Adaptive Probabilistic Search for Peer-to-Peer Networks
P2P '03 Proceedings of the 3rd International Conference on Peer-to-Peer Computing
Efficient Semantic-Based Content Search in P2P Network
IEEE Transactions on Knowledge and Data Engineering
Search strategies for scientific collaboration networks
Proceedings of the 2005 ACM workshop on Information retrieval in peer-to-peer networks
The PASCAL recognising textual entailment challenge
MLCW'05 Proceedings of the First international conference on Machine Learning Challenges: evaluating Predictive Uncertainty Visual Object Classification, and Recognizing Textual Entailment
Hi-index | 0.00 |
Peer-to-Peer networks are gaining increasing attention from both the scientific and the larger Internet user community. Peer-to-peer systems are very large computer networks, where peers collaborate to provide a common service. Providing large-scale Information retrieval, like searching the Internet, is an attractive application for P2P systems. Data discovery and retrieval is of great importance to computer users and the broad Internet community. In this paper, we propose a novel approach to retrieve not only textual documents that have specified keywords, but also to discover semantically equivalent or entailed documents from given keywords. This approach is based on the recent natural language processing approach called the Textual Entailment Approach.