Relevance feedback (RF) is an iterative process, which refines the retrievals by utilizing the user's feedback on previously retrieved results. Traditional RF techniques solel...
Peng-Yeng Yin, Bir Bhanu, Kuang-Cheng Chang, Anlei...
In this paper, we make an attempt to use Inductive Logic Programming (ILP) to automatically learn non trivial descriptions of symbols, based on a formal description. This work is ...
We present two algorithms for supporting semi-automatic ontology building, integrated in WPro, a new architecture for ontology learning from Web documents. The first algorithm auto...
Daniele Bagni, Marco Cappella, Maria Teresa Pazien...
We argue that artificial intelligence systems must be able to manipulate their own internal representations automatically in order to deal with an infinitely complex and ever chan...
We describe an approach designed to reduce the costs of ontology development through the use of untrained, volunteer knowledge engineers. Results are provided from an experiment i...