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We propose the use of the text of the sentences surrounding citations as an important tool for semantic interpretation of bioscience text. We hypothesize several di#erent uses of citation sentences (which we call citances), including the creation of training and testing data for semantic analysis (especially for entity and relation recognition), synonym set creation, database curation, document summarization, and information retrieval generally. We illustrate some of these ideas, showing that citations to one document in particular align well with what a hand-built curator extracted. We also show preliminary results on the problem of normalizing the di#erent ways that the same concepts are expressed within a set of citances, using and improving on existing techniques in automatic paraphrase generation.

Literature indexing tools provide researchers with a means to navigate through the network of scholarly scientific articles in a subject domain. We propose that more effective indexing tools may be designed using the links between articles provided by citations. With the explosion in the amount of scientific literature and with the advent of artifacts requiring more sophisticated indexing, a means to provide more information about the citation relation in order to give more intelligent control to the navigation process is warranted. In order to navigate

Citations play an essential role in navigating academic literature and following chains of evidence in research. With the growing availability of large digital archives of scientific papers, the automated extraction and analysis of citations is becoming increasingly relevant. However, existing approaches to citation extraction still fall short of the high accuracy required to build more sophisticated and reliable tools for citation analysis and corpus navigation. In this paper, we present techniques for high accuracy extraction of citations and references from academic papers. By collecting multiple sources of evidence about entities from documents, and integrating citation extraction, reference segmentation, and citation– reference matching, we are able to significantly improve performance in subtasks including citation identification, author named entity recognition, and citation–reference matching. Applying our algorithm to previously-unseen documents, we demonstrate high F-measure performance of 0.980 for citation extraction, 0.983 for author named entity recognition, and 0.948 for citation–reference matching. 1

Argumentative Zoning (AZ) is an analysis of the argumentative and rhetorical structure of a scientific paper. It has been shown to be reliably used by independent human coders, and has proven useful for various information access tasks. Annotation experiments have however so far been restricted to one discipline, computational linguistics (CL). Here, we present a more informative AZ scheme with 15 categories in place of the original 7, and show that it can be applied to the life sciences as well as to CL. We use a domain expert to encode basic knowledge about the subject (such as terminology and domain specific rules for individual categories) as part of the annotation guidelines. Our results show that non-expert human coders can then use these guidelines to reliably annotate this scheme in two domains, chemistry and computational linguistics. 1

Abstract not found

Indeed time is speeding up. Events follow close upon each other. While the last issue heralded the start of the third volume of the ISSI newsletter, the society is now approaching its following benchmarking event. It is fifteen years ago that the board of the 4th International Conference on Scientometrics and Informetrics decided to found the International Society for Scientometrics and Informetrics (ISSI) to contribute to the advancement of the theory, methods and explanations with regard to Scientometrics, Informetrics and related fields. The Society intends to achieve these goals, among others, by encouraging communication and exchange of professional information and by enhancing the public perception of the discipline. The ISSI Newsletter took up the cause of this mission

Journal of Digital Information Management ABSTRACT: Citations management is an important task in managing digital libraries. Citations provide valuable information e.g., used in evaluating an author’s influences or scholarly quality (the impact factor of research journals). But although a reliable and effective autonomous citation management is essential, manual citation management can be extremely costly. Automatic citation mining on the other hand is a non-trivial task mainly due to non-conforming citation styles, spelling errors and the difficulty of reliably extracting text from PDF documents. In this paper we propose a novel rule-based autonomous citation mining technique, to address this important task. We define a set of common heuristics that together allow to improve the state of the art in automatic citation mining. Moreover, by first disambiguating citations based on venues, our technique significantly enhances the correct discovery of citations. Our experiments show that the proposed approach is indeed able to overcome limitations of current leading citation indexes such as ISI Web of Knowledge,

Indeed time is speeding up. Events follow close upon each other. While the last issue heralded the start of the third volume of the ISSI newsletter, the society is now approaching its following benchmarking event. It is fifteen years ago that the board of the 4th International Conference on Scientometrics and Informetrics decided to found the International Society for Scientometrics and Informetrics (ISSI) to contribute to the advancement of the theory, methods and explanations with regard to Scientometrics, Informetrics and related fields. The Society intends to achieve these goals, among others, by encouraging communication and exchange of professional information and by enhancing the public perception of the discipline. The ISSI Newsletter took up the cause of this mission

Domain analysis in information science Eleven approaches traditional as well as innovative