Clustering query results to support keyword search on tree data

Cem Aksoy, Ananya Dass, Dimitri Theodoratos, Xiaoying Wu

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

4 Scopus citations


Keyword search conveniently allows users to search for information on tree data. Several semantics for keyword queries on tree data have been proposed in recent years. Some of these approaches filter the set of candidate results while others rank the candidate result set. In both cases, users might spend a significant amount of time searching for their intended result in a plethora of candidates. To address this problem, we introduce an original approach for clustering keyword search results on tree data at different levels. The clustered output allows the user to focus on a subset of the results while looking for the relevant results. We also provide a ranking of the clusters at different levels to facilitate the selection of the relevant clusters by the user. We present an algorithm that efficiently implements our approach. Our experimental results show that our proposed clusters can be computed efficiently and the clustering methodology is effective in retrieving the relevant results.

Original languageEnglish (US)
Title of host publicationWeb-Age Information Management - 15th International Conference, WAIM 2014, Proceedings
PublisherSpringer Verlag
Number of pages12
ISBN (Print)9783319080093
StatePublished - 2014
Event15th International Conference on Web-Age Information Management, WAIM 2014 - Macau, China
Duration: Jun 16 2014Jun 18 2014

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8485 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Other15th International Conference on Web-Age Information Management, WAIM 2014

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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