By Oskar Bartenstein, Ulrich Geske, Markus Hannebauer, Osamu Yoshie

The 20 revised complete papers awarded during this e-book including four part surveys have been rigorously reviewed and chosen from the papers contributed to the 14th overseas convention on purposes of Prolog, INAP 2001, held in Tokyo, Japan, in October 2002.

The papers are dedicated to the 4 tightly interwoven elements wisdom acquisition, wisdom administration, wisdom processing, and information distribution, all within the context of the realm extensive internet; they're geared up in topical sections on net languages and common sense, knowlege acquisition and data illustration, selection aid via complicated good judgment programming, and Web-knowledge administration and knowledge mining.

The ebook is focused to designers and clients of e-business platforms and e-government platforms, for IT pros who construct such platforms, in addition to for the broader viewers drawn to the technical historical past of information processing for the internet.

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Additional info for Web Knowledge Management and Decision Support: 14th International Conference on Applications of Prolog, INAP 2001 Tokyo, Japan, October 20–22, 2001 Revised Papers

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The mechanism is more efficient and widely used than the JAVA serialize-based mechanism. The iML framework consists of three parts, an integrated development environment(IDE), runtime classes for standalone deployment, and an agent code generator. The integrated development environment (IDE) provides a comprehensive collection of development tools which include visual tools, the MiLog runtime environment, agent monitor, and debugger. The runtime classes are provided for standalone deployment of developed agents on both of JAVA applications and MiLog agents.

The iML framework provides three parts, an integrated development environment(IDE), runtime classes for standalone deployment, and an agent code generator. We evaluate the iML framework from two viewpoints, migration performance and the usability of the framework. The following sections are organized as follows. In Section 2, we briefly describe our previous work, the MiLog framework. In Section 3, we present the overview of the iML framework. In Section 4, we show some implementation details of the iML framework.

To obtain new partitions (labelled clusters) of the set of documents that the user selected with his query(ies). – To use domain knowledge whenever the system has it. In order to build the dialogue manager for a web information retrieval system we must take into account that: – – – – The number of users registered in the system is large (thousands). Typically there are more then one user using the system at the same instant. The users may interrupt their session for large periods of time. The users would like to be informed when a previous query result changes due to updates in the database.

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