Adaptive interfaces for ubiquitous web access

Abstract

T T he invention of the movable type printing press launched the information age by making the mass distribution of information both feasible and economical. Newspapers, magazines, shopping catalogs, restaurant guides, and classified advertisements can trace their origins to the printing process. Five and a half centuries of technological progress in communications networks, protocols, computers, and user interface design led to the Web, online publishing, and e-commerce. Consumers and businesses have access to vast stores of information. All this information, however, used to be accessible only while users were tethered to a computer at home or in an office. Wireless data and voice access to this vast store allows unprecedented access to information from any location at any time.

Negative ratings play a positive role in information filtering

“…(8) Then all u i 's uncollected objects are sorted in the descending order according to the final resource and those objects with the highest values are recommended.…”

“…For example, Amazon.com uses one's purchase record to recommend books [7], AdaptiveInfo.com uses one's reading history to recommend news [8], and the TiVo digital video system recommends TV shows and movies on the basis of users' viewing patterns and ratings [9]. The design of recommendation algorithms thus has not only academic interests but also practical benefits, which has attracted increasing attention of many branches of science and engineering, ranging from computer science and management science to mathematics and physics [10].…”

Automatic form filling on mobile devices

“…This context information 2 is used to initiate services and contents adaptation. In the application area of this paper particularly personalized web applications for mobile devices have to be concerned that adapt web applications according the user and according the used device [18][19][20][21]. The usage of rule-or policy-based systems based on artificial intelligence concepts are one standard approach when designing systems for context-aware services.…”

A Survey on Personalized Multimedia Content Search

“…The interest in this area rapidly increasing because it constitute a problem rich research area and many of practical applications that support users to deal with data overload and supply personalized recommendations, services and content to them. Following are some examples of such applications-CDs , recommendation books, and news at VERSIFI Technologies (formerly AdaptiveInfo.com) [2], movies by MovieLens [3], products at Amazon [4]. Many vendors have preferred to incorporate recommendation capabilities into their commerce server.Recommender system also useful for calculating proper contents to smart TV.…”