Proceedings of the 17th International Conference on Data Engineering
An Information-Theoretic Definition of Similarity
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
An Apriori-Based Algorithm for Mining Frequent Substructures from Graph Data
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
gSpan: Graph-Based Substructure Pattern Mining
ICDM '02 Proceedings of the 2002 IEEE International Conference on Data Mining
CloseGraph: mining closed frequent graph patterns
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Introduction to Algorithms and Java CD-ROM
Introduction to Algorithms and Java CD-ROM
Graph indexing: a frequent structure-based approach
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Scalable mining of large disk-based graph databases
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Automatic Measurement of a QoS Metric for Web Service Recommendation
ASWEC '05 Proceedings of the 2005 Australian conference on Software Engineering
On mining cross-graph quasi-cliques
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Finding Frequent Patterns in a Large Sparse Graph*
Data Mining and Knowledge Discovery
CLAN: An Algorithm for Mining Closed Cliques from Large Dense Graph Databases
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Out-of-core coherent closed quasi-clique mining from large dense graph databases
ACM Transactions on Database Systems (TODS)
Discovering the best web service
Proceedings of the 16th international conference on World Wide Web
The Google Similarity Distance
IEEE Transactions on Knowledge and Data Engineering
Web Service Discovery with additional Semantics and Clustering
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
On Mining Movement Pattern from Mobile Users
International Journal of Distributed Sensor Networks - Heterogenous Wireless Ad Hoc and Sensor Networks
WordNet::Similarity: measuring the relatedness of concepts
HLT-NAACL--Demonstrations '04 Demonstration Papers at HLT-NAACL 2004
Clustering Web Services for Automatic Categorization
SCC '09 Proceedings of the 2009 IEEE International Conference on Services Computing
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Clustering WSDL Documents to Bootstrap the Discovery of Web Services
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
A Mechanism for Web Service Selection and Recommendation Based on Multi-QoS Constraints
SERVICES '10 Proceedings of the 2010 6th World Congress on Services
Ranking and Clustering Web Services Using Multicriteria Dominance Relationships
IEEE Transactions on Services Computing
QoS-Aware Web Service Recommendation by Collaborative Filtering
IEEE Transactions on Services Computing
Composite Service Recommendation Based on Bayes Theorem
International Journal of Web Services Research
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Along with a continuously growing number of Web services, how to locate appropriate Web services to complete the task of service composition is becoming more critical. Differing from most recent studies which mainly focus on functional and non-functional properties, we mine nuggets from the Historical Service-composition Dataset HSD, which carries related users' past experiences. In this paper, a graph mining based recommendation approach is presented to facilitate the process of service composition. In particular, we first extend the graph mining approach gSpan to recognise Frequently Used Web Services FUWS with their connecting structures from HSD. Then, according to the records in HSD, which share the same FUWSs with user's partially composed service, a bunch of Web services with higher probability is recommended automatically as candidates. Finally, the skyline approach is adopted for optimal composite service selection with consideration of overall quality of services QoS. Furthermore, experiments based on 1,530 real Web services demonstrate the effectiveness and efficiency of our approach.