Research of Database Full-Text Retrieval Based on Related Words Recognition

Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 269)


With the popularity of application system, there is a growing demand for database full-text retrieval application. Users hope that they can easily find the information they want. This brings more restrict requirement on the Chinese synonyms recognition. At present, the study about Chinese synonym recognition has just begun in the domestic and the application of Chinese synonym recognition in the area is not just as one wish either. In this paper, we build a database full-text retrieval system which supports related words recognition in combination with lucene. The recognition of related words is applied to the full-text retrieval system. The data of related words were extracted from subject and achievement information.


Recognition of Chinese related words Chinese word segmentation Lucene Database full-text retrieval 


  1. 1.
    Lang X, Wang S (2006) Research and development of full text search engine based on lucene. Zhejiang University, HangzhouGoogle Scholar
  2. 2.
    Song M (1996) The Chinese vocabulary literal similarity principle after the controlled vocabulary the dynamic maintenance study. Information 04:261–271Google Scholar
  3. 3.
    Wu Z (1999) Economic information retrieval control the vocabulary study. Journal of Nanjing Agricultural University, NanjingGoogle Scholar
  4. 4.
    Crouch CJ (1990) An approach to the automatic construction of global thesaurus. Inf Process Manage 26:629–640CrossRefGoogle Scholar
  5. 5.
    Lu Y, Hou H (2004) Chinese synonym automatic recognition based on dictionary annotation. In: NCIRCSGoogle Scholar
  6. 6.
    Cheng T, Shi S, Wang X (2007) Thematic words extracting from Chinese text based on synonym Cilin. J Guangxi Normal Univ: Nat Sci Edn 25(2):145–148Google Scholar
  7. 7.
    Qun Liu, Sujian Li (2002) How net-based lexical semantic similarity calculation. Chin Comput Linguis 7(2):59–76Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  1. 1.Department of Computer Science and TechnologyShandong UniversityShandongChina

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