Journal•ISSN: 1532-2882
Journal of the Association for Information Science and Technology
About: Journal of the Association for Information Science and Technology is an academic journal. The journal publishes majorly in the area(s): Information system & Information science. It has an ISSN identifier of 1532-2882. Over the lifetime, 5994 publication(s) have been published receiving 268327 citation(s). The journal is also known as: American Society for Information Science and Technology. Journal & Journal of the American Society for Information Science and Technology.
Topics: Information system, Information science, Relevance (information retrieval), Citation analysis, Information seeking
Papers published on a yearly basis
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TL;DR: A new method for automatic indexing and retrieval to take advantage of implicit higher-order structure in the association of terms with documents (“semantic structure”) in order to improve the detection of relevant documents on the basis of terms found in queries.
Abstract: A new method for automatic indexing and retrieval is described. The approach is to take advantage of implicit higher-order structure in the association of terms with documents (“semantic structure”) in order to improve the detection of relevant documents on the basis of terms found in queries. The particular technique used is singular-value decomposition, in which a large term by document matrix is decomposed into a set of ca. 100 orthogonal factors from which the original matrix can be approximated by linear combination. Documents are represented by ca. 100 item vectors of factor weights. Queries are represented as pseudo-document vectors formed from weighted combinations of terms, and documents with supra-threshold cosine values are returned. initial tests find this completely automatic method for retrieval to be promising.
12,005 citations
TL;DR: Experiments on large coauthorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures.
Abstract: Given a snapshot of a social network, can we infer which new interactions among its members are likely to occur in the near future? We formalize this question as the link-prediction problem, and we develop approaches to link prediction based on measures for analyzing the “proximity” of nodes in a network. Experiments on large coauthorship networks suggest that information about future interactions can be extracted from network topology alone, and that fairly subtle measures for detecting node proximity can outperform more direct measures. © 2007 Wiley Periodicals, Inc.
3,793 citations
TL;DR: A new form of document coupling called co-citation is defined as the frequency with which two documents are cited together, and clusters of co- cited papers provide a new way to study the specialty structure of science.
Abstract: A new form of document coupling called co-citation is defined as the frequency with which two documents are cited together. The co-citation frequency of two scientific papers can be determined by comparing lists of citing documents in the Science Citation Index and counting identical entries. Networks of co-cited papers can be generated for specific scientific specialties, and an example is drawn from the literature of particle physics. Co-citation patterns are found to differ significantly from bibliographic coupling patterns, but to agree generally with patterns of direct citation. Clusters of co-cited papers provide a new way to study the specialty structure of science. They may provide a new approach to indexing and to the creation of SDI profiles.
3,042 citations
TL;DR: A model of the information search process is presented derived from a series of five studies investigating common experiences of users in information seeking situations, suggesting a gap between the users’ natural process of information use and the information system and intermediaries’ traditional patterns of information provision.
Abstract: The article discusses the users’ perspective of information seeking. A model of the information search process is presented derived from a series of five studies investigating common experiences of users in information seeking situations. The cognitive and affective aspects of the process of information seeking suggest a gap between the users’ natural process of information use and the information system and intermediaries’ traditional patterns of information provision.
1,996 citations
TL;DR: In this article, a series of relevance weighting functions is derived and is justified by theoretical considerations, in particular, it is shown that specific weighted search methods are implied by a general probabilistic theory of retrieval.
Abstract: This paper examines statistical techniques for exploiting relevance information to weight search terms. These techniques are presented as a natural extension of weighting methods using information about the distribution of index terms in documents in general. A series of relevance weighting functions is derived and is justified by theoretical considerations. In particular, it is shown that specific weighted search methods are implied by a general probabilistic theory of retrieval. Different applications of relevance weighting are illustrated by experimental results for test collections.
1,846 citations