MaSTerClass: a case-based reasoning system for the classification of biomedical terms.

@article{citeulike:136572, abstract = {MOTIVATION: The sheer volume of textually described biomedical knowledge exerts the need for natural language processing (NLP) applications in order to allow flexible and efficient access to relevant information. Specialised semantic networks (such as biomedical ontologies, terminologies or semantic lexicons) can significantly enhance these applications by supplying the necessary terminological information in a machine-readable form. Due to the explosive growth of bio-literature, new terms (representing newly identified concepts or variations of the existing terms) may not be explicitly described within the network and hence cannot be fully exploited by NLP applications. Linguistic and statistical clues can be used to extract many new terms from free text. The extracted terms still need to be correctly positioned relative to other terms in the network. Classification as a means of semantic typing represents the first step in updating a semantic network with new terms. RESULTS: The MASTERCLASS system implements the case-based reasoning methodology for the classification of biomedical terms. AVAILABILITY: MASTERCLASS is available at http://www.cbr-masterclass.org. It is distributed under an open source licence for educational and research purposes. The software requires Java, JWDSP, Ant, MySQL and X-hive to be installed and licences obtained separately where needed.}, address = {School of Chemistry, The University of Manchester, Sackville Street, PO Box 88, Manchester, M60 1QD, UK.}, author = {Spasic, Irena and Ananiadou, Sophia and Tsujii, Jun-Ichi I. }, citeulike-article-id = {136572}, comment = {http://www.cbr-masterclass.org}, issn = {1367-4803}, journal = {Bioinformatics}, keywords = {bib, bio, cbr, class, nlp, software, spasic, srb, term, tool}, month = {March}, posted-at = {2005-03-22 17:21:16}, priority = {0}, title = {MaSTerClass: a case-based reasoning system for the classification of biomedical terms.}, url = {http://view.ncbi.nlm.nih.gov/pubmed/15728115}, year = {2005} }

TY - JOUR ID - citeulike:136572 L3 - citeulike-article-id:136572 TI - MaSTerClass: a case-based reasoning system for the classification of biomedical terms. JF - Bioinformatics AD - School of Chemistry, The University of Manchester, Sackville Street, PO Box 88, Manchester, M60 1QD, UK. SN - 1367-4803 N2 - MOTIVATION: The sheer volume of textually described biomedical knowledge exerts the need for natural language processing (NLP) applications in order to allow flexible and efficient access to relevant information. Specialised semantic networks (such as biomedical ontologies, terminologies or semantic lexicons) can significantly enhance these applications by supplying the necessary terminological information in a machine-readable form. Due to the explosive growth of bio-literature, new terms (representing newly identified concepts or variations of the existing terms) may not be explicitly described within the network and hence cannot be fully exploited by NLP applications. Linguistic and statistical clues can be used to extract many new terms from free text. The extracted terms still need to be correctly positioned relative to other terms in the network. Classification as a means of semantic typing represents the first step in updating a semantic network with new terms. RESULTS: The MASTERCLASS system implements the case-based reasoning methodology for the classification of biomedical terms. AVAILABILITY: MASTERCLASS is available at http://www.cbr-masterclass.org. It is distributed under an open source licence for educational and research purposes. The software requires Java, JWDSP, Ant, MySQL and X-hive to be installed and licences obtained separately where needed. KW - bib KW - bio KW - cbr KW - class KW - nlp KW - software KW - spasic KW - srb KW - term KW - tool N1 - http://www.cbr-masterclass.org AU - Spasic, Irena AU - Ananiadou, Sophia AU - Tsujii, Jun-Ichi PY - 2005/03/03/ UR - http://view.ncbi.nlm.nih.gov/pubmed/15728115 ER -