AI
2001
Springer
14 years 3 days ago
2001
Springer
Abstract. Term extraction is an important problem in natural language processing. In this paper, we propose a language independent statistical corpus-based term extraction algorith...
NLDB
2010
Springer
14 years 11 days ago
2010
Springer
NLDB
2010
Springer
14 years 11 days ago
2010
Springer
Abstract. In the paper we present a method that allows an extraction of singleword terms for a specific domain. At the next stage these terms can be used as candidates for multi-wo...
ITS
2010
Springer
14 years 11 days ago
2010
Springer
Abstract. In this paper, we use supervised machine learning to automatically identify the problem localization of peer-review feedback. Using five features extracted via Natural L...
CICLING
2010
Springer
14 years 21 days ago
2010
Springer
We introduce an Information Extraction (IE) system which uses the logical theory of an ontology as a generalisation of the typical information extraction patterns to extract biolog...
CICLING
2010
Springer
14 years 21 days ago
2010
Springer
Sentence compression is a valuable task in the framework of text summarization. In this paper we compress sentences from news articles from Dutch and Flemish newspapers written in ...
ECML
2003
Springer
14 years 24 days ago
2003
Springer
Comparative machine learning experiments have become an important methodology in empirical approaches to natural language processing (i) to investigate which machine learning algor...
CLEF
2003
Springer
14 years 24 days ago
2003
Springer
: The basic line of our action is first to use natural language processing to prune the texts and the query, and secondly to use an ontology to expand the queries. Last year The sy...
CICLING
2003
Springer
14 years 24 days ago
2003
Springer
Finite-state processing is typically based on structures that allow for efficient indexing and sequential search. However, this “rigid” framework has several disadvantages when...
CICLING
2003
Springer
14 years 24 days ago
2003
Springer
: In this paper, we present a spoken language understanding method based on the maximum entropy model. We first extract certain features from the corpus, and then train the maximum...