Understanding query interfaces by statistical parsing

Author:

Su Weifeng1,Wu Hejun2,Li Yafei3,Zhao Jing3,Lochovsky Frederick H.4,Cai Hongmin5,Huang Tianqiang6

Affiliation:

1. BNU-HKBU United International College and Shenzhen Key Laboratory of Intelligent Media and Speech, PKU-HKUST Shenzhen Hong Kong Institution

2. Sun Yat-Sen University

3. BNU-HKBU United International College

4. The Hong Kong University of Science and Technology

5. South China University of Technology

6. Fujian Normal University

Abstract

Users submit queries to an online database via its query interface. Query interface parsing, which is important for many applications, understands the query capabilities of a query interface. Since most query interfaces are organized hierarchically, we present a novel query interface parsing method, StatParser (Statistical Parser), to automatically extract the hierarchical query capabilities of query interfaces. StatParser automatically learns from a set of parsed query interfaces and parses new query interfaces. StatParser starts from a small grammar and enhances the grammar with a set of probabilities learned from parsed query interfaces under the maximum-entropy principle. Given a new query interface, the probability-enhanced grammar identifies the parse tree with the largest global probability to be the query capabilities of the query interface. Experimental results show that StatParser very accurately extracts the query capabilities and can effectively overcome the problems of existing query interface parsers.

Funder

UIC

National Natural Science Foundation of China

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Networks and Communications

Cited by 9 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Dependency-aware Form Understanding;2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE);2021-10

2. WebQuIn-LD: A Method of Integrating Web Query Interfaces Based on Linked Data;IEEE Access;2021

3. Schema Extraction for Deep Web Query Interfaces Using Heuristics Rules;Information Systems Frontiers;2018-06-07

4. Deep Web crawling: a survey;World Wide Web;2018-06-05

5. Semantic Analysis Based Approach for Relevant Text Extraction Using Ontology;International Journal of Information Retrieval Research;2017-10

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