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We derive from first principles the basic equations for a few of the basic hidden-Markov-model word taggers as well as equations for other models which may be novel (the descriptions in previous papers being too spare to be sure). We give performance results for all of the models. The results from our best model (96.45% on an unused test sample from the(More)
Recognizing and recording activities of daily living is a significant problem in elder care. A new paradigm for ADL inferencing leverages radio-frequency-identification technology, data mining, and a probabilistic inference engine to recognize ADLs, based on the objects people use. A key aspect of pervasive computing is using computers and sensor networks(More)
The creation of a complex web site is a thorny problem in user interface design. In this paper we explore the notion of adaptive web sites: sites that semi-automatically improve their organization and presentation by learning from visitor access patterns. It is easy to imagine and implement web sites that ooer shortcuts to popular pages. Are more(More)
This paper investigates the problem of automatically learning declarative models of information sources available on the Internet. We report on ILA, a domain-independent program that learns the meaning of external information by explaining it in terms of internal categories. In our experiments, ILA starts with knowledge of local faculty members, and is able(More)
D esigning a complex Web site so that it readily yields its information is a difficult task. The designer must anticipate the users' needs and structure the site accordingly. Yet users may have vastly differing views of the site's information, their needs may change over time, and their usage patterns may violate the designer's initial expectations. As a(More)
The ability to determine what day-to-day activity (such as cooking pasta, taking a pill, or watching a video) a person is performing is of interest in many application domains. A system that can do this requires models of the activities of interest, but model construction does not scale well: humans must specify low-level details, such as segmentation and(More)
The explosive growth of the Web has made intelligent software assistants increasingly necessary for ordinary computer users. Both traditional approaches | search engines, hierarchical indices | and intelligent software agents require signiicant amounts of human eeort to keep up with the Web. As an alternative, we investigate the problem of automatically(More)
Many recent studies have underscored the applicability to healthcare of a system able to observe and understand day-today human activities. The Guide project is aimed at building just such a system. The project combines novel sensing technology, expressive but scalable learners and unsupervised mining of activity models from the web to address the problem.(More)