A Reading Answering System Model for Vietnamese Language

Author

Son The Pham ; Dang Tuan Nguyen

Author_Institution

Dept. of Inf. Sci. & Eng., Vietnam Nat. Univ. - Ho Chi Minh City, Ho Chi Minh City, Vietnam

fYear

2014

Firstpage

170

Lastpage

174

Abstract

Based on our previous researches for building a Reading Answering System Model (RASM) which can read many simple news titles of ICTNEWS (http://ictnews.vn/) to answer related Vietnamese questions. The construction of RASM is based on an approach of computational semantics. In this paper we focus on introducing our approach to build the RASM, the general architecture, and functional operations of RASM. In particular, we present new experimental results to evaluate the performance of our system in practice. We tested the system on 8 datasets composing 403 Vietnamese testing questions, and a vocabulary of 1142 lexicons. In experiments, the precision of our system is 66.63%.

Keywords

natural language processing; question answering (information retrieval); ICTNEWS; RASM; Vietnamese language; Vietnamese questions; functional operations; reading answering system model; Cities and towns; Computational modeling; Computer architecture; Natural language processing; Semantics; Syntactics; Testing; Computational Semantics; Question Answering System; Reading Answering System; Semantic Representation;

fLanguage

English

Publisher

ieee

Conference_Titel

Modelling Symposium (AMS), 2014 8th Asia

Print_ISBN

978-1-4799-6486-4

Type

conf

DOI

10.1109/AMS.2014.41

Filename

7079294