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Automatic Biological Term Annotation

Using n-gram and Classification Models

Jezik AngleščinaAngleščina
Knjiga Mehka
Knjiga Automatic Biological Term Annotation Sittichai Jiampojamarn
Koda Libristo: 06819675
Založba VDM Verlag Dr. Müller, november 2008
Exciting research in biology has resulted in a large§amount of biological publications. §Knowledge d... Celoten opis
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Exciting research in biology has resulted in a large§amount of biological publications. §Knowledge discovery in biology becomes an interesting§task which can be established§by recognizing terms in text to extract useful§information such as interaction relationships.§§We propose the Automatic Biological Term Annotation§(ABTA) system which uses classification methods to§annotate terms in text. A novel method is presented§to express lexical features in pattern notations.§Prefix and suffix characters are used instead of§lists of potential terms or external resources. We§demonstrate that part-of-speech tag information is§the most effective attribute. Creating classification§exemplars is conducted from text by using word n-gram§model. We illustrate improvements on our system's§performance which depends on the feature attributes§we define. Biological concept markers are also§assigned to each located term indicating its meaning.§Our results are comparable to the performance of§other existing systems while our system retains§simplicity and generalizability. Exciting research in biology has resulted in a large§amount of biological publications. §Knowledge discovery in biology becomes an interesting§task which can be established§by recognizing terms in text to extract useful§information such as interaction relationships.§We propose the Automatic Biological Term Annotation§(ABTA) system which uses classification methods to§annotate terms in text. A novel method is presented§to express lexical features in pattern notations.§Prefix and suffix characters are used instead of§lists of potential terms or external resources. We§demonstrate that part-of-speech tag information is§the most effective attribute. Creating classification§exemplars is conducted from text by using word n-gram§model. We illustrate improvements on our system''s§performance which depends on the feature attributes§we define. Biological concept markers are also§assigned to each located term indicating its meaning.§Our results are comparable to the performance of§other existing systems while our system retains§simplicity and generalizability.

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O knjigi

Polni naslov Automatic Biological Term Annotation
Jezik Angleščina
Vezava Knjiga - Mehka
Datum izida 2009
Število strani 96
EAN 9783639107333
Koda Libristo 06819675
Teža 159
Mere 150 x 220 x 6
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1 Dodajte knjigo v košarico in izberite dostavo kot darilo 2 V zameno vam bomo poslali kupon 3 Knjiga bo dostavljena na naslov obdarovanca

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