Incremental semantic web retrieval model based on web service

ABSTRACT

In the thesis, the new algorithm (CFCKE_SE) is illustrated mainly based on a large quantity of semantic knowledge in the Word Sense Code in accordance with the method of lexical chain and semantic expansion degree. The information of various characteristics in the chain to which the vocabulary belongs is sufficiently analyzed through the disambiguation of keywords and calculation of semantic relativity and similarity; then, the weight calculation is optimized for extraction. We find through inspection that the co-occurrence rate model can reduce ambiguity problem to a large extent and prevent the redundant expression of synonyms in the process of synonyms combination. If this new technology is applied to the text with a large quantity of synonyms, better results can be obtained and the keywords obtained can cover several topics comprehensively and accurately and the aggregative indicator F - measure, accuracy rate and recall rate can be improved compared with common algorithms.

KEYWORDS:

• Semantic web
• semantic model
• resource search
• ontology

Additional information

Funding

This work was supported by the Key Scientific Research Project of ABA Teachers University Foundation of China [grant number ASA16-07]; the Research Project of Sichuan Provincial Department of Education Foundation of China [grant number 17ZB0001].