3se: a semi-structured search engine for heterogeneous data in graph model

Authors:
Ming Zhong;Mengchi Liu
Affiliations:
Wuhan University, Wuhan, China;Carleton University, Ottawa, Canada
Venue:
Proceedings of the 18th ACM conference on Information and knowledge management
Year:
2009

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Abstract

As the ubiquitous interplay of structured, semi-structured and unstructured data from different sources, neither DB-style structured query requiring knowledge of full schema and complex language, nor IR-style keyword search ignoring latent structures, can satisfy users. In this paper, we present a novel Semi-Structured Search Engine (3SE) that provides easy, flexible, precise and rapid access to heterogeneous data represented by a semi-structured graph model. By using an intuitive 3SE Query Language (3SQL), users are able to pose queries on heterogeneous data in a varying degree of structural constraint according to their knowledge of schema. 3SE evaluates 3SQL queries as the top-k answers composed of "logical units" and relationship paths between them, and thus can extract meaningful information even if the query conditions are vague, ambiguous, and inaccurate.