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Object-stack: An object-oriented approach for top-k keyword querying over fuzzy XML

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Abstract

Keyword search is the most popular technique of searching information from XML (eXtensible markup language) document. It enables users to easily access XML data without learning the structure query language or studying the complex data schemas. Existing traditional keyword query methods are mainly based on LCA (lowest common ancestor) semantics, in which the returned results match all keywords at the granularity of elements. In many practical applications, information is often uncertain and vague. As a result, how to identify useful information from fuzzy data is becoming an important research topic. In this paper, we focus on the issue of keyword querying on fuzzy XML data at the granularity of objects. By introducing the concept of “object tree”, we propose the query semantics for keyword query at object-level. We find the minimum whole matching result object trees which contain all keywords and the partial matching result object trees which contain partial keywords, and return the root nodes of these result object trees as query results. For effectively and accurately identifying the top-K answers with the highest scores, we propose a score mechanism with the consideration of tf*idf document relevance, users’ preference and possibilities of results. We propose a stack-based algorithm named object-stack to obtain the top-K answers with the highest scores. Experimental results show that the object-stack algorithm outperforms the traditional XML keyword query algorithms significantly, and it can get high quality of query results with high search efficiency on the fuzzy XML document.

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Acknowledgements

The authors thank the anonymous referees for their valuable comments and suggestions, which improved the technical content and the presentation of the paper. The work was supported in part by the National Natural Science Foundation of China (61370075 and 61572118).

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Authors and Affiliations

  1. School of Computer Science and Engineering, Northeastern University, Shenyang, 110819, China

    Ting Li

  2. College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, 211106, China

    Zongmin Ma

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  1. Ting Li
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  2. Zongmin Ma
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Correspondence to Zongmin Ma.

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Li, T., Ma, Z. Object-stack: An object-oriented approach for top-k keyword querying over fuzzy XML. Inf Syst Front 19, 669–697 (2017). https://doi.org/10.1007/s10796-017-9748-0

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