Snowball: extracting relations from large plain-text collections
DL '00 Proceedings of the fifth ACM conference on Digital libraries
Extracting Patterns and Relations from the World Wide Web
WebDB '98 Selected papers from the International Workshop on The World Wide Web and Databases
Web-scale information extraction in knowitall: (preliminary results)
Proceedings of the 13th international conference on World Wide Web
Integrating Unstructured Data into Relational Databases
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Espresso: leveraging generic patterns for automatically harvesting semantic relations
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Names and similarities on the web: fact extraction in the fast lane
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
A supervised learning approach to acronym identification
AI'05 Proceedings of the 18th Canadian Society conference on Advances in Artificial Intelligence
Jigs and lures: associating web queries with structured entities
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Learning to find comparable entities on the web
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Learning open-domain comparable entity graphs from user search queries
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
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Web search engines are often presented with user queries that involve comparisons of real-world entities. Thus far, this interaction has typically been captured by users submitting appropriately designed keyword queries for which they are presented a list of relevant documents. Richer interactions that explicitly allow for a comparative analysis of entities represent a new potential direction to improve the search experience. With this in mind, we present an initial step of mining comparable entities from sources of information available to a large-scale Web search engine, namely, search query logs and documents from a Web crawl. Our mining methods generate a diverse set of comparables consisting of entities from a broad class of categories, such as medicines, appliances, electronics, and vacation destinations.