DEESSE: Entity-driven exploratory and serendipitous search SystEm

Olivier Van Laere, Ilaria Bordino, Yelena Mejova, Mounia Lalmas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

We present DEESSE [1], a tool that enables an exploratory and serendipitous exploration - at entity level, of the content of two different social media: Wikipedia, a user-curated online encyclopedia, and Yahoo Answers, a more unconstrained question/answering forum. DEESSE represents the content of each source as an entity network, which is further enriched with metadata about sentiment, writing quality, and topical category. Given a query entity, entity results are retrieved from the network by employing an algorithm based on a random walk with restart to the query. Following the emerging paradigm of composite retrieval, we organize the results into topically coherent bundles instead of showing them in a simple ranked list.

Original languageEnglish
Title of host publicationCIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery, Inc
Pages2072-2074
Number of pages3
ISBN (Print)9781450325981
DOIs
Publication statusPublished - 3 Nov 2014
Event23rd ACM International Conference on Information and Knowledge Management, CIKM 2014 - Shanghai, China
Duration: 3 Nov 20147 Nov 2014

Other

Other23rd ACM International Conference on Information and Knowledge Management, CIKM 2014
CountryChina
CityShanghai
Period3/11/147/11/14

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Keywords

  • Composite retrieval
  • Entity networks
  • Entity search

ASJC Scopus subject areas

  • Information Systems and Management
  • Computer Science Applications
  • Information Systems

Cite this

Van Laere, O., Bordino, I., Mejova, Y., & Lalmas, M. (2014). DEESSE: Entity-driven exploratory and serendipitous search SystEm. In CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management (pp. 2072-2074). Association for Computing Machinery, Inc. https://doi.org/10.1145/2661829.2661853