OHSUMED: an interactive retrieval evaluation and new large test collection for research
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
ACM Computing Surveys (CSUR)
Co-clustering documents and words using bipartite spectral graph partitioning
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Iterative Double Clustering for Unsupervised and Semi-supervised Learning
EMCL '01 Proceedings of the 12th European Conference on Machine Learning
Document clustering based on non-negative matrix factorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Composing Web services on the Semantic Web
The VLDB Journal — The International Journal on Very Large Data Bases
Information-theoretic co-clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
RCV1: A New Benchmark Collection for Text Categorization Research
The Journal of Machine Learning Research
Co-clustering by block value decomposition
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Unsupervised content discovery in composite audio
Proceedings of the 13th annual ACM international conference on Multimedia
Document clustering with prior knowledge
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Orthogonal nonnegative matrix t-factorizations for clustering
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Co-clustering Documents and Words Using Bipartite Isoperimetric Graph Partitioning
ICDM '06 Proceedings of the Sixth International Conference on Data Mining
Information-theoretic metric learning
Proceedings of the 24th international conference on Machine learning
A Generalized Maximum Entropy Approach to Bregman Co-clustering and Matrix Approximation
The Journal of Machine Learning Research
Introduction to Information Retrieval
Introduction to Information Retrieval
An efficient hierarchical clustering model for grouping web transactions
International Journal of Business Intelligence and Data Mining
Incorporating User Provided Constraints into Document Clustering
ICDM '07 Proceedings of the 2007 Seventh IEEE International Conference on Data Mining
A matrix-based approach for semi-supervised document co-clustering
Proceedings of the 17th ACM conference on Information and knowledge management
Non-negative matrix factorization for semi-supervised data clustering
Knowledge and Information Systems
Semi-supervised graph clustering: a kernel approach
Machine Learning
Latent class models for collaborative filtering
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Fragmenting very large XML data warehouses via K-means clustering algorithm
International Journal of Business Intelligence and Data Mining
Data clustering: 50 years beyond K-means
Pattern Recognition Letters
Discovering homogenous service communities through web service clustering
SOCASE'08 Proceedings of the 2008 AAMAS international conference on Service-oriented computing: agents, semantics, and engineering
International Journal of Business Intelligence and Data Mining
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
Non-Negative Matrix Factorization for Semisupervised Heterogeneous Data Coclustering
IEEE Transactions on Knowledge and Data Engineering
Co-clustering analysis of weblogs using bipartite spectral projection approach
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part III
Efficient Semi-supervised Spectral Co-clustering with Constraints
ICDM '10 Proceedings of the 2010 IEEE International Conference on Data Mining
A clustering method of bloggers based on social annotations
International Journal of Business Intelligence and Data Mining
Co-clustering: A Versatile Tool for Data Analysis in Biomedical Informatics
IEEE Transactions on Information Technology in Biomedicine
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Co-clustering refers to the problem of deriving sub-matrices of the data matrix by simultaneously clustering the rows (data instances) and columns (features) of the matrix. While very effective in discovering useful knowledge, many of the co-clustering algorithms adopt a completely unsupervised approach. Integration of domain knowledge can guide the co-clustering process and greatly enhance the overall performance. We propose a semi-supervised Non-negative Matrix-factorisation (SS-NMF) based framework to integrate domain knowledge in the form of must-link and cannot-link constraints. Specifically, we augment the data matrix by integrating the constraints using metric learning and then perform NMF to obtain co-clustering. Under the proposed framework, we present two approaches to integrate domain knowledge, viz. a distance metric learning approach and an information theoretic metric learning approach. Through experiments performed on real-world web service data and publicly available text datasets, we demonstrate the performance of the proposed SS-NMF based approach for data co-clustering.