NDLI: A semantic enhanced approach for online hotspot forums detection

Content Provider	IEEE Xplore Digital Library
Author	Preethi, T. Nirmala Devi, K. Murali Bhaskaran, V.
Copyright Year	2012
Description	Author affiliation: Department of CSE, Kongu Engineering College, Erode, Tamilnadu, India (Preethi, T.; Nirmala Devi, K.) \|\| Paavai College of Engineering, Pachal, Namakkal, Tamilnadu, India (Murali Bhaskaran, V.)
Abstract	The user generated content on the web grows rapidly in this emergent information age. The evolutionary changes in technology make use of such information to capture only the user's essence and finally the useful information are exposed to information seekers. In this paper we detect online hotspot forums by computing sentiment analysis for text data available in each forum. This approach analyzes the forum text data and computes sentiment score for each word or phrase of text. Then we propose two text mining approaches like K-means clustering and Support Vector Machine with Particle Swarm Optimization (PSO-SVM) classification algorithms that can be used to group into two forum clusters forming hotspot forums and non-hotspot forums within each time window. The text datasets that we use in our experimental research are collected from forums.digitalpoint.com and after data cleaning they are formatted to 37 different forums and 1616 threads. The experiment helps to identify that K-means and PSO-SVM together achieve highly consistent results.
Starting Page	497
Ending Page	501
File Size	281885
Page Count	5
File Format	PDF
ISBN	9781467315999
e-ISBN	9781467316019
DOI	10.1109/ICRTIT.2012.6206785
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-04-19
Publisher Place	India
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Text mining Sentiment analysis Accuracy Instruction sets Hotspot detection Feature extraction Cleaning Classification algorithms Support Vector Machine Particle swarm optimization Particle Swarm Optimization
Content Type	Text
Resource Type	Article

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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
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