Distinguished Published Research, for their article "Information Grounds and the Use of Need-based Services by Immigrants in Queens, NY: A Context-based, Outcome Evaluation Approach."

In this issue of the "Journal of the American Society Information Science and Technology " the special topics editor will introduce the five papers that comprise the majority of this issue. A Biology domain was created from 74 documents yielding 953 descriptors after manual removal of a small set of spurious descriptors and manual addition of about 30% of the set. Some clusters were considered effective, others not. The automatic selection of root terms was successful in only 25% of the cases despite the use of seven different classification methods. The scholars look at the effectiveness of fusing various effective methods of assigning similarity between a document and a query in a single retrieval system, while holding all other variables constant.