ISSN:
1573-1391
Keywords:
User model
;
machine learning
;
server-client architecture
;
multivariate statistical analysis
;
Markov models
;
Beta distribution
;
linear prediction
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
Notes:
Abstract Doppelgänger is a generalized user modeling system that gathers data about users, performs inferences upon the data, and makes the resulting information available to applications.Doppelgänger's learning is calledheterogeneous for two reasons: first, multiple learning techniques are used to interpret the data, and second, the learning techniques must often grapple with disparate data types. These computations take place at geographically distributed sites, and make use of portable user models carried by individuals. This paper concentrates onDoppelgänger's learning techniques and their implementation in an application-independent, sensor-independent environment.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF01099429
Permalink