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...
Lexical selection is a significant problem for widecoverage machine translation: depending on the context, a given source language word can often be translated into different targ...
We present a knowledge and context-based system for parsing and translating natural language and evaluate it on sentences from the Wall Street Journal. Applying machine learning t...
In this paper, we identify factors that affect machine translation (MT) of a source query for cross-language information retrieval (CLIR) and empirically evaluate the effect of ps...
Yan Qu, Alla N. Eilerman, Hongming Jin, David A. E...
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 ...