Document Similarity Judgment for Interactive Document Clustering
Yasufumi Takama, Minghuang Chen, Seiji Yamada · SCIS & ISIS SCIS & ISIS 2010 · 2010
This paper investigates the task of document similarity judgment for interactive document clustering. We suppose one of the promising approaches for develop- ing next generation of web search engines is to incorporate user feedback mechanism into constrained clustering. As a basis for designing such search engines, it is important to study the interface design that can reduce user' burden of giving feedback to a system. This paper focuses on the task of judging the similarity of two documents as the primitive task for user feedback, and compares 3 types of informa- tion to be presented to users: snippet, topic terms, and original text. In particular, snippets suitable for document similarity judgment are proposed, which consist of two kinds of snippets: common snippets showing the common part of documents, and specific snippets showing the dif- ference between documents. An experiment is conducted with 21 test participants, who were asked to judge the similarity of document pairs based on the 3 conditions. Those conditions are compared in terms of judgment time and accuracy with ANOVA and chi-square analysis. The typical judging behavior of the participants is also inves- tigated by an eye-tracking system. Keywords—snippets, document clustering, eye-tracking.