Patent
Cooperative topical servers with automatic prefiltering and routing
TLDR
In this article, an information organization and retrieval system that efficiently organizes documents for rapid and efficient search and retrieval based upon topical content is presented, where documents may be relevant to one or more topics, and will be associated with each topic via the topical hierarchies maintained by the information servers.Abstract:
An information organization and retrieval system that efficiently organizes documents for rapid and efficient search and retrieval based upon topical content is presented. The information organization and retrieval system is optimized for the organization and retrieval of only those documents that are relevant to a given set of predefined topics. If a document does not have a topic that is included in the given set of topics, the document is excluded from the provided service. In like manner, if a document includes a topic that is specifically banned from the provided service, it is excluded. In this paradigm, the provider purposely limits the scope of the provided search and retrieval services, but in so doing provides a more efficient and effective service that is targeted to an expected user demand. The information organization and retrieval system also supports context-sensitive search and retrieval techniques, including the use of predefined or user-defined views for augmenting the search criteria, as well as the use of user specific vocabularies. In a preferred embodiment, the select set of topics are organized in multiple overlapping hierarchies, and a distributed software architecture is used to support the topic-based information organization, routing, and retrieval services. Documents may be relevant to one or more topics, and will be associated with each topic via the topical hierarchies that are maintained by the information servers.read more
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References
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Patent
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Patent
Method and apparatus for identifying textual documents and multi-mediafiles corresponding to a search topic
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Proceedings Article
Hierarchical Bayesian clustering for automatic text classification
Makoto Iwayama,Takenobu Tokunaga +1 more
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