By Toshio Fukuda (auth.), Jiming Liu, Pong C. Yuen, Chun-hung Li, Joseph Ng, Toru Ishida (eds.)

ISBN-10: 3540430350

ISBN-13: 9783540430353

The prior few years have witnessed quick scienti?c and technological devel- ments in human-centered, seamless computing environments, interfaces, de- ces, and platforms with purposes starting from enterprise and conversation to leisure and studying. those advancements are jointly top charac- rized as lively Media expertise (AMT), a brand new region of knowledge expertise and desktop technology that emphasizes the proactive, seamless roles of interfaces and structures in addition to new electronic media in all features of human existence. This - lume includes the papers offered on the 6th overseas laptop technological know-how convention: lively Media expertise (AMT 2001), the ?rst convention of its sort, taking pictures the nation of study and improvement in AMT and the most recent architectures, prototypes, instruments, and ?elded platforms that display or let AMT. the quantity is prepared into the subsequent 8 components: I. shrewdpermanent electronic - dia; II. net Personalization; III. energetic Interfaces; IV. independent Agent - proaches; V. Facial photograph Processing; VI. AMT-Supported trade, enterprise, studying, and overall healthiness Care; VII. instruments and methods; and VIII. Algorithms.

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Extra info for Active Media Technology: 6th International Computer Science Conference, AMT 2001 Hong Kong, China, December 18–20, 2001 Proceedings

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Observation of Phase Transition behavior in Internet traffics. Advances in performance 2, (1999) 45-66 6. : Statistical physics to the Internet traffics. Phisica A 274, (1999) 30-49 7. : Dynamic phase transition observed in the Internet traffics flow. Phisica A 277 (2000) 248-255 8. Haken, H: Information and Self-Organization. Springer, Berlin (1988) 9. : Influence of the Complexity of Configuration of the Performance of a stochastic analog Neural Network for the Travel Salesman problems. Neural Networks, (to be submitted) 10.

1. Classification of Personalization Techniques control; therefore, they provide contents that dynamically respond to customer preferences and requirements. Examples of customer-driven systems are as follows: Search Engine. In this case, a search engine can be classified into three subcategories: Menu Selection. In the menu selection, customers must directly interact with the system in order to receive recommendations. Typically, customers choose from a set of predefined options on which to base their recommendations.

Saving records of a company’s supply purchases to the site 7. Searching for information on a particular topic based on keywords 8. Allowing an employee to select among options, such as the look and feel of the user interface 5 43 Community rating Menu selection Customer data storage Profile-filter agent Personalization Technique Profile-filter agent Simple filtering Simple filtering Profile-filter agent Attribute search Customer data storage Keyword/freeform search Menu selection Conclusion Today, personalized recommendation systems are changing from innovations used by a few sites to serious business tools that are re-forming the world of E-commerce.

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Active Media Technology: 6th International Computer Science Conference, AMT 2001 Hong Kong, China, December 18–20, 2001 Proceedings by Toshio Fukuda (auth.), Jiming Liu, Pong C. Yuen, Chun-hung Li, Joseph Ng, Toru Ishida (eds.)


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