Personalized context-aware QoS prediction for web services based on collaborative filtering

Authors:
Qi Xie;Kaigui Wu;Jie Xu;Pan He;Min Chen
Affiliations:
College of Computer Science, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China;College of Computer Science, Chongqing University, Chongqing, China
Venue:
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications - Volume Part II
Year:
2010

Citing 8
Cited 0

GroupLens: an open architecture for collaborative filtering of netnews

CSCW '94 Proceedings of the 1994 ACM conference on Computer supported cooperative work
Understanding and Using Context

Personal and Ubiquitous Computing
A conceptual framework and a toolkit for supporting the rapid prototyping of context-aware applications

Human-Computer Interaction
Using contextual information and multidimensional approach for recommendation

Expert Systems with Applications: An International Journal
WSRec: A Collaborative Filtering Based Web Service Recommender System

ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
Personalized context-aware collaborative filtering based on neural network and slope one

CDVE'09 Proceedings of the 6th international conference on Cooperative design, visualization, and engineering
WSExpress: A QoS-aware Search Engine for Web Services

ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Empirical analysis of predictive algorithms for collaborative filtering

UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

The emergence of abundant Web Services has enforced rapid evolvement of the Service Oriented Architecture (SOA). To help user selecting and recommending the services appropriate to their needs, both functional and nonfunctional quality of service (QoS) attributes should be taken into account. Before selecting, user should predict the quality of Web Services. A Collaborative Filtering (CF)-based recommendation system is introduced to attack this problem. However, existing CF approaches generally do not consider context, which is an important factor in both recommender system and QoS prediction. Motivated by this, the paper proposes a personalized context-aware QoS prediction method for Web Services recommendations based on the SLOPE ONE approach. Experimental results demonstrate that the suggested approach provides better QoS prediction.