NDLI: Cluster analysis based on opinion mining

Content Provider	IEEE Xplore Digital Library
Author	Xiaoye Wang Xiaorui Chai Ching-Hsien Hsu Yingyuan Xiao Yukun Li
Copyright Year	2015
Description	Author affiliation: Tianjin Key Lab. of Intell. Comput. & Novel Software Technol., Tianjin Univ. of Technol., Tianjin, China (Xiaoye Wang; Xiaorui Chai; Ching-Hsien Hsu; Yingyuan Xiao; Yukun Li)
Abstract	Mining based on opinions can extract useful information from users' comments. After doing cluster and analysis on the information, users can get a detailed understanding of the commodity, then determine to buy the commodity or not. In this paper, firstly, we extract evaluation objects and evaluation words, then cluster the evaluation objects. Next based on SO-PMI algorithm, judge the polarity of evaluation words and determine their polarity intensity values, then use K-means clustering algorithm to cluster the evaluation words. Last, for every kind of target evaluation object, make a count on the proportion of each kind evaluation word, and show the result to users in an intuitive way. This paper uses noun phrase pattern to match comments to extract evaluation objects and put forward the thematic words extraction algorithm. On judging the evaluation words' polarity, this paper establishes an emotional seed dictionary for each target object. The method of establishing dictionary for every attribute can eliminate the influence that less-correlation evaluation words have on the polarity judgment.
Starting Page	110
Ending Page	115
File Size	2654025
Page Count	6
File Format	PDF
e-ISBN	9781467382700
DOI	10.1109/UMEDIA.2015.7297438
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-08-24
Publisher Place	Sri Lanka
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computers Algorithm design and analysis Dictionaries Correlation polarity judgment Semantics Clustering algorithms thematic words extraction algorithm k-means clustering algorithm SO-PMI algorithm Opinion mining Data mining
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

An Incremental Weibo-Oriented Method for Unknown Word and Topic Extraction

A brief study on clustering methods: Based on the k-means algorithm

The Application on Intrusion Detection Based on K-means Cluster Algorithm

Feature based clustering considering context dependent words

Link based K-Means clustering algorithm for information retrieval

Product Review Information Extraction Based on Adjective Opinion Words

Optimization and Improvement Based on K-Means Cluster Algorithm

Spectral clustering method for high dimensional data based on K-SVD

Key frame extraction based on improved hierarchical clustering algorithm

Cluster analysis based on opinion mining

Similar Documents

An Incremental Weibo-Oriented Method for Unknown Word and Topic Extraction

A brief study on clustering methods: Based on the k-means algorithm

The Application on Intrusion Detection Based on K-means Cluster Algorithm

Feature based clustering considering context dependent words

Link based K-Means clustering algorithm for information retrieval

Product Review Information Extraction Based on Adjective Opinion Words

Optimization and Improvement Based on K-Means Cluster Algorithm

Spectral clustering method for high dimensional data based on K-SVD

Key frame extraction based on improved hierarchical clustering algorithm

Cluster analysis based on opinion mining