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DOI: 10.4230/OASIcs.SLATE.2016.4

Comparing and Benchmarking Semantic Measures Using SMComp

Authors: Teresa Costa and José Paulo Leal

Published in: OASIcs, Volume 51, 5th Symposium on Languages, Applications and Technologies (SLATE'16) (2016)

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.

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Teresa Costa and José Paulo Leal. Comparing and Benchmarking Semantic Measures Using SMComp. In 5th Symposium on Languages, Applications and Technologies (SLATE'16). Open Access Series in Informatics (OASIcs), Volume 51, pp. 4:1-4:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{costa_et_al:OASIcs.SLATE.2016.4,
  author =	{Costa, Teresa and Leal, Jos\'{e} Paulo},
  title =	{{Comparing and Benchmarking Semantic Measures Using SMComp}},
  booktitle =	{5th Symposium on Languages, Applications and Technologies (SLATE'16)},
  pages =	{4:1--4:13},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-006-4},
  ISSN =	{2190-6807},
  year =	{2016},
  volume =	{51},
  editor =	{Mernik, Marjan and Leal, Jos\'{e} Paulo and Gon\c{c}alo Oliveira, Hugo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2016.4},
  URN =		{urn:nbn:de:0030-drops-60090},
  doi =		{10.4230/OASIcs.SLATE.2016.4},
  annote =	{Keywords: Semantic similarity, semantic relatedness, testbed, web application}
}

Document

DOI: 10.4230/OASIcs.SLATE.2014.201

Multiscale Parameter Tuning of a Semantic Relatedness Algorithm

Authors: José Paulo Leal and Teresa Costa

Published in: OASIcs, Volume 38, 3rd Symposium on Languages, Applications and Technologies (2014)

Abstract

The research presented in this paper builds on previous work that lead to the definition of a family of semantic relatedness algorithms that compute a proximity given as input a pair of concept labels. The algorithms depends on a semantic graph, provided as RDF data, and on a particular set of weights assigned to the properties of RDF statements (types of arcs in the RDF graph). The current research objective is to automatically tune the weights for a given graph in order to increase the proximity quality. The quality of a semantic relatedness method is usually measured against a benchmark data set. The results produced by the method are compared with those on the benchmark using the Spearman's rank coefficient. This methodology works the other way round and uses this coefficient to tune the proximity weights. The tuning process is controlled by a genetic algorithm using the Spearman's rank coefficient as the fitness function. The genetic algorithm has its own set of parameters which also need to be tuned. Bootstrapping is based on a statistical method for generating samples that is used in this methodology to enable a large number of repetitions of the genetic algorithm, exploring the results of alternative parameter settings. This approach raises several technical challenges due to its computational complexity. This paper provides details on the techniques used to speedup this process. The proposed approach was validated with the WordNet 2.0 and the WordSim-353 data set. Several ranges of parameters values were tested and the obtained results are better than the state of the art methods for computing semantic relatedness using the WordNet 2.0, with the advantage of not requiring any domain knowledge of the ontological graph.

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José Paulo Leal and Teresa Costa. Multiscale Parameter Tuning of a Semantic Relatedness Algorithm. In 3rd Symposium on Languages, Applications and Technologies. Open Access Series in Informatics (OASIcs), Volume 38, pp. 201-213, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2014)

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@InProceedings{leal_et_al:OASIcs.SLATE.2014.201,
  author =	{Leal, Jos\'{e} Paulo and Costa, Teresa},
  title =	{{Multiscale Parameter Tuning of a Semantic Relatedness Algorithm}},
  booktitle =	{3rd Symposium on Languages, Applications and Technologies},
  pages =	{201--213},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-68-2},
  ISSN =	{2190-6807},
  year =	{2014},
  volume =	{38},
  editor =	{Pereira, Maria Jo\~{a}o Varanda and Leal, Jos\'{e} Paulo and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2014.201},
  URN =		{urn:nbn:de:0030-drops-45702},
  doi =		{10.4230/OASIcs.SLATE.2014.201},
  annote =	{Keywords: semantic similarity, linked data, genetic algorithms, bootstrapping, WordNet}
}

Document

DOI: 10.4230/OASIcs.SLATE.2013.67

Publishing Linked Data with DaPress

Authors: Teresa Costa and José Paulo Leal

Published in: OASIcs, Volume 29, 2nd Symposium on Languages, Applications and Technologies (2013)

Abstract

The central idea of the Web of Data is to interlink the information available in the Web, most of which is actually stored in databases rather than in static HTML pages. Tools to convert relational data into semantic web formats and publish then as linked data are essential to fulfill the vision of a web of data available for automatic processing, as web content is currently available to humans. This paper presents DaPress, a simple tool to publish linked data on the Web, that maps a relational database to an RDF triplestore and creates a SPARQL access point. The paper reports the use of DaPress to publish the database of Authenticus, a system that automatically assigns publication authors to known Portuguese researchers and institutions.

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Teresa Costa and José Paulo Leal. Publishing Linked Data with DaPress. In 2nd Symposium on Languages, Applications and Technologies. Open Access Series in Informatics (OASIcs), Volume 29, pp. 67-81, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InProceedings{costa_et_al:OASIcs.SLATE.2013.67,
  author =	{Costa, Teresa and Leal, Jos\'{e} Paulo},
  title =	{{Publishing Linked Data with DaPress}},
  booktitle =	{2nd Symposium on Languages, Applications and Technologies},
  pages =	{67--81},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-52-1},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{29},
  editor =	{Leal, Jos\'{e} Paulo and Rocha, Ricardo and Sim\~{o}es, Alberto},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2013.67},
  URN =		{urn:nbn:de:0030-drops-40312},
  doi =		{10.4230/OASIcs.SLATE.2013.67},
  annote =	{Keywords: RDF, RDF Schema, Relational data; Semantic web}
}

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Comparing and Benchmarking Semantic Measures Using SMComp

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Multiscale Parameter Tuning of a Semantic Relatedness Algorithm

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Publishing Linked Data with DaPress

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