Incremental conceptual clustering is an important area of machine learning. It is concerned with summarizing data in a form of concept hierarchies, which will eventually ease the ...
This paper 3 proposes a new method to qualify the result given by a decision tree when it is used as a decision aid system. When the data are numerical, we compute the distance of ...
The aim of this paper is to describe and evaluate a system that automates a part of the transition from analytical to tectogrammatical tree structures within the Prague Dependency...
Question answering (QA) on table data is a challenging information retrieval task. This paper describes a QA system for tables created with both machine learning and heuristic tab...
Compounded words are a challenge for NLP applications such as machine translation (MT). We introduce methods to learn splitting rules from monolingual and parallel corpora. We eva...