International Journal of Computational Intelligence Systems

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Volume 13, Issue 1, 2020, Pages 275 - 290

Information Retrieval Based on Knowledge-Enhanced Word Embedding Through Dialog: A Case Study

Authors
Jin Ren1, *, Hengsheng Wang1, 2, Tong Liu1
1College of Mechanical & Electrical Engineering, Central South University, Changsha 410083, China
2State Key Laboratory for High Performance Complex Manufacturing, Central South University, Changsha 410083, China
*Corresponding author. Email: renjin@csu.edu.cn
Corresponding Author
Jin Ren
Received 15 April 2019, Accepted 3 March 2020, Available Online 16 March 2020.
DOI
10.2991/ijcis.d.200310.002How to use a DOI?
Keywords
Information retrieval; Domain knowledge; Enhanced word embedding; Semantic understanding
Abstract

The aim of this paper is to provide a systematic route of information retrieval from a knowledge-based database (or domain knowledge) through a dialog system of natural language interaction. The application is about a comprehensive building at a university, with classrooms, laboratory rooms, meeting rooms, research rooms and offices, and is to present related information the user asks for. First, the domain knowledge is expressed with predicate expressions based on the ontology structure; then the vocabulary is presented distributedly with word embedding enhanced with the domain knowledge; queries from the user are then converted into the intent (general) and slot elements (specific) with the help of trained recurrent neural network (RNN). The system works smoothly. The key point is integrating the two methods of knowledge-based and data-driven natural language processing into one system, and the domain knowledge is in the central part which is incorporated into the word embedding to make it specifically fit the natural language in this application.

Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

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<Previous Article In Issue
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Journal
International Journal of Computational Intelligence Systems
Volume-Issue
13 - 1
Pages
275 - 290
Publication Date
2020/03/16
ISSN (Online)
1875-6883
ISSN (Print)
1875-6891
DOI
10.2991/ijcis.d.200310.002How to use a DOI?
Copyright
© 2020 The Authors. Published by Atlantis Press SARL.
Open Access
This is an open access article distributed under the CC BY-NC 4.0 license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - JOUR
AU  - Jin Ren
AU  - Hengsheng Wang
AU  - Tong Liu
PY  - 2020
DA  - 2020/03/16
TI  - Information Retrieval Based on Knowledge-Enhanced Word Embedding Through Dialog: A Case Study
JO  - International Journal of Computational Intelligence Systems
SP  - 275
EP  - 290
VL  - 13
IS  - 1
SN  - 1875-6883
UR  - https://doi.org/10.2991/ijcis.d.200310.002
DO  - 10.2991/ijcis.d.200310.002
ID  - Ren2020
ER  -