ROU: advanced keyword search on graph

Authors:
Yifan Pan;Yuqing Wu
Affiliations:
Indiana University, Bloomington, IN, USA;Indiana Univeristy, Bloomington, IN, USA
Venue:
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
Year:
2013

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Abstract

Keyword search, the major means for Internet search engines, has recently been explored in structured and semi-structured data. What is yet to be explored thoroughly is how optional and negative keywords can be expressed, what the results should be and how such search queries can be evaluated efficiently. In this paper, we formally define a new type of keyword search query, ROU-query, which takes as input keywords in three categories: required, optional and unwanted, and returns as output sets of nodes in the data graph whose neighborhood satisfies the keyword requirements. We define multiple semantics, including maximal coverage and minimal footprint, to ensure the meaningfulness of results. We propose query induced partite graph (QuIP), that can capture the constraints on neighborhood size and unwanted keywords, and propose a family of algorithms for evaluation of ROU-queries. We conducted extensive experimental evaluations to show our approaches are able to generate results for ROU-queries efficiently.