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