Algorithms And Data Structures

Download e-book for kindle: Network flows: theory, algorithms, and by Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin

By Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin

ISBN-10: 013617549X

ISBN-13: 9780136175490

Bringing jointly the vintage and the modern facets of the sphere, this complete advent to community flows offers an integrative view of conception, algorithms, and purposes. It bargains in-depth and self-contained remedies of shortest course, greatest movement, and minimal fee circulation difficulties, together with an outline of latest and novel polynomial-time algorithms for those center versions. For pros operating with community flows, optimization, and community programming.

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Additional info for Network flows: theory, algorithms, and applications(conservative)

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F. de Sousa Universidade Federal de Campina Grande, Brazil ABSTRACT With the growing significance of digital libraries and the Internet, more and more electronic texts become accessible to a wide and geographically disperse public. This requires adequate tools to facilitate indexing, storage and retrieval of documents written in different languages. We present a method for semi-automatic indexing of electronic documents and construction of a multilingual thesaurus, which can be used for query formulation and information retrieval.

The documents are indexed and the extracted terms are converted to a languageneutral thesaurus (called multilingual thesaurus). The same occurs with the query, and the correspondence between query terms and documents is obtained via the neutral thesaurus. The first solution is the most widely used in the Cross-Language Information Retrieval (CLIR) community (Go02; Ogden & Davis, 2000; Oard, 1999). It applies also to other information retrieval environments, such as the World Wide Web. For digital libraries, with thousands of documents, indexing of incoming documents and a good association structure between index terms and documents can become crucial for efficient document retrieval.

1998). Table 2. 1 0 Copyright © 2003, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Managing Document Taxonomies in Relational Databases 41 Figure 3. A Path Table Connects Each Classification with all its Parents Topic Topic_ID Name Level Topic_Above PATH topic_id topic_above Classify Topic_ID Doc_ID Document Doc_ID Name Date_Created Owner Listing 3. name ; One limitation of the Path Table approach is that the number of records in the Path Table can grow quite large for deep hierarchies.

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Network flows: theory, algorithms, and applications(conservative) by Ravindra K. Ahuja, Thomas L. Magnanti, James B. Orlin

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