Context-Based Question-Answering Evaluation

Document Type

Poster

Journal/Book Title/Conference

Special Interest Group for Information Retrieval

Publisher

Association for Computing Machinery

Publication Date

2004

First Page

578

Last Page

579

Abstract

We propose several context-based methods for text categorization. One method, a small modification to the PPM compression-based model which is known to significantly degrade compression performance, counter-intuitively has the opposite effect on categorization performance. Another method, called C-measure, simply counts the presence of higher order character contexts, and outperforms all other approaches investigated.

Comments

Originally published by the Association for Computing Machinery. Publisher's PDF is available through remote link.

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