Unsupervised approach to generate informative structured snippets for job search engines

Nikita Spirin, Karrie Karahalios

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

Abstract

Aiming to improve user experience for a job search engine, in this paper we propose an idea to switch from query-biased snippets used by most web search engines to rich structured snippets associated with the main sections of a job post- ing page, which are more appropriate for job search due to specific user needs and the structure of job pages. We present a very simple yet actionable approach to generate such snippets in an unsupervised way. The advantages of the proposed approach are two-fold: it doesn't require manual annotation and therefore can be easily deployed to many languages, which is a desirable property for a job search en- gine operating internationally; it fuses naturally with the trend towards Mobile Web where the content needs to be optimized for small screen devices and informativeness.

Original languageEnglish (US)
Title of host publicationWWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web
PublisherAssociation for Computing Machinery
Pages203-204
Number of pages2
ISBN (Print)9781450320382
DOIs
StatePublished - Jan 1 2013
Event22nd International Conference on World Wide Web, WWW 2013 - Rio de Janeiro, Brazil
Duration: May 13 2013May 17 2013

Publication series

NameWWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web

Other

Other22nd International Conference on World Wide Web, WWW 2013
Country/TerritoryBrazil
CityRio de Janeiro
Period5/13/135/17/13

Keywords

  • Information extraction
  • Search snippet
  • Summarization

ASJC Scopus subject areas

  • Computer Networks and Communications

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