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Proceedings Paper

Retrieving topical sentiments from online document collections
Author(s): Matthew F. Hurst; Kamal Nigam
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Paper Abstract

Retrieving document sby subject matter is the general goal of information retrieval and othe rcontent access systems. There are aspects of textual content, however, which form equally valid election critiria. One such aspect is that of sentiment or polarity - indicating the author's opinion or emotional relationship with some topic. Recent work in this are has treated polarity effectively as a discrete aspect of text. In this paper we present a lightweight but robust approach to combining topic and polarity thus enabling content access systems to select content based on a certain opinion about a certain topic.

Paper Details

Date Published: 15 December 2003
PDF: 8 pages
Proc. SPIE 5296, Document Recognition and Retrieval XI, (15 December 2003); doi: 10.1117/12.529422
Show Author Affiliations
Matthew F. Hurst, Intelliseek Applied Research Ctr. (United States)
Kamal Nigam, Intelliseek Applied Research Ctr. (United States)


Published in SPIE Proceedings Vol. 5296:
Document Recognition and Retrieval XI
Elisa H. Barney Smith; Jianying Hu; James Allan, Editor(s)

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