Entity Embedding Analogy for Implicit Link Discovery

Nada Mimouni; Jean Claude Moissinac; Anh Tuan Vu

doi:10.1007/978-3-030-32327-1_25

Entity Embedding Analogy for Implicit Link Discovery

Nada Mimouni
, Jean Claude Moissinac
, Anh Tuan Vu

Telecom Paris

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In this work we are interested in the problem of knowledge graph (KG) incompleteness, which we propose to solve by discovering implicit triples using observed ones in the incomplete graph leveraging analogy structures deducted from a KG embedding model. We use a language modelling approach that we adapt to entities and relations. The first results show that analogical inferences in the projected vector space is relevant to a link prediction task.

Original language	English
Title of host publication	The Semantic Web
Subtitle of host publication	ESWC 2019 Satellite Events - ESWC 2019 Satellite Events, Revised Selected Papers
Editors	Pascal Hitzler, Sabrina Kirrane, Olaf Hartig, Victor de Boer, Stefan Schlobach, Maria-Esther Vidal, Maria Maleshkova, Karl Hammar, Nelia Lasierra, Steffen Stadtmüller, Katja Hose, Ruben Verborgh
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	126-129
Number of pages	4
ISBN (Print)	9783030323264
DOIs	https://doi.org/10.1007/978-3-030-32327-1_25
Publication status	Published - 1 Jan 2019
Event	16th Extended Semantic Web Conference, ESWC 2019 - Portoroz, Slovenia Duration: 2 Jun 2019 → 6 Jun 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11762 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	16th Extended Semantic Web Conference, ESWC 2019
Country/Territory	Slovenia
City	Portoroz
Period	2/06/19 → 6/06/19

Access to Document

10.1007/978-3-030-32327-1_25

Cite this

Mimouni, N., Moissinac, J. C., & Vu, A. T. (2019). Entity Embedding Analogy for Implicit Link Discovery. In P. Hitzler, S. Kirrane, O. Hartig, V. de Boer, S. Schlobach, M.-E. Vidal, M. Maleshkova, K. Hammar, N. Lasierra, S. Stadtmüller, K. Hose, & R. Verborgh (Eds.), The Semantic Web: ESWC 2019 Satellite Events - ESWC 2019 Satellite Events, Revised Selected Papers (pp. 126-129). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11762 LNCS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-32327-1_25

Mimouni, Nada ; Moissinac, Jean Claude ; Vu, Anh Tuan. / Entity Embedding Analogy for Implicit Link Discovery. The Semantic Web: ESWC 2019 Satellite Events - ESWC 2019 Satellite Events, Revised Selected Papers. editor / Pascal Hitzler ; Sabrina Kirrane ; Olaf Hartig ; Victor de Boer ; Stefan Schlobach ; Maria-Esther Vidal ; Maria Maleshkova ; Karl Hammar ; Nelia Lasierra ; Steffen Stadtmüller ; Katja Hose ; Ruben Verborgh. Springer Science and Business Media Deutschland GmbH, 2019. pp. 126-129 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Entity Embedding Analogy for Implicit Link Discovery",

abstract = "In this work we are interested in the problem of knowledge graph (KG) incompleteness, which we propose to solve by discovering implicit triples using observed ones in the incomplete graph leveraging analogy structures deducted from a KG embedding model. We use a language modelling approach that we adapt to entities and relations. The first results show that analogical inferences in the projected vector space is relevant to a link prediction task.",

author = "Nada Mimouni and Moissinac, \{Jean Claude\} and Vu, \{Anh Tuan\}",

note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 16th Extended Semantic Web Conference, ESWC 2019 ; Conference date: 02-06-2019 Through 06-06-2019",

year = "2019",

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doi = "10.1007/978-3-030-32327-1\_25",

language = "English",

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series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Science and Business Media Deutschland GmbH",

pages = "126--129",

editor = "Pascal Hitzler and Sabrina Kirrane and Olaf Hartig and \{de Boer\}, Victor and Stefan Schlobach and Maria-Esther Vidal and Maria Maleshkova and Karl Hammar and Nelia Lasierra and Steffen Stadtm{\"u}ller and Katja Hose and Ruben Verborgh",

booktitle = "The Semantic Web",

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Mimouni, N, Moissinac, JC & Vu, AT 2019, Entity Embedding Analogy for Implicit Link Discovery. in P Hitzler, S Kirrane, O Hartig, V de Boer, S Schlobach, M-E Vidal, M Maleshkova, K Hammar, N Lasierra, S Stadtmüller, K Hose & R Verborgh (eds), The Semantic Web: ESWC 2019 Satellite Events - ESWC 2019 Satellite Events, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11762 LNCS, Springer Science and Business Media Deutschland GmbH, pp. 126-129, 16th Extended Semantic Web Conference, ESWC 2019, Portoroz, Slovenia, 2/06/19. https://doi.org/10.1007/978-3-030-32327-1_25

Entity Embedding Analogy for Implicit Link Discovery. / Mimouni, Nada; Moissinac, Jean Claude; Vu, Anh Tuan.
The Semantic Web: ESWC 2019 Satellite Events - ESWC 2019 Satellite Events, Revised Selected Papers. ed. / Pascal Hitzler; Sabrina Kirrane; Olaf Hartig; Victor de Boer; Stefan Schlobach; Maria-Esther Vidal; Maria Maleshkova; Karl Hammar; Nelia Lasierra; Steffen Stadtmüller; Katja Hose; Ruben Verborgh. Springer Science and Business Media Deutschland GmbH, 2019. p. 126-129 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11762 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - Entity Embedding Analogy for Implicit Link Discovery

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AU - Moissinac, Jean Claude

AU - Vu, Anh Tuan

N1 - Publisher Copyright: © Springer Nature Switzerland AG 2019.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - In this work we are interested in the problem of knowledge graph (KG) incompleteness, which we propose to solve by discovering implicit triples using observed ones in the incomplete graph leveraging analogy structures deducted from a KG embedding model. We use a language modelling approach that we adapt to entities and relations. The first results show that analogical inferences in the projected vector space is relevant to a link prediction task.

AB - In this work we are interested in the problem of knowledge graph (KG) incompleteness, which we propose to solve by discovering implicit triples using observed ones in the incomplete graph leveraging analogy structures deducted from a KG embedding model. We use a language modelling approach that we adapt to entities and relations. The first results show that analogical inferences in the projected vector space is relevant to a link prediction task.

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DO - 10.1007/978-3-030-32327-1_25

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A2 - Kirrane, Sabrina

A2 - Hartig, Olaf

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A2 - Schlobach, Stefan

A2 - Vidal, Maria-Esther

A2 - Maleshkova, Maria

A2 - Hammar, Karl

A2 - Lasierra, Nelia

A2 - Stadtmüller, Steffen

A2 - Hose, Katja

A2 - Verborgh, Ruben

PB - Springer Science and Business Media Deutschland GmbH

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Mimouni N, Moissinac JC, Vu AT. Entity Embedding Analogy for Implicit Link Discovery. In Hitzler P, Kirrane S, Hartig O, de Boer V, Schlobach S, Vidal ME, Maleshkova M, Hammar K, Lasierra N, Stadtmüller S, Hose K, Verborgh R, editors, The Semantic Web: ESWC 2019 Satellite Events - ESWC 2019 Satellite Events, Revised Selected Papers. Springer Science and Business Media Deutschland GmbH. 2019. p. 126-129. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-32327-1_25

Entity Embedding Analogy for Implicit Link Discovery

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