Textual information is becoming available in abundance on the web, arising the requirement
of techniques and tools to extract the meaningful information. One of such an important …

Named Entity (NE) recognition is a task in which proper nouns and numerical information
are extracted from documents and are classified into categories such as person …

Abstract We apply Support Vector Machines (SVMs) to identify English base phrases
(chunks). SVMs are known to achieve high generalization performance even with input data …

Named Entity (NE) extraction is an important subtask of document processing such as
information extraction and question answering. A typical method used for NE extraction of …

We explore the use of Support Vector Machines (SVMs) for biomedical named entity
recognition. To make the SVM training with the available largest corpus–the GENIA corpus …

Abstract Background and Objectives: Named Entity Recognition (NER) and Relation
Extraction (RE) are two of the most studied tasks in biomedical Natural Language …

Paraphrases play an important role in the variety and complexity of natural language
documents. However, they add to the difficulty of natural language processing. Here we …

This book introduces Chinese language-processing issues and techniques to readers who
already have a basic background in natural language processing (NLP). Since the major …

We are trying to find paraphrases from Japanese news articles which can be used for
Information Extraction. We focused on the fact that a single event can be reported in more …

This paper considers the hypothesis that voting between multiple data representations can
be more accurate than voting between multiple learning models. This hypothesis has been …