This paper reports our knowledge-ignorant machine learning approach to the triage task in TREC2004 genomics track, which is actually a text categorization problem. We applied Supp...
Machine learning is often used to automatically solve human tasks. In this paper, we look for tasks where machine learning algorithms are not as good as humans with the hope of ga...
We report on our on-going effort to build an adaptive driver support system, Driver AdvocateTM , merging various AI techniques, in particular, agents, ontology, production systems...
Chung Hee Hwang, Noel Massey, Bradford W. Miller, ...
Expressing web page content in a way that computers can understand is the key to a semantic web. Generating ontological information from the web automatically using machine learni...
In this paper, we describe a method to enhance the readability of out-of-vocabulary items (OOVs) in the textual output in a large vocabulary continuous speech recognition system. ...
Bart Decadt, Jacques Duchateau, Walter Daelemans, ...
We describe a Named Entity Recognition system for Dutch that combines gazetteers, handcrafted rules, and machine learning on the basis of seed material. We used gazetteers and a c...
This paper presents a novel idea, which combines Planning, Machine Learning and Knowledge-Based techniques. It is concerned with the development of an adaptive planning system tha...
Dimitris Vrakas, Grigorios Tsoumakas, Nick Bassili...
This paper presents a method that assists in maintaining a rule-based named-entity recognition and classification system. The underlying idea is to use a separate system, construc...
Georgios Petasis, Frantz Vichot, Francis Wolinski,...
Information visualization and visual data mining leverage the human visual system to provide insight and understanding of unorganized data. In order to scale to massive sets of hig...