The query of database must rely on professional query language, which is difficult to grasp for ordinary users. Natural language query interface (NLQI) can be applied to solve this problem with better human-computer interaction and intelligence. However, current natural language understanding technology is not mature. Though the query sentences’ structure is fixed, it is also difficult to accurately convert query sentences into understandable database query language for computer. Therefore a method of designing NLQI based on syntax and semantic analysis is proposed in this paper. First of all, Maximum forward and maximum reverse matching algorithms are used to analyse sentence by part of speech (POS) template, which is able to demonstrate the syntax relationship among the words. After syntax analysis, query conditions and targets are identified. Then, single conditions and targets are analyzed to relative standard forms by the relationship among entity, property, connect verb and unit. At last, these standard forms are transformed to SQL sentence. Regarding printing ERP system as experimental subject, experiment is done in this paper. The result shows that the method proposed in this paper can meet the needs of natural language query, and has a good transform effect for combination, omitting and other complex sentences.
Keyword-based online book retrieval can not fully understand the user's query intent. Query expansion is a typical solution, but the rate of recall and precision is still very low in existing methods. In response to these problems, this paper presents a semantic query expansion method based on domain ontology and local co-occurrence probability model. First, ontology reasoning and concepts related calculation are used to obtain the initial expansion terms. Furthermore, the local co-occurrence probability model is used to filter the candidate expansion terms and the filtering function is used for secondary selection. Experiment results show that this method can effectively improve retrieval efficiency.
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