Research On Chinese Scientific And Technical Paper Based Interactive Ontology Building

The peer review of grant proposals is important to academics from all disciplines, which depends on the selection of reviewers. Generally speaking, reviewers' selection is to search experts who have similar knowledge with the proposals, in other words, it can be treated as a process of semantic retrieval, where ontology appears to be an important part. However, manually building ontologies turns to be time consuming and labor intensive, thus inhibits the applications. As a result, automatic ontology building is an urgent problem to be resolved.In this paper, theories about automatic ontology building are comprehensively analyzed and a novel method for Chinese scienfitic and technical papers based interactive ontology building is proposed. The method makes full use of ideas from system integrated innovation, natural language processing techniques and statistical algorithms to extract domain-specific concepts as well as their semantic relations from domain texts. Key work of this paper can be summarized in the following three parts:(1) Domain-specific concepts extraction. Here domain-specific concepts are extracted from texts through semantic string segmentation, rules matching, analysis of domain consensus and domain relevance, and concept reduction.(2) Semantic relations learning. First associated concepts are mined by association rule, and then sentences containing them are analyzed by dependency tree parser. Then syntactic patterns are generated by machine learning algorithms and are used to extract relations between new associated concepts. At last, relations are named according to the patterns.(3) The implementation of the interactive ontology building system. The system has three modules: text management, ontology building, and ontology maintenance, and ontology building module is strengthened and described in detail.In the end, a small ontology is built from Chinese texts in Computer Science domain and its sub domain Computer Hardware, and experimental results are evaluated, which show that the method for interactive ontology building proposed in this paper can improve the efficiency to a great extent and show the promise of relatively high precision. Furthermore, it is domain lexicon independent, thus is suitable for any domain ontology building.