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Author, Editor

Author(s):

Qu, Lizhen
Gemulla, Rainer
Weikum, Gerhard

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Editor(s):





BibTeX cite key*:

Qu2012a

Title, Booktitle

Title*:

A Weakly Supervised Model for Sentence-Level Semantic Orientation Analysis with Multiple Experts


MEM_EMNLP_camera_ready.pdf (308.92 KB)

Booktitle*:

2012 Joint Conference on Empirical Methods in Natural Language Processing
and Computational Natural Language Learning (EMNLP-CoNLL 2012)

Event, URLs

URL of the conference:

http://emnlp-conll2012.unige.ch/

URL for downloading the paper:

http://aclweb.org/anthology-new/D/D12/D12-1014.pdf

Event Address*:

Jeju Island, Korea

Language:

English

Event Date*
(no longer used):


Organization:


Event Start Date:

12 July 2012

Event End Date:

14 July 2012

Publisher

Name*:

ACL

URL:

http://www.aclweb.org/

Address*:

Stroudsburg, USA

Type:


Vol, No, Year, pp.

Series:


Volume:


Number:


Month:

July

Pages:

149-159

Year*:

2012

VG Wort Pages:


ISBN/ISSN:

978-1-937284-43-5

Sequence Number:


DOI:




Note, Abstract, ©


(LaTeX) Abstract:

We propose the weakly supervised \emph{Multi-Experts Model} (MEM) for analyzing the semantic orientation of opinions expressed in natural language reviews. In contrast to most prior work, MEM predicts both opinion polarity and opinion strength at the level of individual sentences; such fine-grained analysis helps to understand better why users like or dislike the entity under review. A key challenge in this setting is that it is hard to obtain sentence-level training data for both polarity and strength. For this reason, MEM is weakly supervised: It starts with potentially noisy indicators obtained from coarse-grained training data (i.e., document-level ratings), a small set of diverse base predictors, and, if available, small amounts of fine-grained training data. We integrate these noisy indicators into a unified probabilistic framework using ideas from ensemble learning and graph-based semi-supervised learning. Our experiments indicate that MEM outperforms state-of-the-art methods by a significant margin.



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Access Level:

Public

Correlation

MPG Unit:

Max-Planck-Institut für Informatik



MPG Subunit:

Databases and Information Systems Group

Appearance:

MPII WWW Server, MPII FTP Server, MPG publications list, university publications list, working group publication list, Fachbeirat, VG Wort



BibTeX Entry:

@INPROCEEDINGS{Qu2012a,
AUTHOR = {Qu, Lizhen and Gemulla, Rainer and Weikum, Gerhard},
TITLE = {A Weakly Supervised Model for Sentence-Level Semantic Orientation Analysis with Multiple Experts},
BOOKTITLE = {2012 Joint Conference on Empirical Methods in Natural Language Processing
and Computational Natural Language Learning (EMNLP-CoNLL 2012)},
PUBLISHER = {ACL},
YEAR = {2012},
PAGES = {149--159},
ADDRESS = {Jeju Island, Korea},
MONTH = {July},
ISBN = {978-1-937284-43-5},
}


Entry last modified by Anja Becker, 03/04/2013
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Created
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Anja Becker
Anja Becker
Anja Becker
Lizhen Qu
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01.03.2013 09:15:48
28.02.2013 15:02:29
02/04/2013 09:58:50 PM
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