Alexander Gelbukh
Titolo
Citata da
Citata da
Anno
Aspect extraction for opinion mining with a deep convolutional neural network
S Poria, E Cambria, A Gelbukh
Knowledge-Based Systems 108, 42-49, 2016
5262016
Deep convolutional neural network textual features and multiple kernel learning for utterance-level multimodal sentiment analysis
S Poria, E Cambria, A Gelbukh
Proceedings of the 2015 conference on empirical methods in natural language …, 2015
3162015
Soft similarity and soft cosine measure: Similarity of features in vector space model
G Sidorov, A Gelbukh, H Gómez-Adorno, D Pinto
Computación y Sistemas 18 (3), 491-504, 2014
2932014
Syntactic n-grams as machine learning features for natural language processing
G Sidorov, F Velasquez, E Stamatatos, A Gelbukh, ...
Expert Systems with Applications 41 (3), 853-860, 2014
2642014
Deep learning-based document modeling for personality detection from text
N Majumder, S Poria, A Gelbukh, E Cambria
IEEE Intelligent Systems 32 (2), 74-79, 2017
2622017
A Rule-Based Approach to Aspect Extraction from Product Reviews
S Poria, E Cambria, LW Ku, C Gui, A Gelbukh
COLING 2014 Workshop on Natural Language Processing for Social Media …, 2014
2272014
Enhanced SenticNet with Affective Labels for Concept-Based Opinion Mining
S Poria, A Gelbukh, A Hussain, N Howard, D Das, S Bandyopadhyay
IEEE Intelligent Systems, 2013
2042013
Sentiment analysis is a big suitcase
E Cambria, S Poria, A Gelbukh, M Thelwall
IEEE Intelligent Systems 32 (6), 74-80, 2017
1852017
Empirical study of machine learning based approach for opinion mining in tweets
G Sidorov, S Miranda-Jiménez, F Viveros-Jiménez, A Gelbukh, ...
Mexican international conference on Artificial intelligence, 1-14, 2012
1682012
EmoSenticSpace: A novel framework for affective common-sense reasoning
S Poria, A Gelbukh, E Cambria, A Hussain, GB Huang
Knowledge-Based Systems 69, 108-123, 2014
1482014
Zipf and Heaps laws’ coefficients depend on language
A Gelbukh, G Sidorov
International Conference on Intelligent Text Processing and Computational …, 2001
1462001
Sentiment data flow analysis by means of dynamic linguistic patterns
S Poria, E Cambria, A Gelbukh, F Bisio, A Hussain
IEEE Computational Intelligence Magazine 10 (4), 26-36, 2015
1302015
Multilingual sentiment analysis: state of the art and independent comparison of techniques
K Dashtipour, S Poria, A Hussain, E Cambria, AYA Hawalah, A Gelbukh, ...
Cognitive computation 8 (4), 757-771, 2016
1252016
Concept-Level Sentiment Analysis with Dependency-Based Semantic Parsing: A Novel Approach
B Agarwal, S Poria, N Mittal, A Gelbukh, A Hussain
Cognitive Computation 7 (4), 487–499, 2015
1252015
Computational Linguistics: Models, Resources, Applications
IA Bolshakov, A Gelbukh
1242004
Syntactic dependency-based n-grams as classification features
G Sidorov, F Velasquez, E Stamatatos, A Gelbukh, ...
Mexican International Conference on Artificial Intelligence, 1-11, 2012
1162012
Pre-conceptual schema: A conceptual-graph-like knowledge representation for requirements elicitation
CMZ Jaramillo, A Gelbukh, FA Isaza
Mexican International Conference on Artificial Intelligence, 27-37, 2006
1112006
Information retrieval with Conceptual Graph Matching
M Montes y Gómez, A López, A Gelbukh
Lecture Notes in Computer Science 1873, 312-321, 2000
982000
Merging SenticNet and WordNet-Affect emotion lists for sentiment analysis
S Poria, A Gelbukh, E Cambria, P Yang, A Hussain, T Durrani
2012 IEEE 11th International Conference on Signal Processing 2, 1251-1255, 2012
952012
Dialoguernn: An attentive rnn for emotion detection in conversations
N Majumder, S Poria, D Hazarika, R Mihalcea, A Gelbukh, E Cambria
Proceedings of the AAAI Conference on Artificial Intelligence 33, 6818-6825, 2019
912019
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