Character-based Neural Embeddings for Tweet Clustering

Svitlana Vakulenko; Lyndon Nixon; Mihai Lupu

doi:10.18653/v1/W17-1105

Character-based Neural Embeddings for Tweet Clustering

Svitlana Vakulenko
, Lyndon Nixon
, Mihai Lupu

Institute for Data, Process and Knowledge Management (AE Polleres)

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

Abstract

In this paper we show how the performance of tweet clustering can be improved by leveraging character-based neural networks. The proposed approach overcomes the limitations related to the vocabulary explosion in the word-based models and allows for the seamless processing of the multilingual content.

Original language	English
Title of host publication	SocialNLP 2017 - 5th International Workshop on Natural Language Processing for Social Media
Subtitle of host publication	Proceedings of the Workshop AFNLP SIG SocialNLP
Publisher	Association for Computational Linguistics (ACL)
Pages	36-44
Number of pages	9
ISBN (Electronic)	9781945626425
DOIs	https://doi.org/10.18653/v1/W17-1105
Publication status	Published - 2017
Event	5th International Workshop on Natural Language Processing for Social Media, SocialNLP 2017, associated with EACL 2017 - Valencia, Spain Duration: 3 Apr 2017 → …

Conference

Conference	5th International Workshop on Natural Language Processing for Social Media, SocialNLP 2017, associated with EACL 2017
Country/Territory	Spain
City	Valencia
Period	3/04/17 → …

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Publisher Copyright:
© 2017 Association for Computational Linguistics sion (Section 6) summarizes our findings and directions for future work.

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10.18653/v1/W17-1105Licence: CC BY

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@inproceedings{70e092c1d7fe4b61828db7d13ab1062c,

title = "Character-based Neural Embeddings for Tweet Clustering",

abstract = "In this paper we show how the performance of tweet clustering can be improved by leveraging character-based neural networks. The proposed approach overcomes the limitations related to the vocabulary explosion in the word-based models and allows for the seamless processing of the multilingual content.",

author = "Svitlana Vakulenko and Lyndon Nixon and Mihai Lupu",

note = "Publisher Copyright: {\textcopyright} 2017 Association for Computational Linguistics sion (Section 6) summarizes our findings and directions for future work.; 5th International Workshop on Natural Language Processing for Social Media, SocialNLP 2017, associated with EACL 2017 ; Conference date: 03-04-2017",

year = "2017",

doi = "10.18653/v1/W17-1105",

language = "English",

pages = "36--44",

booktitle = "SocialNLP 2017 - 5th International Workshop on Natural Language Processing for Social Media",

publisher = "Association for Computational Linguistics (ACL)",

address = "Australia",

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Vakulenko, S, Nixon, L & Lupu, M 2017, Character-based Neural Embeddings for Tweet Clustering. in SocialNLP 2017 - 5th International Workshop on Natural Language Processing for Social Media: Proceedings of the Workshop AFNLP SIG SocialNLP. Association for Computational Linguistics (ACL), pp. 36-44, 5th International Workshop on Natural Language Processing for Social Media, SocialNLP 2017, associated with EACL 2017, Valencia, Spain, 3/04/17. https://doi.org/10.18653/v1/W17-1105

Character-based Neural Embeddings for Tweet Clustering. / Vakulenko, Svitlana; Nixon, Lyndon; Lupu, Mihai.
SocialNLP 2017 - 5th International Workshop on Natural Language Processing for Social Media: Proceedings of the Workshop AFNLP SIG SocialNLP. Association for Computational Linguistics (ACL), 2017. p. 36-44.

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

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AU - Vakulenko, Svitlana

AU - Nixon, Lyndon

AU - Lupu, Mihai

PY - 2017

Y1 - 2017

N2 - In this paper we show how the performance of tweet clustering can be improved by leveraging character-based neural networks. The proposed approach overcomes the limitations related to the vocabulary explosion in the word-based models and allows for the seamless processing of the multilingual content.

AB - In this paper we show how the performance of tweet clustering can be improved by leveraging character-based neural networks. The proposed approach overcomes the limitations related to the vocabulary explosion in the word-based models and allows for the seamless processing of the multilingual content.

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DO - 10.18653/v1/W17-1105

M3 - Contribution to conference proceedings

AN - SCOPUS:85058622415

SP - 36

EP - 44

BT - SocialNLP 2017 - 5th International Workshop on Natural Language Processing for Social Media

PB - Association for Computational Linguistics (ACL)

T2 - 5th International Workshop on Natural Language Processing for Social Media, SocialNLP 2017, associated with EACL 2017

Y2 - 3 April 2017

ER -

Character-based Neural Embeddings for Tweet Clustering

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