scholarly journals Enhanced Natural Language Interface for Web-Based Information Retrieval

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 4233-4241
Author(s):  
Tian Bai ◽  
Yan Ge ◽  
Shuyu Guo ◽  
Zhenting Zhang ◽  
Leiguang Gong
Keyword(s):  
Information Retrieval ◽  
Natural Language ◽  
Web Based ◽  
Natural Language Interface

scholarly journals AUDiaL: A Natural Language Interface to Make Statistical Charts Accessible to Blind Persons

2020 ◽  
pp. 373-384
Author(s):  
Tomas Murillo-Morales ◽  
Klaus Miesenberger
Keyword(s):  
Natural Language ◽  
Data Visualization ◽  
Initial Evaluation ◽  
Natural Manner ◽  
Web Based ◽  
User Training ◽  
Natural Language Interface ◽  
Blind Persons ◽  
Visualization Techniques ◽  
Traditional Approaches

AbstractThis paper discusses the design and evaluation of AUDiaL (Accessible Universal Diagrams through Language). AUDiaL is a web-based, accessible natural language interface (NLI) prototype that allows blind persons to access statistical charts, such as bar and line charts, by means of free-formed analytical and navigational queries expressed in natural language. Initial evaluation shows that NLIs are an innovative, promising approach to accessibility of knowledge representation graphics, since, as opposed to traditional approaches, they do not require of additional software/hardware nor user training while allowing users to carry out most tasks commonly supported by data visualization techniques in an efficient, natural manner.

Developing an Intelligent Tutoring System that has Automatically Generated Hints and Summarization for Algebra and Geometry

2015 ◽  
Vol 11 (2) ◽  
pp. 14-31 ◽  
Author(s):  
Yatao Li ◽  
Ke Zhao ◽  
Wei Xu
Keyword(s):  
Problem Solving ◽  
Natural Language ◽  
Intelligent Tutoring ◽  
Intelligent Tutoring System ◽  
After School ◽  
Tutoring System ◽  
Learning Gain ◽  
Web Based ◽  
Tutoring Systems ◽  
Natural Language Interface

Intelligent tutoring systems (ITSs), which provide step-by-step guidance to students in problem-solving activities, have been shown to enhance student learning in a range of domains. However, they tend to be preestablished and cannot supply the tutoring function immediately from the diverse mathematical questions. The MITSAS (multiagent intelligent tutoring system after school) is a web-based ITS in algebra and geometry with a natural language interface which is designed to extract the hint and summarization from the detailed solving answer automatically. In this paper, its Design principles and functionality is analysed firstly. Then, the framework including the natural language understanding agent, automatic modelling agent and automatic problem-solving agent are discussed in the following in order to support the real-time problems solution. Next, the methods for automatically extracting tutoring function such as hint and summarization is given based on the difficulty of knowledge components and the type of problem acquired from the detailed answer. Finally, the effectiveness of MITSAS at improving the Chinese Students' learning gain is shown by an experiment conducted in junior school.

scholarly journals AUTO STEMMING OF AZERBAIJANI LANGUAGE

2019 ◽  
Vol 10 (1) ◽  
pp. 59-66
Author(s):  
Morteza Hasan Alizadeh ◽  
◽  
Seyyed Amin Seyyedi ◽  
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Finite Automaton ◽  
Document Retrieval ◽  
Experimental Result ◽  
Deterministic Finite Automaton ◽  
Web Based ◽  
Structural Methods

One of important features in natural language processing is to find the root of a word. Stemming means to remove prefixes, suffixes, and infixes for finding the root of the word. Its aims are about to information retrieval, exploring text, machine for translation, and word look up based on its root. Stemming increases document retrieval by 10-50% in most of international languages, it also compresses the size of web-based table indexes documents up to 50%. In this paper, by analyzing stemming approaches, using structural methods, and deterministic finite automaton machine, applying 274 existing prefixes in language (linkage), a stemming system for Azerbaijani language is generated. Experimental result demonstrates that the proposed algorithm performs more than 97% accuracy.

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