izpis_h1_title_alt

Evaluating context features for medical relation mining
Vintar, Špela (Avtor)

URLURL - Predstavitvena datoteka, za dostop obiščite http://www.informatik.hu-berlin.de/%7Escheffer/publications/ws03proc/vintar.pdf Novo okno

Izvleček
The paper describes a set of experiments aimed at identifying and evaluating context features and machine learning methods to identify medical semantic relations in texts. We use manually constructed lists of pairs of MeSH-classesthat represent specific relations, and a linguistically and semantically annotated corpus of medical abstracts to explore the contextual features of relations. Using hierarchical clustering we compare and evaluate linguistic aspects of relation context and different data representations. Through feature selection on a small data set we also show that relations are characterized by typical context words, and by isolating these we can construct a more robust language model representing the target relation. Finally, we present graph visualization as an alternative and promising way ofdata representation facilitating feature selection.

Jezik:Angleški jezik
Ključne besede:korpusna lingvistika, jezikoslovje, leksikologija, semantika, informacijski sistemi, jezik stroke, strokovni jezik, medicina
Vrsta gradiva:Delo ni kategorizirano (r6)
Tipologija:1.08 - Objavljeni znanstveni prispevek na konferenci
Organizacija:FF - Filozofska fakulteta
Leto izida:2003
Št. strani:Str. 64-70
UDK:004.4.:61
COBISS.SI-ID:28772450 Povezava se odpre v novem oknu
Število ogledov:262
Število prenosov:93
Metapodatki:XML RDF-CHPDL DC-XML DC-RDF
 
Skupna ocena:(0 glasov)
Vaša ocena:Ocenjevanje je dovoljeno samo prijavljenim uporabnikom.
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Sekundarni jezik

Jezik:Angleški jezik
Ključne besede:Natural language processing, Linguistics, Semantics, Information systems, Unified medical language system

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