DocumentCode :
2343239
Title :
Domain-Knowledge Driven Recommendation Method and Its Application
Author :
Lingling Zhang ; Xiaojie Zhang ; Quan Chen ; Zhengxiang Zhu ; Yong Shi
Author_Institution :
Sch. of Manage., Grad. Univ. of Chinese Acad. of Sci., Beijing, China
fYear :
2011
fDate :
15-19 April 2011
Firstpage :
21
Lastpage :
25
Abstract :
In order to tackle the problems of current recommendation system, such as lack of domain knowledge and limited applications in e-commerce field, a domain-driven recommendation method based on binary data is proposed in this paper. By introducing the importance of domain knowledge and its application in recommendation, we discuss how to combine domain knowledge with collaborative filtering and apply it on binary purchasing data. Empirical result on supermarket dataset shows that domain-driven recommendation method outperforms other recommendation methods on three common evaluating indicators.
Keywords :
groupware; information filtering; purchasing; recommender systems; binary purchasing data; collaborative filtering; domain-knowledge driven recommendation method; supermarket dataset; Collaboration; Filtering; Filtering algorithms; Industries; Marketing and sales; Ontologies; Semantics; collaborative filtering; domain knowledge; recommendation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Sciences and Optimization (CSO), 2011 Fourth International Joint Conference on
Conference_Location :
Yunnan
Print_ISBN :
978-1-4244-9712-6
Electronic_ISBN :
978-0-7695-4335-2
Type :
conf
DOI :
10.1109/CSO.2011.305
Filename :
5957602
Link To Document :
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