A computational semantic information retrieval model for Vietnamese texts
by Tuyen Thi-Thanh Do; Dang Tuan Nguyen
International Journal of Computational Science and Engineering (IJCSE), Vol. 24, No. 3, 2021

Abstract: Semantic information retrieval system for text documents aims at retrieving text documents containing the similar semantic representation to the query. Semantic representation of text can be vector or dependency graph depending on the approach of semantic analysis. This paper proposes a model of semantic information retrieval for Vietnamese to retrieve similar texts to a query. In the proposed system, the semantic analysis is to identify the semantic dependency graph of sentences and the retrieving process computes the relevance of text document with these semantic dependency graphs. For identifying the semantic dependency graph of a sentence, the transformation rules are studied to apply on dependency parse using lexicon ontology for Vietnamese. For ranking retrieval results, the Jaccard-Tanimoto distance is applied to the ranking function. The evaluation shows that the proposed model has higher MAP (0.4045) than MAP of BM25 model (0.3825) and of TF.IDF model (0.3688).

Online publication date: Tue, 15-Jun-2021

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Computational Science and Engineering (IJCSE):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com