A Genetic Model with Semantic Analysis for Feedback Classification
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


Downloads: 121 | Views: 389

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 1, January 2014 | Popularity: 6.7 / 10


     

A Genetic Model with Semantic Analysis for Feedback Classification

Shanmuga Priya.A, Vijayakumar.P


Abstract: An opinion, sentiment and topic detection system uses G-Tose algorithm and its work is based on the semantic analysis and string co-occurrence rules. Compared with classical search and optimization, Genetic approaches are less stuck in local suboptimal regions of search space because they perform multiple searches for a solution. A G-Tose (GA) is a search based, self-learning algorithm that imitates the theory of natural evaluation based on selective screening of results based on fitness of purpose. The system evaluation results show precision of 90.25 % respectively for feedback review process.


Keywords: G-Tose=Genetic approach for Topic, opinion and semantic extraction


Edition: Volume 3 Issue 1, January 2014


Pages: 147 - 150



Please Disable the Pop-Up Blocker of Web Browser

Verification Code will appear in 2 Seconds ... Wait



Text copied to Clipboard!
Shanmuga Priya.A, Vijayakumar.P, "A Genetic Model with Semantic Analysis for Feedback Classification", International Journal of Science and Research (IJSR), Volume 3 Issue 1, January 2014, pp. 147-150, https://www.ijsr.net/getabstract.php?paperid=08011403, DOI: https://www.doi.org/10.21275/08011403

Top