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ABSTRACT This paper proposes a 'rough co-citation', which is a measure of relationship to expand co-citation networks so as to include new relevant documents. A rough co-citation relationship is a linkage between a pair of documents which are cited by two other documents in a similar citation context. The linkage strength of a rough co-citation relationship may be weaker than the original co-citation relationship, because a rough co-citation relationship is determined by citations in two separate documents. Rough co-citation linkages, however, may yield new relevant documents that are not identified by the original co-citation linkages. For example, the rough co-citation can identify relevant documents that are published after the citing document of the original co-citation becomes public. This study conducted IR experiments to evaluate the search performances of retrieval methods using the co-citation networks expanded by the rough co-citation relationships. Specifically, the random walk with restart, which is one of the latest graph search algorithms, is applied to the expanded and original co-citation networks. Scores of the normalized discounted cumulative gain (nDCG@K) are then compared. The results indicate that the search performance of the method using the expanded network outperforms a baseline method using the original network. [ABSTRACT FROM AUTHOR]

This study analyzes the relation between author affiliation reputation and uncitedness. We use 2015 U.S. News Best Global University Subject rankings as representative of affiliation reputation and collect uncited papers from 24 journals in six subjects from WoS. Preliminary correlation analysis results indicate that: (1) there is a significant correlation between affiliation reputation and uncitedness. (2) their relation is negatively and weakly correlated. And secondary data collection and correlation analysis proved that relation between affiliation reputation and uncitedness vary in different subjects. The findings of this study would attract scientists' attention to avoid Matthew Effect and focus more on research papers rather than reputation when citing references. [ABSTRACT FROM AUTHOR]

Researchers in academia and industry face a deluge of data in our digital world. In this paper, we investigate a novel problem, query-centric scientific topic evolution. Using heterogeneous graph mining techniques we construct a topic evolution tree (TET) from massive collections of scientific publications, enabling students and researchers to explore the foundation of research topics outside their specialization. Prior research has focused mainly on citation relationships; in this study we employed multiple types of relationships, including authorship, citation, publishing venue, and the contributions authors, papers, and venues have made to a specific topic. We examine multiple restricted meta-paths in constructing a TET covering topics from the MeSH vocabulary for biomedical research. [ABSTRACT FROM AUTHOR]

Citation analyses are used to investigate the influence of architect Christopher Alexander over the period of 1964- 2014. Alexander's work has been so influential that he has been cited by nearly 2000 source items in the Web of Science Core Collection, by Thomson Reuters. Alexander's work has had a profound interdisciplinary reach. Citation analyses reveal that scholars in computing disciplines have cited Alexander's work more than scholars in any other discipline including architecture. Alexander's most cited work, A Pattern Language, is one of two volumes that Alexander refers to as an indivisible whole. These analyses reveal very different citation patterns for the two volumes of this indivisible whole. Although the difference is measurable, in terms of number of citations, we cannot say why this is so. However, the results of these analyses raise several questions including why we, as a community, have for the most part cited only a piece of this indivisible whole. The citation patterns support that this series has been largely reduced to one of its parts, when possibly the whole is greater than the sum of its parts or one of its parts. In this paper I propose that we might begin to see the potential benefits of pattern languages in computing disciplines when we take holistic approach, considering and applying the theory as described in all of the volumes in the series. [ABSTRACT FROM AUTHOR]

Despite the emergence of e-learning trends, the author cocitation analysis (ACA) method has not yet been used to analyze e-learning extensively. This study applies ACA to analyze the collected literature on e-learning from 1981- 2015, with the goal of identifying the top intellectual areas in three time periods - 1981-1991, 1992-2002, and 2003-2014 - to provide a reference framework for future researchers. Therefore, the objective of this paper is to construct an intellectual framework in the field of e-learning. [ABSTRACT FROM AUTHOR]