Research Article
Novel Relevance Model for Sentiment Classification Based on Collision Theory
230 downloads
@INPROCEEDINGS{10.1007/978-3-642-35615-5_67, author={Meenakshi Murugeshan and Saswati Mukherjee}, title={Novel Relevance Model for Sentiment Classification Based on Collision Theory}, proceedings={Third International conference on advances in communication, network and computing}, proceedings_a={CNC}, year={2012}, month={12}, keywords={Relevance Measure Sentiment Classification Collision Theory}, doi={10.1007/978-3-642-35615-5_67} }- Meenakshi Murugeshan
Saswati Mukherjee
Year: 2012
Novel Relevance Model for Sentiment Classification Based on Collision Theory
CNC
Springer
DOI: 10.1007/978-3-642-35615-5_67
Abstract
The performance of an Information Retrieval system is very much dependent on the effectiveness of the relevance model being used. Motivated by the concepts in Collision Theory in Physics, this paper proposes a novel approach of identifying relevance between two text objects. The role of positive and negative features is considered in designing the relevance measure based on the transitions in Collision Theory. For evaluating the measure, we have applied our relevance model on sentiment classification.
Copyright © 2012–2024 ICST
