Scatter/Gather: a cluster-based approach to browsing large document collections
SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Mining the peanut gallery: opinion extraction and semantic classification of product reviews
WWW '03 Proceedings of the 12th international conference on World Wide Web
Document clustering based on non-negative matrix factorization
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
The Journal of Machine Learning Research
Ontologies Improve Text Document Clustering
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
THESUS: Organizing Web document collections based on link semantics
The VLDB Journal — The International Journal on Very Large Data Bases
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Clustering short texts using wikipedia
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Projected Gradient Methods for Nonnegative Matrix Factorization
Neural Computation
TopX: efficient and versatile top-k query processing for semistructured data
The VLDB Journal — The International Journal on Very Large Data Bases
Knowledge sharing and yahoo answers: everyone knows something
Proceedings of the 17th international conference on World Wide Web
Enhancing text clustering by leveraging Wikipedia semantics
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
The YAGO-NAGA approach to knowledge discovery
ACM SIGMOD Record
Exploiting Wikipedia as external knowledge for document clustering
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Feature generation for text categorization using world knowledge
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Exploiting internal and external semantics for the clustering of short texts using world knowledge
Proceedings of the 18th ACM conference on Information and knowledge management
On ontology-driven document clustering using core semantic features
Knowledge and Information Systems - Special Issue on "Context-Aware Data Mining (CADM)"
Active learning for cross language text categorization
PAKDD'12 Proceedings of the 16th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part I
Exploiting social relations for sentiment analysis in microblogging
Proceedings of the sixth ACM international conference on Web search and data mining
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Social media websites allow users to exchange short texts such as tweets via microblogs and user status in friendship networks. Their limited length, pervasive abbreviations, and coined acronyms and words exacerbate the problems of synonymy and polysemy, and bring about new challenges to data mining applications such as text clustering and classification. To address these issues, we dissect some potential causes and devise an efficient approach that enriches data representation by employing machine translation to increase the number of features from different languages. Then we propose a novel framework which performs multi-language knowledge integration and feature reduction simultaneously through matrix factorization techniques. The proposed approach is evaluated extensively in terms of effectiveness on two social media datasets from Facebook and Twitter. With its significant performance improvement, we further investigate potential factors that contribute to the improved performance.