John Mcnaught

Details der Publikationsliste

Zeitraum

1993 - 2009

Anzahl

23

Co-Autoren

BioMed Central Research How to make the most of NE dictionaries in statistical NER (2009)

Bmc Bioinformatics, Yutaka Sasaki, Yoshimasa Tsuruoka, John Mcnaught, Sophia Ananiadou, John Mcnaught, ...

growth of a wide range of repositories of biomedical data and literature. The automatic construction and update of scientific knowledge bases is a major research topic in Biofrom

Construction of an annotated corpus to support biomedical information extraction (2009)

Thompson, Paul, Iqbal, Syed A, McNaught, John, Ananiadou, Sophia

Abstract Background Information Extraction (IE) is a component of text mining that facilitates knowledge discovery by automatically locating instances of interesting biomedical events from huge...

THE G~INERATION OF TERM DEFINITIONS FROM AN ON-LINE TEP~NOLOGICAL ~SA[~S (2009)

John Mcnaught

A new type of machine dictionary is described, which uses terminological relations to build up a semantic network representing the terms of a particular subject field, through interaction with the...

An Annotation Type System for a Data-Driven NLP Pipeline (2009)

Udo Hahn, Ekaterina Buyko, Katrin Tomanek, Scott Piao, John Mcnaught, Yoshimasa Tsuruoka, ...

We introduce an annotation type system for a data-driven NLP core system. The specifications cover formal document structure and document meta information, as well as the linguistic levels of...

How to make the most of NE dictionaries in statistical NER (2008)

Sasaki, Yutaka, Tsuruoka, Yoshimasa, McNaught, John, Ananiadou, Sophia

Abstract Background When term ambiguity and variability are very high, dictionary-based Named Entity Recognition ( NER ) is not an ideal solution even though large-scale terminological resources are...

BOOTStrep Annotation Scheme – Encoding Information for Text Mining (2008)

Scott Piao, Ekaterina Buyko, Yoshimasa Tsuruoka, Katrin Tomanek, John Mcnaught, Udo Hahn, ...

Annotation of information in corpora is an important aspect of text mining. It bridges between the information hidden in natural language texts and the semantic search queries for the information...

Normalizing biomedical terms by minimizing ambiguity and variability (2008)

Tsuruoka, Yoshimasa, McNaught, John, Ananiadou, Sophia

Abstract Background One of the difficulties in mapping biomedical named entities, e.g. genes, proteins, chemicals and diseases, to their concept identifiers stems from the potential variability of...

Ontology-enablement of a system for semantic annotation of digital documents (2008)

William J Black, Simon Jowett, Thomas Mavroudakis, John Mcnaught, Babis Theodoulidis, Argyrios Vasilakopoulos, ...

We describe the recent enhancement of the CAFETIERE formalism (Conceptual Annotation of Facts, Events, Terms, Individual Entities and RElations) with the ability to link natural language words and...

Extracting semantic clusters from the alignment of definitions Gerardo SIERRA (2007)

Apdo Postal, John Mcnaught

Through the alignment of definitions from two or more different sources, it is possible to retrieve pairs of words that can be used indistinguishably in the same sentence without changing the meaning...

The (2007)

Eugenia Eumeridou, Blaise Nkwenti-azeh, John Mcnaught

contribution of verbal semantic content towards term recognition

Learning string similarity measures for gene/protein name dictionary look-up using logistic regression (2007)

Tsuruoka, Yoshimasa, McNaught, John, Tsujii, Jun'i;chi, Ananiadou, Sophia

Motivation: One of the bottlenecks of biomedical data integration is variation of terms. Exact string matching often fails to associate a name with its biological concept, i.e. ID or accession number...

Mining Opinion Polarity Relations of Citations (2006)

Scott S. Piao, Sophia Ananiadou, Yoshimasa Tsuruoka, Yutaka Sasaki, John Mcnaught

Opinion mining has been receiving increasing attention recently, and various approaches have been suggested for mining sentiment information, such as mining attitudes or opinions about a topic or...

Text mining and ontologies in biomedicine: making sense of raw text (2005)

Irena Spasic, Sophia Ananiadou, John Mcnaught

The volume of biomedical literature is increasing at such a rate that it is becoming difficult to locate, retrieve and manage the reported information without text mining, which aims to automatically...

Text mining and ontologies in biomedicine: Making sense of raw text (2005)

Spasic, Irena, Ananiadou, Sophia, McNaught, John, Kumar, Anand

The volume of biomedical literature is increasing at such a rate that it is becoming difficult to locate, retrieve and manage the reported information without text mining, which aims to automatically...

Coupling Information Extraction and Data Mining for (2004)

Ontology Learning In, Myra Spiliopoulou, Fabio Rinaldi, William J. Black, Gian Piero Zarri, M. Mueller, ...

Strategic decision making, especially in the areas of business intelligence and competitive intelligence, requires the acquisition of decision-relevant information pieces like market trends, fusions...

EXTRACTING SEMANTIC CLUSTERS FROM MRDs FOR AN ONOMASIOLOGICAL SEARCH DICTIONARY (2000)

Sierra, Gerardo, McNaught, John

The ideal onomasiological dictionary should allow users to search for a word by introducing the knowledge they already have about a concept. Such an onomasiological search relies crucially on indexed...

User Needs for Textual Corpora in Natural Language Processing (1993)

MCNAUGHT, JOHN

We discuss the needs of natural language processing (NLP) researchers in relation to corpora. Reasons for the growing interest in corpora by NLP researchers are given. Their needs are quite different...