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Extracting cross references from life science databases for search result ranking

Published: 24 October 2011 Publication History

Abstract

Scholars in life sciences have to process huge amounts of data in a disciplined and efficient way. These data are spread among thousands of databases which overlap in content but differ substantially with respect to interface, formats and data structure. Search engines have the potential of assisting in data retrieval from these structured sources but fall short of providing a relevance ranking of the results that reflects the needs of life science scholars. One such need is to acquire insights to cross-references among entities in the databases, whereby search hits with many cross-references are expected to be more informative than those with few cross-references. In this work, we investigate to what extend this expectation holds. We propose BioXREF, a method that extracts cross-references from multiple life science databases by combining targeted crawling, pointer chasing, sampling and information extraction. We study the retrieval quality of our method and the relationship between manually crafted relevance ranking and relevance ranking based on cross-references, and report on first, promising results.

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  • (2013)Extraction and Prediction of Biomedical Database Identifier Using Neural Networks towards Data Network ConstructionCases on Open-Linked Data and Semantic Web Applications10.4018/978-1-4666-2827-4.ch004(58-83)Online publication date: 2013

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cover image ACM Conferences
CIKM '11: Proceedings of the 20th ACM international conference on Information and knowledge management
October 2011
2712 pages
ISBN:9781450307178
DOI:10.1145/2063576
Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 24 October 2011

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Author Tags

  1. life science
  2. outgoing cross references
  3. ranking
  4. search engines

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  • (2013)Extraction and Prediction of Biomedical Database Identifier Using Neural Networks towards Data Network ConstructionCases on Open-Linked Data and Semantic Web Applications10.4018/978-1-4666-2827-4.ch004(58-83)Online publication date: 2013

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