In this paper, we propose an innovative approach to extracting semi-structured data from Web sources. The idea is to collect a couple of example objects from the user and to use this information to extract new objects from new pages or texts. We propose a top-down strategy that extracts complex objects decomposing them in objects less complex, until atomic objects have been extracted. Through e...

Macro tree transducers are a combination of top-down tree transducers and macro grammars. They serve as a model for syntax-directed semantics in which context information can be handled. In this paper the formal model of macro tree transducers is studied by investigating typical automata theoretical topics like composition, decomposition, domains, and ranges of the induced translation classes. ...

Galliwasp is a goal-directed implementation of answer set programming. Unlike other answer set solvers, Galliwasp computes partial answer sets which are provably extensible to full answer sets. Galliwasp can execute arbitrary answer set programs in a top-down manner similar to SLD resolution. Galliwasp generates candidate answer sets by executing ordinary rules in a top-down, goal-directed mann...

The control of overt visual attention relies on an interplay of bottom-up and top-down mechanisms. Purely bottom-up models may provide a reasonable account of the looking behaviors of young infants, but they cannot accurately account for attention orienting of adults in many natural behaviors. But how do humans learn to incorporate topdown mechanisms into their control of attention? The phenome...

The use of multiple acoustic models has reported great improvements when facing speaker independent difficult tasks. In this paper, we are applying this strategy to a flexible, large vocabulary, speaker-independent, isolated-word hypothesis generation system in a telephone environment with vocabularies up to 10000 words. The new problem addressed here is how to efficiently integrate the multipl...

In this article we provide an analysis of existing methods for the incorporation of color in bag-of-words based image representations. We propose a list of desired properties on which bases fusing methods can be compared. We discuss existing methods and indicate shortcomings of the two well-known fusing methods, namely early and late fusion. Several recent works have addressed these shortcoming...

For large vocabulary recognition system, as well as for flexible vocabulary applications using hidden Markov model(HMM), parameter smoothing and tying have been used to increase the reliability of models. This paper describes bottom-up and topdown clustering techniques for state level tying. This paper also describes a method of applying parameter smoothing to the clustered states and covarianc...

Discovering the structure inherent in a set of patterns is a fundamental aim of statistical inference or learning. One fruitful approach is to build a parameterized stochastic generative model, independent draws from which are likely to produce the patterns. For all but the simplest generative models, each pattern can be generated in exponentially many ways. It is thus intractable to adjust the...

Vision is a crucial sensor. It provides a very rich collection of information about our environment. The difficulty in vision arises, since this information is not obvious in the image, it has to be constructed. Wheres earlier approaches have favored a bottom-up approach, which maps the image onto an internal representation of the world, more recent approaches search for alternatives and develo...

This paper suggests formal frameworks that can be used as the basis for defining, reasoning about, and verifying properties of agent systems. The language, Little-JIL is graphical, yet has precise mathematically defined semantics. It incorporates a wide range of semantics needed to define the subtleties of agent system behaviors. We demonstrate that the semantics of Little-JIL are sufficiently ...