André Vellino

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Constraint interval arithmetic is a sublanguage of BNR Prolog which o ers a new approach to the old problem of deriving numerical consequences from algebraic models. Since it is simultaneously a numerical computation technique and a proof technique, it bypasses the traditional dichotomy between (numeric) calculation and (symbolic) proofs. This interplay(More)
The importance of a research article is routinely measured by counting how many times it has been cited. However, treating all citations with equal weight ignores the wide variety of functions that citations perform. We want to automatically identify the subset of references in a bibliography that have a central academic influence on the citing paper. For(More)
There are two principal data sources for collaborative filtering recommenders in scholarly digital libraries: usage data obtained from harvesting a large, distributed collection of Open URL web logs and citation data obtained from the journal articles. This study explores the characteristics of recommendations generated by implementations of these two(More)
A recommender system for scientific scholarly articles that is both hybrid (content and collaborative filtering based) and multi-dimensional (across metadata categories such as subject hierarchies, journal clusters and keyphrases) can improve scientists' ability to discover new knowledge from a digital library. Providing users with an interface which(More)
This thesis explores the relative complexity of proofs produced by the automatic theorem proving procedures of analytic tableaux, linear resolution, the connection method, tree resolution and the Davis-Putnam procedure. It is shown that tree resolution simulates the improved tableau procedure and that SL-resolution and the connection method are equivalent(More)
The TechLens+ strategy for addressing the recommender cold-start problem in a scholarly digital library is to seed the preference matrix with article references. However, this method generates boolean ratings rather than ratings on a numerical scale, as is more typical with recommender systems for commodity products. One strategy for generating a better(More)
A proof method for a system of logic is more powerful than another to the degree that it simplifies the task of producing derivations for theorems. One measure of the relative complexity of proof systems is offered by the notion polynomial simulation [Cook 1971]. Intuitively speaking, if any proof α of a tautology T in proof system A can be transformed into(More)
We describe a recommender system based on dynamically structured holographic memory (DSHM), a cognitive model of associative memory that uses holographic reduced representations as the basis for its encoding of object associations. We compare this recommender to a conventional user-based collaborative filtering algorithm on three datasets: MovieLens, and(More)