Machine learning for personalized wireless portals

Summary form only given. People have access to vast stores of information on the World Wide Web ranging from online publications to electronic commerce. All this information, however, used to be accessible only while users are 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. The presentation of this information must be tailored to the constraints of mobile devices. Although browsing and searching are the acceptable methods of locating information on the wired Web, those operations soon become cumbersome and inefficient in the wireless setting and impossible in voice interfaces. Small screens, slower connections, high latency, limited input capabilities, and the serial nature of voice interfaces present new challenges. This work focuses on personalization techniques that are essential for the usability of handheld wireless devices.