A proposal for Kansei knowledge extraction method based on natural language processing technology and online product reviews

2019 ◽  
Vol 108 ◽  
pp. 1-11 ◽  
Author(s):  
Yiru Jiao ◽  
Qing-Xing Qu
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Extraction Method ◽  
Knowledge Extraction ◽  
Processing Technology ◽  
Product Reviews ◽  
Online Product Reviews

scholarly journals Keyword extraction method for machine reading comprehension based on natural language processing

2021 ◽  
Vol 1955 (1) ◽  
pp. 012072
Author(s):  
Ruiheng Li ◽  
Xuan Zhang ◽  
Chengdong Li ◽  
Zhongju Zheng ◽  
Zihang Zhou ◽  
...  
Keyword(s):  
Reading Comprehension ◽  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Extraction Method ◽  
Keyword Extraction ◽  
Machine Reading

scholarly journals Logical Intelligent Detection Algorithm of Chinese Language Articles Based on Text Mining

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Zihui Zheng
Keyword(s):  
Natural Language Processing ◽  
Text Mining ◽  
Natural Language ◽  
Language Processing ◽  
Chinese Language ◽  
Detection Algorithm ◽  
Processing Technology ◽  
Experimental Comparison ◽  
Intelligent Detection ◽  
Web Text Mining

With the advent of the big data era and the rapid development of the Internet industry, the information processing technology of text mining has become an indispensable role in natural language processing. In our daily life, many things cannot be separated from natural language processing technology, such as machine translation, intelligent response, and semantic search. At the same time, with the development of artificial intelligence, text mining technology has gradually developed into a research hotspot. There are many ways to realize text mining. This paper mainly describes the realization of web text mining and the realization of text structure algorithm based on HTML through a variety of methods to compare the specific clustering time of web text mining. Through this comparison, we can also get which web mining is the most efficient. The use of WebKB datasets for many times in experimental comparison also reflects that Web text mining for the Chinese language logic intelligent detection algorithm provides a basis.

scholarly journals Sentiment Analysis of Review Data of a Product Using Python

2018 ◽  
Vol 7 (3.12) ◽  
pp. 674
Author(s):  
P Santhi Priya ◽  
T Venkateswara Rao
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Sentiment Analysis ◽  
Language Processing ◽  
Opinion Mining ◽  
The Other ◽  
Product Reviews ◽  
Prime Problem

The other name of sentiment analysis is the opinion mining. It’s one of the primary objectives in a Natural Language Processing(NLP). Opinion mining is having a lot of audience lately. In our research we have taken up a prime problem of opinion mining which is theSentiment Polarity Categorization(SPC) that is very influential. We proposed a methodology for the SPC with explanations to the minute level. Apart from theories computations are made on both review standard and sentence standard categorization with benefitting outcomes. Also, the data that is represented here is from the product reviews given on the shopping site called Amazon.  

scholarly journals Smart Project Management: Interactive Platform Using Natural Language Processing Technology

2021 ◽  
Vol 11 (4) ◽  
pp. 1597
Author(s):  
Jieh-Haur Chen ◽  
Mu-Chun Su ◽  
Vidya Trisandini Azzizi ◽  
Ting-Kwei Wang ◽  
Wei-Jen Lin
Keyword(s):  
Neural Network ◽  
Natural Language Processing ◽  
Project Management ◽  
Natural Language ◽  
Real Time ◽  
Construction Industry ◽  
Language Processing ◽  
Recurrent Neural Network ◽  
Processing Technology ◽  
Management Platform

Technological developments have made the construction industry efficient. The aim of this research is to solve communication interaction problems to build a project management platform using the interactive concept of natural language processing technology. A comprehensive literature review and expert interviews associated with techniques dealing with natural languages suggests the proposed system containing the Progressive Scale Expansion Network (PSENet), Convolutional Recurrent Neural Network (CRNN), and Bi-directional Recurrent Neutral Networks Convolutional Recurrent Neural Network (BRNN-CNN) toolboxes to extract the key words for construction projects contracts. The results show that a fully automatic platform facilitating contract management is achieved. For academic domains, the Contract Keyword Detection (CKD) mechanism integrating PSENet, CRNN, and BRNN-CNN approaches to cope with real-time massive document flows is novel in the construction industry. For practice, the proposed approach brings significant reduction for manpower and human error, an alternative for settling down misunderstanding or disputes due to real-time and precise communication, and a solution for efficient documentary management. It connects all contract stakeholders proficiently.

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