Latent Semantic Index Applied in Question-Answering System about Agriculture Technology

In this paper was proposed to use latent semantic indexing technology in agricultural knowledge questions and answers system in accordance with the current condition of agricultural knowledge resources in JILIN province and the problems existing in the agricultural knowledge questions and answers system and professional work process. This technology can enhance or reduce the influence on the semantic in the document and can more clear the semantic relationships, retrieve the natural language to some extent, eliminate the interference from identity and polysemantics and obtain better search results.

Download Full-text

Bi-directional Long Short-Term Memory Model with Semantic Positional Attention for the Question Answering System

ACM Transactions on Asian and Low-Resource Language Information Processing ◽

10.1145/3439800 ◽

2021 ◽

Vol 20 (5) ◽

pp. 1-13

Author(s):

Mingwen Bi ◽

Qingchuan Zhang ◽

Min Zuo ◽

Zelong Xu ◽

Qingyu Jin

Keyword(s):

Question Answering ◽

Short Term Memory ◽

Semantic Representation ◽

Semantic Mapping ◽

Semantic Role ◽

Semantic Role Labeling ◽

Position Information ◽

Question Answering System ◽

Questions And Answers ◽

Mapping Mechanism

The intelligent question answering system aims to provide quick and concise feedback on the questions of users. Although the performance of phrase-level and numerous attention models have been improved, the sentence components and position information are not emphasized enough. This article combines Ci-Lin and word2vec to divide all of the words in the question-answer pairs into groups according to the semantics and select one kernel word in each group. The remaining words are common words and realize the semantic mapping mechanism between kernel words and common words. With this Chinese semantic mapping mechanism, the common words in all questions and answers are replaced by the semantic kernel words to realize the normalization of the semantic representation. Meanwhile, based on the bi-directional LSTM model, this article introduces a method of the combination of semantic role labeling and positional context, dividing the sentence into multiple semantic segments according to semantic logic. The weight is given to the neighboring words in the same semantic segment and propose semantic role labeling position attention based on the bi-directional LSTM model (BLSTM-SRLP). The good performance of the BLSTM-SRLP model has been demonstrated in comparative experiments on the food safety field dataset (FS-QA).

Download Full-text

Information Extraction from Web as Knowledge Resources for Indonesian Question Answering System

Proceedings of the Sriwijaya International Conference on Information Technology and Its Applications (SICONIAN 2019) ◽

10.2991/aisr.k.200424.064 ◽

2020 ◽

Author(s):

Abdiansah ABDIANSAH ◽

Alvi Syahrini UTAMI

Keyword(s):

Information Extraction ◽

Question Answering ◽

Knowledge Resources ◽

Question Answering System

Download Full-text

Study on Finding Experts in Community Question-Answering System

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.513-517.1760 ◽

2014 ◽

Vol 513-517 ◽

pp. 1760-1764 ◽

Cited By ~ 1

Author(s):

Rong Rong Yang ◽

Jian Hua Wu

Keyword(s):

Web 2.0 ◽

Web Mining ◽

Question Answering ◽

Service Model ◽

Question Answering System ◽

Community Question Answering ◽

Questions And Answers ◽

Hits Algorithm ◽

The Relationship ◽

The Web

As one of the new service model of Web 2.0, the emergence of Community Question-Answering system brings a new way for users to obtain information. However, the explosive growth of users and information, it will be hard for users to obtain the information quickly and accurately. Therefore, it is important to find experts in Community Question-Answering system to improve the accuracy and efficiency of information obtaining. This paper firstly analyzed the relationship among users, questions, and answers in Community Question-Answering system, and built the user diagram, and then by means of the Web mining technology, that is the link analysis weighted HITS algorithm, to find experts out. Finally, three evaluation indices were used to measure the validity of the experts finding algorithm. Experimental results show the effectiveness of the weighted HITS algorithm.

Download Full-text