—It has been shown that the Universum data, which do not belong to either class of the classification problem of interest, may contain useful prior domain knowledge for training...
Hybrid learning methods use theoretical knowledge of a domain and a set of classified examples to develop a method for classification. Methods that use domain knowledge have been ...
In previous works, we showed how sequential pattern mining can be used to extract a partial problem space from logged user interactions for a procedural and ill-defined domain wher...
Philippe Fournier-Viger, Roger Nkambou, Engelbert ...
We present a random-walk-based approach to learning paraphrases from bilingual parallel corpora. The corpora are represented as a graph in which a node corresponds to a phrase, an...
Abstract--This paper presents a similarity measure that combines low-level trajectory information with geographical domain knowledge to compare vessel trajectories. The similarity ...
Gerben de Vries, Willem Robert van Hage, Maarten v...
Abstract Constructing correspondencesbetween points characterizing one shape with those characterizing another is crucial to understanding what the two shapes have in common. These...
Task planning for mobile robots usually relies solely on spatial information and on shallow domain knowledge, like labels attached to objects and places. Although spatial informat...
This paper proposes a system for personalization of web portals. A speci c implementation is discussed in reference to a web portal containing a news feed service. Techniques are ...
A desired capability of automatic problem solvers is that they can explain the results. Such explanations should justify that the solution proposed by the problem solver arises fr...
OLAP is an important tool in decision support. With the help of domain knowledge, such as hierarchies of attribute values, OLAP helps the user observe the effects of various decis...