Personal History Based Recommendation Service System with Collaborative Filtering

被引：1

作者：

Kim, Jong-Hun ^{[1
]}

Chung, Kyung-Yong ^{[2
]}

Ryu, Joong-Kyung ^{[3
]}

Rim, Kee-Wook ^{[4
]}

Lee, Jung-Hyun ^{[1
]}

机构：

[1] Inha Univ, Dept Comp Sci Engn, Inchon, South Korea

[2] Sangji Univ, Sch Comp Informat Engn, Wonju, South Korea

[3] Daelim Coll, Dept Comp Sci, Anyang, South Korea

[4] Sunmoon Univ, Dept Comp & Informat Sci, Asan, South Korea

来源：

PROCEEDINGS OF THE 2008 ADVANCED SOFTWARE ENGINEERING & ITS APPLICATIONS | 2008年

关键词：

D O I：

10.1109/ASEA.2008.56

中图分类号：

TP31 [计算机软件];

学科分类号：

081202 ; 0835 ;

摘要：

Although the conventional ubiquitous home service provides services using the information of environments obtained by the analysis of sensors, it shows a lack of user information. If recommendation services are able to use the past item selection information related to the context information of users, individualized services would be achieved Also, it is possible to solve a specialization tendency that makes not possible to avoid the taste of users themselves for recommended items when users use the item selection information of other users. This paper attempt to use Naive Bayesian for context model and propose Recommendation Service method based on personal history. And the Recommendation Service System (RSS) use a Collaborative Filtering (CF) to solve a specialization tendency on Open Set-vice Gateway Initiative (OSGi).

引用

页码：261 / +

页数：2

共 50 条

[1] A Document Recommendation System Based on Collaborative Filtering and Personal Ontology
Chen, Deng-Neng
Chiang, Yao-Chun
INFORMATION SYSTEMS IN THE CHANGING ERA: THEORY AND PRACTICE, 2009, : 255 - 262
[2] A Web Service Recommendation Approach Based on Collaborative Filtering
Zheng, Fudan
2014 IEEE 11TH INTERNATIONAL CONFERENCE ON E-BUSINESS ENGINEERING (ICEBE), 2014, : 344 - 349
[3] Trustworthy Web service recommendation based on collaborative filtering
Sheng, Guo-Jun
Wen, Tao
Guo, Quan
Wu, Di
Dongbei Daxue Xuebao/Journal of Northeastern University, 2013, 34 (06): : 806 - 809
[4] Performance Improvement of a Movie Recommendation System based on Personal Propensity and Secure Collaborative Filtering
Jeong, Woon-hae
Kim, Se-jun
Park, Doo-soon
Kwak, Jin
JOURNAL OF INFORMATION PROCESSING SYSTEMS, 2013, 9 (01): : 157 - 172
[5] Recommendation system based on collaborative filtering in RapidMiner
Tang, Zhihang
Wen, Zhonghua
Computer Modelling and New Technologies, 2014, 18 (11): : 1004 - 1008
[6] A Survey on Collaborative Filtering Based Recommendation System
Suganeshwari, G.
Ibrahim, S. P. Syed
PROCEEDINGS OF THE 3RD INTERNATIONAL SYMPOSIUM ON BIG DATA AND CLOUD COMPUTING CHALLENGES (ISBCC - 16'), 2016, 49 : 503 - 518
[7] A Fuzzy Based Recommendation System with Collaborative Filtering
Siddiquee, Md Mahfuzur Rahman
Haider, Naimul
Rahman, Rashedur M.
8TH INTERNATIONAL CONFERENCE ON SOFTWARE, KNOWLEDGE, INFORMATION MANAGEMENT AND APPLICATIONS (SKIMA 2014), 2014,
[8] Personal recommendation via modified collaborative filtering
Liu, Run-Ran
Jia, Chun-Xiao
Zhou, Tao
Sun, Duo
Wang, Bing-Hong
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS, 2009, 388 (04) : 462 - 468
[9] Method of collaborative filtering recommendation of personalized product-service system based on user
Lyu F.
Li N.
Feng Z.-Z.
Zhang Y.-H.
Jilin Daxue Xuebao (Gongxueban)/Journal of Jilin University (Engineering and Technology Edition), 2023, 53 (07): : 1935 - 1942
[10] Recommendation of personalized product-service system scheme based on improved collaborative filtering
Chen Y.
Geng X.
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS, 2021, 27 (01): : 240 - 248

← 1 2 3 4 5 →