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. Most of the existing research on text information processing, focuses in the factual domain rather than the opinion domain. In this paper we detect online hotspot forums by computing sentiment analysis for text data available in each forum. This approach analyses the forum text data and computes value for each word of text. The proposed approach combines K-means clustering and Support Vector Machine with PSO (SVM-PSO) classification algorithm that can be used to group the forums into two clusters forming hotspot forums and non-hotspot forums within the current time span. The proposed system accuracy is compared with the other classification algorithms such as Naive Bayes, Decision tree and SVM. The experiment helps to identify that K-means and SVM-PSO together achieve highly consistent results .
Highlights
Data mining is the process of nontrivial extraction of implicit, previously unknown, and potentially useful information from data that can help the businesses to make proactive and knowledge driven decisions
Machine Learning Techniques for Predicting Hot Spots For predicting online hotspot forums two machine learning techniques [5] have been proposed by Nan Li and Dash
Classification can be carried out using Support Vector Machine with Particle Swarm Optimization (SVM-PSO) algorithm
Summary
Data mining is the process of nontrivial extraction of implicit, previously unknown, and potentially useful information from data that can help the businesses to make proactive and knowledge driven decisions It uses machine learning, statistical and visualization techniques to discover and present knowledge that previously went unnoticed. Opinion mining is an important sub discipline within data mining and natural language processing (NLP), which automatically extracts, classifies, and understands the opinion generated by various users These techniques help to enhance the value of existing information resources that can be integrated with new products and systems as they are brought on-line. The proposed work is integrated with K-means clustering and Support Vector Machine with Particle Swarm Optimization (SVM-PSO) algorithm It optimally groups the forums into two clusters, forming hotspot forums and non-hotspot forums within each time window.
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