Latent semantic indexing collaborative filtering recommendation system
Date of Publication
Bachelor of Science in Computer Science
College of Computer Studies
Defense Panel Chair
Defense Panel Member
Lim-Cheng, Nathalie Rose
The recent increase in the amount of information available online pushed the traditional query-based search methods to the limit. The information retrieval (IR) community made a counterproposal stating that building a personalized web surfing experience to the user. The aim of this research was to design a recommendation system that uses Tverskyâ€™s commonality model with LSI algorithm to solve the issues that the traditional collaborative filtering based recommender systems pose: sparsity and scalability. With the help of the commonality and similarity measurement, The LSI algorithm with commonality and similarity performed better than the traditional LSI-based recommendation algorithm.
Archives, The Learning Commons, 12F Henry Sy Sr. Hall
1v. various foliations ; illustrations ; 28 cm.
Kim, T. (2011). Latent semantic indexing collaborative filtering recommendation system. Retrieved from https://animorepository.dlsu.edu.ph/etd_bachelors/2642