Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Seventh workshop on exploiting semantic annotations in information retrieval (ESAIR’14)
KTH, School of Computer Science and Communication (CSC), Theoretical Computer Science, TCS.ORCID iD: 0000-0003-4042-4919
2014 (English)In: CIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management, Association for Computing Machinery (ACM), 2014, 2094-2095 p.Conference paper, Published paper (Refereed)
Abstract [en]

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. The goal of the ESAIR’14 workshop remains to advance the general research agenda on this core problem, with an explicit focus on one of the most challenging aspects to address in the coming years. The main remaining challenge is on the user’s side-the potential of rich document annotations can only be realized if matched by more articulate queries exploiting these powerful retrieval cues-and a more dynamic approach is emerging by exploiting new forms of query autosuggest. How can the query suggestion paradigm be used to encourage searcher to articulate longer queries, with concepts and relations linking their statement of request to existing semantic models? How do entity results and social network data in "graph search" change the classic division between searchers and information and lead to extreme personalization-are you the query? How to leverage transaction logs and recommendation, and how adaptive should we make the system? What are the privacy ramifications and the UX aspects-how to not creep out users?

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2014. 2094-2095 p.
Keyword [en]
Knowledge management, Semantics, Social networking (online), Document annotation, Dynamic approaches, Graph search, Information access, Personalizations, Query suggest, Query suggestion, Semantic annotations, Information retrieval
National Category
Computer Science Information Systems
Identifiers
URN: urn:nbn:se:kth:diva-174749DOI: 10.1145/2661829.2663539Scopus ID: 2-s2.0-84937597776ISBN: 978-145032598-1 (print)OAI: oai:DiVA.org:kth-174749DiVA: diva2:859871
Conference
23rd ACM International Conference on Information and Knowledge Management, CIKM 2014, Shanghai, China, 3 November 2014 through 7 November 2014
Note

QC 20151009

Available from: 2015-10-09 Created: 2015-10-07 Last updated: 2017-01-16Bibliographically approved

Open Access in DiVA

No full text

Other links

Publisher's full textScopus

Authority records BETA

Karlgren, Jussi

Search in DiVA

By author/editor
Karlgren, Jussi
By organisation
Theoretical Computer Science, TCS
Computer ScienceInformation Systems

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 77 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf