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Recommendation systems make suggestions about artifacts to a user. For instance, they may predict whether a user would be interested in seeing a particular movie. Social recomendation methods collect ratings of artifacts from many individuals, and use nearest-neighbor techniques to make recommendations to a user concerning new artifacts. However, these(More)
People display regularities in almost everything they do. This paper proposes characteristics of an idealized algorithm that, when applied to sequences of user actions, would allow a user interface to adapt over time to an individual’s pattern of use. We describe a simple predictive method with these characteristics and show its predictive accuracy on a(More)
Description logics are a popular formalism for knowledge representation and reasoning. This paper introduces a new operation for description logics: computing the “least common subsumer” of a pair of descriptions. This operation computes the largest set of commonalities between two descriptions. After arguing for the usefulness of this operation, we analyze(More)
We review several kinds of previously studied concept similarity measures, and then rephrase them in terms of a simple DL. We discuss the difficulties encountered in trying to generalize these formulations to more complex DLs, and settle on one based on probability/information theory as being the most principled. 1 Motivation and Goals The idea of measuring(More)
This paper presents work that uses Latent Semantic Indexing (LSI) for text classification. However, in addition to relying on labeled training data, we improve classification accuracy by also using unlabeled data and other forms of available "background" text in the classification process. Rather than performing LSI's singular value decomposition (SVD)(More)
Mitchell's version-space approach to inductive concept learning has been highly influential in machine learning, as it formalizes inductive concept learning as a search problem—to identify some concept definition out of a space of possible definitions. This paper lays out some theoretical underpinnings of version spaces. It presents the conditions under(More)
Although there is an increasing amount of experimental research on learning concepts expressed in first-order logic, there are still relatively few formal results on the polynomial learnability of first-order representations from examples. Most previous analyses in the pac-model have focused on subsets of Prolog, and only a few highly restricted subsets(More)