Content-Based Filtering Recommendation Algorithm Using HMM

Author

Li, Hui ; Cai, Fei ; Liao, Zhifang

Author_Institution

Sch. of Software, Central South Univ., Changsha, China

fYear

2012

fDate

17-19 Aug. 2012

Firstpage

275

Lastpage

277

Abstract

In this paper, we combine probabilistic model and classical content-based filtering recommendation algorithms to propose a new algorithm for recommendation system, which we call content-based filtering recommendation algorithm using HMM. We utilize the HMM of recommended items to match user model and recommend items using user data. According to experiment result, this new method is more effective on describing a user´s interest compared with the VSM-based algorithm.

Keywords

recommender systems; HMM; VSM based algorithm; content based filtering recommendation algorithm; probabilistic model; Clustering algorithms; Educational institutions; Filtering; Hidden Markov models; Motion pictures; Probability distribution; Software algorithms; HMM; content-based filtering; recommendation system;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on

Conference_Location

Chongqing

Print_ISBN

978-1-4673-2406-9

Type

conf

DOI

10.1109/ICCIS.2012.112

Filename

6300489

Link To Document

https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=569374