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Title of Journal: Neural Comput & Applic

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Abbravation: Neural Computing and Applications

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Springer-Verlag

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10.1016/j.aim.2009.04.003

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1433-3058

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RAST: finding related documents based on triplet similarity

Authors: Shiro Usui, Nilton Liuji Kamiji, Tatsuki Taniguchi, Naonori Ueda,

Publish Date: 2010/06/15
Volume: 20, Issue:7, Pages: 993-999
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Abstract

With the increasing amount of information available in recent years, searching for the desired content is becoming a challenging task. In this work, a tool for searching abstracts submitted to scientific conferences is introduced. It not only searches abstracts by the given keyword(s) but also displays abstracts related to a single or multiple selection. It also displays highly relevant abstracts together with possible keywords to help users refine their search. Analysis of the conditional similarity algorithm proposed here has shown that it does provide better output compared to ordinary cosine similarity, as well as the list of possible keywords reflects results of latent topic analysis. An interface for storing and sorting selected abstracts for future review and/or printing is also provided.


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