Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
Automatic text structuring and summarization
Information Processing and Management: an International Journal - Special issue: methods and tools for the automatic construction of hypertext
New Methods in Automatic Extracting
Journal of the ACM (JACM)
Generic text summarization using relevance measure and latent semantic analysis
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
Computational Linguistics - Summarization
A web-trained extraction summarization system
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Using maximum entropy for sentence extraction
AS '02 Proceedings of the ACL-02 Workshop on Automatic Summarization - Volume 4
Extractive summarisation of legal texts
Artificial Intelligence and Law - AI & law in eGovernment and eDemocracy part I
Word Sequence Models for Single Text Summarization
ACHI '09 Proceedings of the 2009 Second International Conferences on Advances in Computer-Human Interactions
Support vector machines for query-focused summarization trained and evaluated on pyramid data
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Improving Legal Document Summarization Using Graphical Models
Proceedings of the 2006 conference on Legal Knowledge and Information Systems: JURIX 2006: The Nineteenth Annual Conference
An approach to text summarization
CLIAWS3 '09 Proceedings of the Third International Workshop on Cross Lingual Information Access: Addressing the Information Need of Multilingual Societies
Extractive summarization using supervised and semi-supervised learning
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
LexRank: graph-based lexical centrality as salience in text summarization
Journal of Artificial Intelligence Research
Improving word sense disambiguation in lexical chaining
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Discourse indicators for content selection in summarization
SIGDIAL '10 Proceedings of the 11th Annual Meeting of the Special Interest Group on Discourse and Dialogue
Supervised machine learning for summarizing legal documents
AI'10 Proceedings of the 23rd Canadian conference on Advances in Artificial Intelligence
An automatic system for summarization and information extraction of legal information
Semantic Processing of Legal Texts
Citation based summarisation of legal texts
PRICAI'12 Proceedings of the 12th Pacific Rim international conference on Trends in Artificial Intelligence
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We describe a method for extractive summarization of legal judgments using our own graph-based summarization algorithm. In contrast to the connected and undirected graphs of previous work, we construct directed and disconnected graphs (a set of connected graphs) for each document, where each connected graph indicates a cluster that shares one topic in a document. Our method automatically chooses the number of representative sentences with coherence for summarization, and we don't need to provide a priori, the desired compression rate. We also propose our own node/edge-weighting scheme in the graph. Furthermore, we do not depend on expensive hand-crafted linguistic features or resources. Our experimental results show our method outperforms previous clustering-based methods, including those which use TF*IDF-based and centroid-based sentence selection. Our experimental results also show that our method outperforms previous machine learning methods that exploit a variety of linguistic features.