Domain-specific knowledge acquisition for conceptual sentence analysis
Domain-specific knowledge acquisition for conceptual sentence analysis
Automatic hypertext construction
Automatic hypertext construction
Improving automatic query expansion
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Finite-State Language Processing
Finite-State Language Processing
Embedded machine learning systems for natural language processing: a general framework
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing
Automatic Text Decomposition Using Text Segments and Text Themes
Automatic Text Decomposition Using Text Segments and Text Themes
High-precision information retrieval
High-precision information retrieval
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
A maximum entropy approach to identifying sentence boundaries
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Error-driven pruning of Treebank grammars for base noun phrase identification
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Collection statistics for fast duplicate document detection
ACM Transactions on Information Systems (TOIS)
Improved robustness of signature-based near-replica detection via lexicon randomization
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Improving web information indexing and retrieval based on center block duplication detection
International Journal of Innovative Computing and Applications
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The primary goal of the Cornell/Sabir TIPSTER Phase III project is to develop techniques to improve the end-user efficiency of information retrieval (IR) systems. We have focused our investigations in four related research areas:1. High Precision Information Retrieval. The goal of our research in this area is to increase the accuracy of the set of documents given to the user.