Ranking objects by following paths in entity-relationship graphs

Minsuk Kahng, Sangkeun Lee, Sang Goo Lee

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

In this paper, we propose an object ranking method for search and recommendation. By selecting schema-level paths and following them in an entity-relationship graph, it can incorporate diverse semantics existing in the graph. Utilizing this kind of graph-based data models has been recognized as a reasonable way for dealing with heterogeneous data. However, previous work on ranking models using graphs has some limitations. In order to utilize a variety of semantics in multiple types of data, we define a schema path as a basic component of the ranking model. By following the path or a combination of paths, relevant objects could be retrieved or recommended. We present some preliminary experiments to evaluate our method. In addition, we discuss several interesting challenges that can be considered in future work.

Original languageEnglish
Title of host publicationCIKM 2011 Glasgow
Subtitle of host publicationPIKM'11 - Proceedings of the 2011 Workshop for Ph.D. Students in Information and Knowledge Management
Pages11-18
Number of pages8
DOIs
StatePublished - 2011
Externally publishedYes
Event4th Workshop for Ph.D. Students in Information and Knowledge Management, PIKM'11 - Glasgow, United Kingdom
Duration: Oct 28 2011Oct 28 2011

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference4th Workshop for Ph.D. Students in Information and Knowledge Management, PIKM'11
Country/TerritoryUnited Kingdom
CityGlasgow
Period10/28/1110/28/11

Keywords

  • entity-relationship graph
  • graph
  • information retrieval
  • object retrieval
  • ranking model
  • recommender systems
  • similarity search

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