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Systems General Terms Experimentation, Algorithms

By Ted Pedersen, Bridget Mcinnes, Tutorial Topics, Serguei Pakhomov and Ying Liu

Abstract

The ability to quantify the degree to which concepts are similar or related to each other is a key component in many Natural Language Processing (NLP) and Artificial Intelligence (AI) applications. For example, in a document search application, it can be very useful to identify text snippets that contain terms that are similar to (but not identical) to those provided by a user. This tutorial will introduce the theory behind measures of semantic similarity and relatedness, and show how these can be applied in the medical domain by using freely–available open–source software 1 (UMLS::Similarity). This software takes advantage of the Unified Medical Language System 2 (UMLS), which is maintained by the National Library of Medicine (USA). The tutorial will also show how to evaluate existing measures with manually–created reference standards

Topics: I.2 [Artificial Intelligence, Natural Language Processing
Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.309.4856
Provided by: CiteSeerX
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