Short Text Similarity Computing Method towards Agriculture Question and Answering Systems

DOI

10.2991/iccia.2012.61How to use a DOI?

Keywords

Agricultural question-answering syste, Semantic dictionary, Text similarity,Similarity, Correlation

Abstract

Text similarity computing is the core issue that question-answering system needs to solve. It is mainly used to filter out the existed problems which are similar to the user’s questions from database. Because of the low recall of domain keywords in domain text similarity computing based on traditional semantic dictionary, this paper proposed a short text similarity computing method in the field of agriculture based on the extended version of <> which referred to as <>. This paper propose to consider both the similarity and correlation when calculate the words’ final similarity. The experimental results show that the proposed short text similarity computing method resolve the problem of the low recall of domain words in traditional semantic dictionary well, and improve the similarity calculation performance of high relevant keywords greatly.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Bingjie Sun
AU  - Zhichao Liang
AU  - Qingtian Zeng
AU  - Hua Zhao
AU  - Weijian Ni
PY  - 2014/05
DA  - 2014/05
TI  - Short Text Similarity Computing Method towards Agriculture Question and Answering Systems
BT  - Proceedings of the 2012 2nd International Conference on Computer and Information Application (ICCIA 2012)
PB  - Atlantis Press
SP  - 250
EP  - 253
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccia.2012.61
DO  - 10.2991/iccia.2012.61
ID  - Sun2014/05
ER  -