ACARP: Author-centric analysis of research papers

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Abstract

Scientific publications are an important kind of user-generated content, which contains not only high-quality content but also structures, e.g. citations. Scientific publication analysis has attracted much attention in both database and data mining research community. In this demonstration, we present a system, named as Acarp, for analyzing research papers in database community. The relationship between a research paper and the authors is analyzed based on a learning to rank model. Not only the content of the paper, but also the citation graph is used in the analysis. Acarp can not only guess authors for papers under double-blind reviewing, but also analyze the researchers' continuity and diversity of research. This author-centric analysis could be interesting to researchers and be useful for further studying on double-blind reviewing process.

Original languageEnglish
Title of host publicationDatabase Systems for Advanced Applications - 17th International Conference, DASFAA 2012, Proceedings
Pages287-294
Number of pages8
EditionPART 2
DOIs
StatePublished - 2012
Event17th International Conference on Database Systems for Advanced Applications, DASFAA 2012 - Busan, Korea, Republic of
Duration: 15 Apr 201218 Apr 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume7239 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference17th International Conference on Database Systems for Advanced Applications, DASFAA 2012
Country/TerritoryKorea, Republic of
CityBusan
Period15/04/1218/04/12

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