Topic distillation aims at finding key resources which are high-quality pages for certain topics. With analysis in non-content features of key resources, a pre-selection method is introduced in topic distillation research. A decision tree is constructed to locate key resource pages using query-independent non-content features including in-degree, document length, URL-type and two new features w...

Given a large hierarchical dictionary of concepts, the task of selection of the concepts that describe the contents of a given document is considered. The problem consists in proper handling of the top-level concepts in the hierarchy. As a representation of the document, a histogram of the topics with their respective contribution in the document is used. The contribution is determined by compa...

Wicked problems and social complexity abound in our globalizing, ever more complex society [6]. Wicked problems, such as many socioeconomic and environmental issues, cannot be solved in traditional ways, as no perfect solution can be found. Also, the understanding of the problem evolves as the solution is being worked on, but no clear agreement on what the real problem is can be reached. The on...

A robust strategy for dynamic Language Model (LM) selection, based on topic recognition and switching between topic models, is proposed. It is effective because it relies on a small set of well trained topic−dependent LMs and on reliable topic recognition. By using perplexity as a performance measure of the LM switching model, a tangible reduction is observed with respect to the use of a single...

Supervised topic models are promising tools for text analytics that simultaneously model topical patterns in document collections and relationships between those topics and document metadata, such as timestamps. We examine empirically the effect of OCR noise on the ability of supervised topic models to produce high quality output through a series of experiments in which we evaluate three superv...

Selection tasks in which simple stimuli (e.g. letters) are presented and a target stimulus has to be selected against one or more distractor stimuli are frequently used in the research on human action control. One important question in these settings is how distractor stimuli, competing with the target stimulus for a response, influence actions. The distractor-response binding paradigm can be u...

WordNet is a lexical database of the English language that seeks to capture the relationships between words as a graph data structure [8]. In the WordNet graph, vertices represent word groupings of synonyms, while edges are labeled relations between either two specific words in a grouping or two synonym groupings. The richness of these relationships allow WordNet to encode information about the...

In the context of unified messaging, a textual message may have to be reduced in length for display on certain mobile devices. This paper presents a new method to extract sentences that deal with a certain topic from a given text. The approach is based on automatically computed lists of words that represent the desired topics. These word lists also give semantic hints on how to shorten sentence...

Recent action selection architectures ly on planning, reaction, orboth, ignoring the wide spectrum of architectures inbetween. This paper recasts the action selection problem in terms of projection, commitment, and abstraction.