Document clustering based on non-negative matrix factorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Matching Theory (North-Holland mathematics studies)
Matching Theory (North-Holland mathematics studies)
Document Clustering Using Locality Preserving Indexing
IEEE Transactions on Knowledge and Data Engineering
Orthogonal nonnegative matrix t-factorizations for clustering
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Automated semantic web service discovery with OWLS-MX
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Similarity search for web services
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Efficiently finding web services using a clustering semantic approach
Proceedings of the 2008 international workshop on Context enabled source and service selection, integration and adaptation: organized with the 17th International World Wide Web Conference (WWW 2008)
Colibri: fast mining of large static and dynamic graphs
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Improving Web Service Discovery by Using Semantic Models
WISE '08 Proceedings of the 9th international conference on Web Information Systems Engineering
Discovering Homogeneous Web Service Community in the User-Centric Web Environment
IEEE Transactions on Services Computing
WSExpress: A QoS-aware Search Engine for Web Services
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
Measuring Similarity of Web Services Based on WSDL
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
On Service Community Learning: A Co-clustering Approach
ICWS '10 Proceedings of the 2010 IEEE International Conference on Web Services
Place semantics into context: service community discovery from the WSDL corpus
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
WTCluster: utilizing tags for web services clustering
ICSOC'11 Proceedings of the 9th international conference on Service-Oriented Computing
Bootstrapping Ontologies for Web Services
IEEE Transactions on Services Computing
Graph Regularized Sparse Coding for Image Representation
IEEE Transactions on Image Processing
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Service clustering provides an effective means to discover hidden service communities that group services with relevant functionalities. However, the ever increasing number of Web services poses key challenges for building large-scale service communities. In this paper, we address the scalability issue in service clustering, aiming to discover service communities over very large-scale services. A key observation is that service descriptions are usually represented by long but very sparse term vectors as each service is only described by a limited number of terms. This inspires us to seek a new service representation that is economical to store, efficient to process, and intuitive to interpret. This new representation enables service clustering to scale to massive number of services. More specifically, a set of anchor services are identified that allow to represent each service as a linear combination of a small number of anchor services. In this way, the large number of services are encoded with a much more compact anchor service space. We conduct extensive experiments on real-world service data to assess both the effectiveness and efficiency of the proposed approach. Results on a dataset with over 3,700 Web services clearly demonstrate the good scalability of sparse functional representation.