Using Clusters of Concepts to Extract Semantic Relations from Standalone Documents

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

The extraction of semantic relations from texts is a hot topic. However, a large number of current methods are language and domain dependent, and the statistical and language-independent methods tend to work only with large amounts of text. This leaves out the extraction of semantic relations from standalone documents, such as single documents of unique subjects, reports from very specific domains, or small books. We propose a statistical method to extract semantic relations using clusters of concepts. Clusters are areas in the documents where concepts occur more frequently. When clusters of different concepts occur in the same areas, they may represent highly related concepts. Our method is language independent and we show comparative results for three different European languages.
Original languageUnknown
Title of host publicationProgress in Artificial Intelligence
EditorsLuís Correia, Luís Paulo Reis, José Cascalho
Place of PublicationHeidelberg
PublisherSpringer Berlin Heidelberg
Pages516-527
ISBN (Print)978-3-642-40668-3 / 978-3-642-40669-0
Publication statusPublished - 1 Jan 2013

Publication series

NameLecture Notes in Computer Science
PublisherSpringer Berlin Heidelberg
Number8154
ISSN (Print)0302-9743

Cite this

Silva, J. F. F. (2013). Using Clusters of Concepts to Extract Semantic Relations from Standalone Documents. In L. Correia, L. P. Reis, & J. Cascalho (Eds.), Progress in Artificial Intelligence (pp. 516-527). (Lecture Notes in Computer Science; No. 8154). Heidelberg: Springer Berlin Heidelberg.