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...
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...
Alexander F. Gelbukh, Grigori Sidorov, Eduardo Lav...
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...
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...
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 ...
Comparative machine learning experiments have become an important methodology in empirical approaches to natural language processing (i) to investigate which machine learning algor...
: 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...
Finite-state processing is typically based on structures that allow for efficient indexing and sequential search. However, this “rigid” framework has several disadvantages when...
Alexander Troussov, Brian O'Donovan, Seppo Koskenn...
: 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...