Standard
Wear the right head : Comparing strategies for encoding sentences for aspect extraction. / Malykh, Valentin; Alekseev, Anton; Tutubalina, Elena; Shenbin, Ilya; Nikolenko, Sergey.
Analysis of Images, Social Networks and Texts - 8th International Conference, AIST 2019, Revised Selected Papers. ed. / Wil M.P. van der Aalst; Vladimir Batagelj; Dmitry I. Ignatov; Valentina Kuskova; Sergei O. Kuznetsov; Irina A. Lomazova; Michael Khachay; Andrey Kutuzov; Natalia Loukachevitch; Amedeo Napoli; Panos M. Pardalos; Marcello Pelillo; Andrey V. Savchenko; Elena Tutubalina. Springer Nature, 2019. p. 166-178 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11832 LNCS).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review
Harvard
Malykh, V
, Alekseev, A, Tutubalina, E, Shenbin, I
& Nikolenko, S 2019,
Wear the right head: Comparing strategies for encoding sentences for aspect extraction. in WMP van der Aalst, V Batagelj, DI Ignatov, V Kuskova, SO Kuznetsov, IA Lomazova, M Khachay, A Kutuzov, N Loukachevitch, A Napoli, PM Pardalos, M Pelillo, AV Savchenko & E Tutubalina (eds),
Analysis of Images, Social Networks and Texts - 8th International Conference, AIST 2019, Revised Selected Papers. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11832 LNCS, Springer Nature, pp. 166-178, 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019, Kazan, Russian Federation,
17/07/19.
https://doi.org/10.1007/978-3-030-37334-4_15APA
Malykh, V.
, Alekseev, A., Tutubalina, E., Shenbin, I.
, & Nikolenko, S. (2019).
Wear the right head: Comparing strategies for encoding sentences for aspect extraction. In W. M. P. van der Aalst, V. Batagelj, D. I. Ignatov, V. Kuskova, S. O. Kuznetsov, I. A. Lomazova, M. Khachay, A. Kutuzov, N. Loukachevitch, A. Napoli, P. M. Pardalos, M. Pelillo, A. V. Savchenko, & E. Tutubalina (Eds.),
Analysis of Images, Social Networks and Texts - 8th International Conference, AIST 2019, Revised Selected Papers (pp. 166-178). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11832 LNCS). Springer Nature.
https://doi.org/10.1007/978-3-030-37334-4_15Vancouver
Malykh V
, Alekseev A, Tutubalina E, Shenbin I
, Nikolenko S.
Wear the right head: Comparing strategies for encoding sentences for aspect extraction. In van der Aalst WMP, Batagelj V, Ignatov DI, Kuskova V, Kuznetsov SO, Lomazova IA, Khachay M, Kutuzov A, Loukachevitch N, Napoli A, Pardalos PM, Pelillo M, Savchenko AV, Tutubalina E, editors, Analysis of Images, Social Networks and Texts - 8th International Conference, AIST 2019, Revised Selected Papers. Springer Nature. 2019. p. 166-178. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
https://doi.org/10.1007/978-3-030-37334-4_15Author
Malykh, Valentin
; Alekseev, Anton ; Tutubalina, Elena ; Shenbin, Ilya
; Nikolenko, Sergey. /
Wear the right head : Comparing strategies for encoding sentences for aspect extraction. Analysis of Images, Social Networks and Texts - 8th International Conference, AIST 2019, Revised Selected Papers. editor / Wil M.P. van der Aalst ; Vladimir Batagelj ; Dmitry I. Ignatov ; Valentina Kuskova ; Sergei O. Kuznetsov ; Irina A. Lomazova ; Michael Khachay ; Andrey Kutuzov ; Natalia Loukachevitch ; Amedeo Napoli ; Panos M. Pardalos ; Marcello Pelillo ; Andrey V. Savchenko ; Elena Tutubalina. Springer Nature, 2019. pp. 166-178 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
BibTeX
@inproceedings{cf1e1c8380fa4f90b40aa39c4a8016c6,
title = "Wear the right head: Comparing strategies for encoding sentences for aspect extraction",
abstract = "In this work we investigate the impact of encoding mechanisms used in neural aspect extraction models on the quality of the resulting aspects. We concentrate on the neural attention-based aspect extraction (ABAE) model and evaluate five different types of encoding mechanisms: simple averaging, self-attention with and without positional encoding, recurrent, and convolutional architectures. Our experiments on four datasets of user reviews demonstrate that, in the family of ABAE-like architectures, all models with different encoding mechanisms show the similar results in terms of standard coherence metrics for English and Russian data. Our qualitative study shows that all models yield interpretable aspects as well, and the difference in quality is often very minor.",
keywords = "Aspect extraction, Aspect-based sentiment analysis, Deep learning, Neural network, Self-attention, User reviews",
author = "Valentin Malykh and Anton Alekseev and Elena Tutubalina and Ilya Shenbin and Sergey Nikolenko",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2019.; 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019 ; Conference date: 17-07-2019 Through 19-07-2019",
year = "2019",
doi = "10.1007/978-3-030-37334-4_15",
language = "English",
isbn = "9783030373337",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature",
pages = "166--178",
editor = "{van der Aalst}, {Wil M.P.} and Vladimir Batagelj and Ignatov, {Dmitry I.} and Valentina Kuskova and Kuznetsov, {Sergei O.} and Lomazova, {Irina A.} and Michael Khachay and Andrey Kutuzov and Natalia Loukachevitch and Amedeo Napoli and Pardalos, {Panos M.} and Marcello Pelillo and Savchenko, {Andrey V.} and Elena Tutubalina",
booktitle = "Analysis of Images, Social Networks and Texts - 8th International Conference, AIST 2019, Revised Selected Papers",
address = "Germany",
}
RIS
TY - GEN
T1 - Wear the right head
T2 - 8th International Conference on Analysis of Images, Social Networks and Texts, AIST 2019
AU - Malykh, Valentin
AU - Alekseev, Anton
AU - Tutubalina, Elena
AU - Shenbin, Ilya
AU - Nikolenko, Sergey
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - In this work we investigate the impact of encoding mechanisms used in neural aspect extraction models on the quality of the resulting aspects. We concentrate on the neural attention-based aspect extraction (ABAE) model and evaluate five different types of encoding mechanisms: simple averaging, self-attention with and without positional encoding, recurrent, and convolutional architectures. Our experiments on four datasets of user reviews demonstrate that, in the family of ABAE-like architectures, all models with different encoding mechanisms show the similar results in terms of standard coherence metrics for English and Russian data. Our qualitative study shows that all models yield interpretable aspects as well, and the difference in quality is often very minor.
AB - In this work we investigate the impact of encoding mechanisms used in neural aspect extraction models on the quality of the resulting aspects. We concentrate on the neural attention-based aspect extraction (ABAE) model and evaluate five different types of encoding mechanisms: simple averaging, self-attention with and without positional encoding, recurrent, and convolutional architectures. Our experiments on four datasets of user reviews demonstrate that, in the family of ABAE-like architectures, all models with different encoding mechanisms show the similar results in terms of standard coherence metrics for English and Russian data. Our qualitative study shows that all models yield interpretable aspects as well, and the difference in quality is often very minor.
KW - Aspect extraction
KW - Aspect-based sentiment analysis
KW - Deep learning
KW - Neural network
KW - Self-attention
KW - User reviews
UR - http://www.scopus.com/inward/record.url?scp=85077503890&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-37334-4_15
DO - 10.1007/978-3-030-37334-4_15
M3 - Conference contribution
AN - SCOPUS:85077503890
SN - 9783030373337
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 166
EP - 178
BT - Analysis of Images, Social Networks and Texts - 8th International Conference, AIST 2019, Revised Selected Papers
A2 - van der Aalst, Wil M.P.
A2 - Batagelj, Vladimir
A2 - Ignatov, Dmitry I.
A2 - Kuskova, Valentina
A2 - Kuznetsov, Sergei O.
A2 - Lomazova, Irina A.
A2 - Khachay, Michael
A2 - Kutuzov, Andrey
A2 - Loukachevitch, Natalia
A2 - Napoli, Amedeo
A2 - Pardalos, Panos M.
A2 - Pelillo, Marcello
A2 - Savchenko, Andrey V.
A2 - Tutubalina, Elena
PB - Springer Nature
Y2 - 17 July 2019 through 19 July 2019
ER -
