Exploiting semantic result clustering to support keyword search on linked data

Ananya Dass, Cem Aksoy, Aggeliki Dimitriou, Dimitri Theodoratos

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

1 Scopus citations


Keyword search is by far the most popular technique for searching linked data on the web. The simplicity of keyword search on data graphs comes with at least two drawbacks: difficulty in identifying results relevant to the user intent among an overwhelming number of candidates and performance scalability problems. In this paper, we claim that result ranking and top-k processing which adapt schema unaware IR-based techniques to loosely structured data are not sufficient to address these drawbacks and efficiently produce answers of high quality. We present an alternative solution which hierarchically clusters the results based on a semantic interpretation of the keyword instances and takes advantage of relevance feedback from the user. Our clustering hierarchy exploits graph patterns which are structured queries clustering together result graphs of the same structure and represent possible interpretations for the keyword query. We present an algorithm which computes r-radius Steiner patterns graphs using exclusively the structural summary of the data graph. The user selects relevant pattern graphs by exploring only a small portion of the hierarchy supported by a ranking of the hierarchy components.Our experimental results show the feasibility of our system by demonstrating short reach times and efficient computation of the relevant results.

Original languageEnglish (US)
Title of host publicationWeb Information Systems Engineering – WISE 2014 - 15th International Conference, Proceedings
EditorsBoualem Benatallah, Azer Bestavros, Yannis Manolopoulos, Athena Vakali, Yanchun Zhang
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319117485
StatePublished - 2014
Event15th International Conference on Web Information Systems Engineering, WISE 2014 - Thessaloniki, Greece
Duration: Oct 12 2014Oct 14 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8786 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference15th International Conference on Web Information Systems Engineering, WISE 2014

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)


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