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

2020 ◽  
Author(s):  
Abdiansah ABDIANSAH ◽  
Alvi Syahrini UTAMI
Keyword(s):  
Information Extraction ◽  
Question Answering ◽  
Knowledge Resources ◽  
Question Answering System

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

2014 ◽  
Vol 989-994 ◽  
pp. 4785-4788
Author(s):  
Li Ying Cao ◽  
Xiao Xian Zhang ◽  
Xiao Hui San ◽  
Gui Fen Chen
Keyword(s):  
Question Answering ◽  
Latent Semantic Indexing ◽  
Semantic Indexing ◽  
Work Process ◽  
Knowledge Resources ◽  
Question Answering System ◽  
Semantic Relationships ◽  
Search Results ◽  
Agricultural Knowledge ◽  
Questions And Answers

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.

scholarly journals Ontology-Based Question Answering System for an Academic Domain

2021 ◽  
Author(s):  
García-Robledo Gabriela A ◽  
Reyes-Ortiz José A ◽  
González-Beltrán Beatriz A ◽  
Bravo Maricela
Keyword(s):  
Natural Language Processing ◽  
User Interface ◽  
Speech Recognition ◽  
Natural Language ◽  
Information Extraction ◽  
Language Processing ◽  
Question Answering ◽  
Question Answering System ◽  
Methods And Techniques

The development of question answering (QA) systems involves methods and techniques from the areas of Information Extraction (EI), Natural Language Processing (NLP), and sometimes speech recognition. A user interface that involves all these tasks requires deep development to improve the interaction between a user and a device. This paper describes a Spanish QA system for an academic domain through a multi-platform user interface. The system uses a voice query to be transformed into text. The semi-structured query is converted into SQWRL language to extract a system of ontologies from an academic domain using patterns. The answer of the ontologies is placed in templates classified according to the type of question. Finally, the answer is transformed into a voice. A method for experimentation is presented focusing on the questions asked in voice and their respective answers by experts from the academic domain in a set of 258 questions, obtaining a 92% accuracy.

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