Abstract
The goal of the semantic measures is to compare pairs of concepts, words, sentences or named entities. Their categorization depends on what they measure. If a measure only considers taxonomy relationships is a similarity measure; if it considers all type of relationships it is a relatedness measure.
The evaluation process of these measures usually relies on semantic gold standards. These datasets, with several pairs of words with a rating assigned by persons, are used to assess how well a semantic measure performs.
There are a few frameworks that provide tools to compute and analyze several well-known measures. This paper presents a novel tool - SMComp - a testbed designed for path-based semantic measures. At its current state, it is a domain-specific tool using three different versions of WordNet.
SMComp has two views: one to compute semantic measures of a pair of words and another to assess a semantic measure using a dataset. On the first view, it offers several measures described in the literature as well as the possibility of creating a new measure, by introducing Java code snippets on the GUI. The other view offers a large set of semantic benchmarks to use in the assessment process. It also offers the possibility of uploading a custom dataset to be used in the assessment.
BibTeX - Entry
@InProceedings{costa_et_al:OASIcs:2016:6009,
author = {Teresa Costa and Jos{\'e} Paulo Leal},
title = {{Comparing and Benchmarking Semantic Measures Using SMComp}},
booktitle = {5th Symposium on Languages, Applications and Technologies (SLATE'16)},
pages = {4:1--4:13},
series = {OpenAccess Series in Informatics (OASIcs)},
ISBN = {978-3-95977-006-4},
ISSN = {2190-6807},
year = {2016},
volume = {51},
editor = {Marjan Mernik and Jos{\'e} Paulo Leal and Hugo Gon{\c{c}}alo Oliveira},
publisher = {Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
address = {Dagstuhl, Germany},
URL = {http://drops.dagstuhl.de/opus/volltexte/2016/6009},
URN = {urn:nbn:de:0030-drops-60090},
doi = {10.4230/OASIcs.SLATE.2016.4},
annote = {Keywords: Semantic similarity, semantic relatedness, testbed, web application}
}
Keywords: |
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Semantic similarity, semantic relatedness, testbed, web application |
Collection: |
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5th Symposium on Languages, Applications and Technologies (SLATE'16) |
Issue Date: |
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2016 |
Date of publication: |
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21.06.2016 |