CONSENTO: a consensus search engine for answering subjective queries

Authors:
Jaehoon Choi;Donghyeon Kim;Seongsoon Kim;Junkyu Lee;Sangrak Lim;Sunwon Lee;Jaewoo Kang
Affiliations:
Korea University, Seoul, South Korea;Korea University, Seoul, South Korea;Korea University, Seoul, South Korea;Korea University, Seoul, South Korea;Korea University, Seoul, South Korea;Korea University, Seoul, South Korea;Korea University, Seoul, South Korea
Venue:
Proceedings of the 21st international conference companion on World Wide Web
Year:
2012

Citing 3
Cited 1

Question answering from the web using knowledge annotation and knowledge mining techniques

CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Web-scale entity-relation search architecture

Proceedings of the 20th international conference companion on World wide web
Opinion-based entity ranking

Information Retrieval

CONSENTO: a new framework for opinion based entity search and summarization

Proceedings of the 21st ACM international conference on Information and knowledge management

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Abstract

Search engines have become an important decision making tool today. Decision making queries are often subjective, such as 'best sedan for family use,' 'best action movies in 2010,' to name a few. Unfortunately, such queries cannot be answered properly by conventional search systems. In order to address this problem, we introduce Consento, a consensus search engine designed to answer subjective queries. Consento performs subdocument-level indexing to more precisely capture semantics from user opinions. We also introduce a new ranking method, or ConsensusRank that counts in online comments referring to an entity as a weighted vote to the entity. We validated the framework with an empirical study using the data on movie reviews.