Numerical recipes in C: the art of scientific computing
Numerical recipes in C: the art of scientific computing
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Sentence Fusion for Multidocument News Summarization
Computational Linguistics
A Novel Partitioning-Based Clustering Method and Generic Document Summarization
WI-IATW '06 Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology
The second release of the RASP system
COLING-ACL '06 Proceedings of the COLING/ACL on Interactive presentation sessions
Comparing clusterings---an information based distance
Journal of Multivariate Analysis
Multi-document summarization via sentence-level semantic analysis and symmetric matrix factorization
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Introduction to Information Retrieval
Introduction to Information Retrieval
Exploiting structure for event discovery using the MDI algorithm
ACL '07 Proceedings of the 45th Annual Meeting of the ACL: Student Research Workshop
NAACL-ANLP-AutoSum '00 Proceedings of the 2000 NAACL-ANLP Workshop on Automatic Summarization
Unsupervised and constrained Dirichlet process mixture models for verb clustering
GEMS '09 Proceedings of the Workshop on Geometrical Models of Natural Language Semantics
Instance sense induction from attribute sets
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
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Sentence Clustering is often used as a first step in Multi-Document Summarization (MDS) to find redundant information. All the same there is no gold standard available. This paper describes the creation of a gold standard for sentence clustering from DUC document sets. The procedure of building the gold standard and the guidelines which were given to six human judges are described. The most widely used and promising evaluation measures are presented and discussed.