In this paper we describe techniques for the discovery and construction of user profiles. Leveraging from the emergent data web, our system addresses the problem of sparseness of user profile information currently faced by both asserted and inferred profile systems. A profile mediator, that dynamically builds the most suitable user profile for a particular service or interaction in real-time, is employed in our prototype implementation.
We propose to deploy and exploit a large number of inexpensive sensors to obtain information or trigger actions over a wide geographic area. Sensors may be of diverse physical natures: acoustic, IR, seismic, chemical, magnetic, thermal, etc. We describe here three major issues:( 1 ) sensor distribution pattems, (2) local sensor frames, and (3) autonomous robot sensor snow exploitation techniques.
In this paper we present a prototype for capturing retail related consumer intent using multiple devices and in multimodal input formats such as text, audio, and still images. The prototype was used in a longitudinal user study to analyze the process that consumers go through in order to make purchasing decisions. Based on these findings, we recommend desirable features for information management systems specifically designed for the retail environment.
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