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Sixth workshop on exploiting semantic annotations in information retrieval (ESAIR'13)

Published:27 October 2013Publication History

ABSTRACT

There is an increasing amount of structure on the web as a result of modern web languages, user tagging and annotation, emerging robust NLP tools, and an ever growing volume of linked data. These meaningful, semantic, annotations hold the promise to significantly enhance information access, by enhancing the depth of analysis of today's systems. Currently, we have only started exploring the possibilities and only begin to understand how these valuable semantic cues can be put to fruitful use. ESAIR'13 focuses on two of the most challenging aspects to address in the coming years. First, there is a need to include the currently emerging knowledge resources (such as DBpedia, Freebase) as underlying semantic model giving access to an unprecedented scope and detail of factual information. Second, there is a need to include annotations beyond the topical dimension (think of sentiment, reading level, prerequisite level, etc) that contain vital cues for matching the specific needs and profile of the searcher at hand.

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    • Published in

      cover image ACM Conferences
      CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management
      October 2013
      2612 pages
      ISBN:9781450322638
      DOI:10.1145/2505515

      Copyright © 2013 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 27 October 2013

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      CIKM '13 Paper Acceptance Rate143of848submissions,17%Overall Acceptance Rate1,861of8,427submissions,22%

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