WEB-SOBA: Word Embeddings-Based Semi-automatic Ontology Building for Aspect-Based Sentiment Classification

Fenna ten Haaf; Christopher Claassen; Ruben Eschauzier; Joanne Tjan; Daniël Buijs; Flavius Frasincar; Kim Schouten

doi:10.1007/978-3-030-77385-4_20

WEB-SOBA: Word Embeddings-Based Semi-automatic Ontology Building for Aspect-Based Sentiment Classification

Fenna ten Haaf, Christopher Claassen, Ruben Eschauzier, Joanne Tjan, Daniël Buijs, Flavius Frasincar^*, Kim Schouten

^*Corresponding author for this work

Econometrics

Research output: Chapter/Conference proceeding › Chapter › Academic

4 Citations (Scopus)

Abstract

For aspect-based sentiment analysis (ABSA), hybrid models combining ontology reasoning and machine learning approaches have achieved state-of-the-art results. In this paper, we introduce WEB-SOBA: a methodology to build a domain sentiment ontology in a semi-automatic manner from a domain-specific corpus using word embeddings. We evaluate the performance of a resulting ontology with a state-of-the-art hybrid ABSA framework, HAABSA, on the SemEval-2016 restaurant dataset. The performance is compared to a manually constructed ontology, and two other recent semi-automatically built ontologies. We show that WEB-SOBA is able to produce an ontology that achieves higher accuracy whilst requiring less than half of user time, compared to the previous approaches.

Original language	English
Title of host publication	The semantic web
Subtitle of host publication	18th Extended Semantic Web Conference (ESWC 2021)
Editors	Ruben Verborgh, Katja Hose, Heiko Paulheim, Pierre-Antoine Champin, Maria Maleshkova, Oscar Corcho, Petar Ristoski, Mehwish Alam
Publisher	Springer-Verlag
Pages	340-355
Number of pages	16
Volume	125
ISBN (Print)	9783030773847
DOIs	https://doi.org/10.1007/978-3-030-77385-4_20
Publication status	E-pub ahead of print - 31 May 2021
Event	18th European Semantic Web Conference, ESWC 2021 - Virtual, Online Duration: 6 Jun 2021 → 10 Jun 2021

Publication series

Series	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	12731 LNCS
ISSN	0302-9743

Conference

Conference	18th European Semantic Web Conference, ESWC 2021
City	Virtual, Online
Period	6/06/21 → 10/06/21

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Research programs

ESE - E&MS

Access to Document

10.1007/978-3-030-77385-4_20

Cite this

ten Haaf, F., Claassen, C., Eschauzier, R., Tjan, J., Buijs, D., Frasincar, F., & Schouten, K. (2021). WEB-SOBA: Word Embeddings-Based Semi-automatic Ontology Building for Aspect-Based Sentiment Classification. In R. Verborgh, K. Hose, H. Paulheim, P.-A. Champin, M. Maleshkova, O. Corcho, P. Ristoski, & M. Alam (Eds.), The semantic web: 18th Extended Semantic Web Conference (ESWC 2021) (Vol. 125, pp. 340-355). Springer-Verlag. Advance online publication. https://doi.org/10.1007/978-3-030-77385-4_20

ten Haaf, Fenna ; Claassen, Christopher ; Eschauzier, Ruben et al. / WEB-SOBA : Word Embeddings-Based Semi-automatic Ontology Building for Aspect-Based Sentiment Classification. The semantic web: 18th Extended Semantic Web Conference (ESWC 2021). editor / Ruben Verborgh ; Katja Hose ; Heiko Paulheim ; Pierre-Antoine Champin ; Maria Maleshkova ; Oscar Corcho ; Petar Ristoski ; Mehwish Alam. Vol. 125 Springer-Verlag, 2021. pp. 340-355 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12731 LNCS).

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ten Haaf, F, Claassen, C, Eschauzier, R, Tjan, J, Buijs, D, Frasincar, F & Schouten, K 2021, WEB-SOBA: Word Embeddings-Based Semi-automatic Ontology Building for Aspect-Based Sentiment Classification. in R Verborgh, K Hose, H Paulheim, P-A Champin, M Maleshkova, O Corcho, P Ristoski & M Alam (eds), The semantic web: 18th Extended Semantic Web Conference (ESWC 2021). vol. 125, Springer-Verlag, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 12731 LNCS, pp. 340-355, 18th European Semantic Web Conference, ESWC 2021, Virtual, Online, 6/06/21. https://doi.org/10.1007/978-3-030-77385-4_20

WEB-SOBA: Word Embeddings-Based Semi-automatic Ontology Building for Aspect-Based Sentiment Classification. / ten Haaf, Fenna; Claassen, Christopher; Eschauzier, Ruben et al.
The semantic web: 18th Extended Semantic Web Conference (ESWC 2021). ed. / Ruben Verborgh; Katja Hose; Heiko Paulheim; Pierre-Antoine Champin; Maria Maleshkova; Oscar Corcho; Petar Ristoski; Mehwish Alam. Vol. 125 Springer-Verlag, 2021. p. 340-355 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12731 LNCS).

Research output: Chapter/Conference proceeding › Chapter › Academic

TY - CHAP

T1 - WEB-SOBA

T2 - 18th European Semantic Web Conference, ESWC 2021

AU - ten Haaf, Fenna

AU - Claassen, Christopher

AU - Eschauzier, Ruben

AU - Tjan, Joanne

AU - Buijs, Daniël

AU - Frasincar, Flavius

AU - Schouten, Kim

PY - 2021/5/31

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N2 - For aspect-based sentiment analysis (ABSA), hybrid models combining ontology reasoning and machine learning approaches have achieved state-of-the-art results. In this paper, we introduce WEB-SOBA: a methodology to build a domain sentiment ontology in a semi-automatic manner from a domain-specific corpus using word embeddings. We evaluate the performance of a resulting ontology with a state-of-the-art hybrid ABSA framework, HAABSA, on the SemEval-2016 restaurant dataset. The performance is compared to a manually constructed ontology, and two other recent semi-automatically built ontologies. We show that WEB-SOBA is able to produce an ontology that achieves higher accuracy whilst requiring less than half of user time, compared to the previous approaches.

AB - For aspect-based sentiment analysis (ABSA), hybrid models combining ontology reasoning and machine learning approaches have achieved state-of-the-art results. In this paper, we introduce WEB-SOBA: a methodology to build a domain sentiment ontology in a semi-automatic manner from a domain-specific corpus using word embeddings. We evaluate the performance of a resulting ontology with a state-of-the-art hybrid ABSA framework, HAABSA, on the SemEval-2016 restaurant dataset. The performance is compared to a manually constructed ontology, and two other recent semi-automatically built ontologies. We show that WEB-SOBA is able to produce an ontology that achieves higher accuracy whilst requiring less than half of user time, compared to the previous approaches.

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T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 340

EP - 355

BT - The semantic web

A2 - Verborgh, Ruben

A2 - Hose, Katja

A2 - Paulheim, Heiko

A2 - Champin, Pierre-Antoine

A2 - Maleshkova, Maria

A2 - Corcho, Oscar

A2 - Ristoski, Petar

A2 - Alam, Mehwish

PB - Springer-Verlag

Y2 - 6 June 2021 through 10 June 2021

ER -

ten Haaf F, Claassen C, Eschauzier R, Tjan J, Buijs D, Frasincar F et al. WEB-SOBA: Word Embeddings-Based Semi-automatic Ontology Building for Aspect-Based Sentiment Classification. In Verborgh R, Hose K, Paulheim H, Champin PA, Maleshkova M, Corcho O, Ristoski P, Alam M, editors, The semantic web: 18th Extended Semantic Web Conference (ESWC 2021). Vol. 125. Springer-Verlag. 2021. p. 340-355. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 12731 LNCS). Epub 2021 May 31. doi: 10.1007/978-3-030-77385-4_20

WEB-SOBA: Word Embeddings-Based Semi-automatic Ontology Building for Aspect-Based Sentiment Classification

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