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Iti Chaturvedi

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2020 – today

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2024
[j17]
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Iti Chaturvedi, Ranjan Satapathy, Curtis Lynch, Erik Cambria:
Predicting word vectors for microtext. Expert Syst. J. Knowl. Eng. 41(8) (2024)
2023
[j16]
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Frank Xing, Björn W. Schuller, Iti Chaturvedi, Erik Cambria, Amir Hussain:
Guest Editorial Neurosymbolic AI for Sentiment Analysis. IEEE Trans. Affect. Comput. 14(3): 1711-1715 (2023)
2022
[j15]
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Iti Chaturvedi, Qian Chen, Erik Cambria, Desmond McConnell:
Landmark calibration for facial expressions and fish classification. Signal Image Video Process. 16(2): 377-384 (2022)
[j14]
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Iti Chaturvedi, Qian Chen, Roy E. Welsch, Kishor Thapa, Erik Cambria:
Gaussian correction for adversarial learning of boundaries. Signal Process. Image Commun. 109: 116841 (2022)
2021
[j13]
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Iti Chaturvedi, Chit Lin Su, Roy E. Welsch:
Fuzzy Aggregated Topology Evolution for Cognitive Multi-tasks. Cogn. Comput. 13(1): 96-107 (2021)
[j12]
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Iti Chaturvedi, Kishor Thapa, Sandro Cavallari, Erik Cambria, Roy E. Welsch:
Predicting video engagement using heterogeneous DeepWalk. Neurocomputing 465: 228-237 (2021)
[j11]
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Qian Chen, Iti Chaturvedi, Shaoxiong Ji, Erik Cambria:
Sequential fusion of facial appearance and dynamics for depression recognition. Pattern Recognit. Lett. 150: 115-121 (2021)
2020
[j10]
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Ana Valdivia, Eugenio Martínez-Cámara, Iti Chaturvedi, María Victoria Luzón, Erik Cambria, Yew-Soon Ong, Francisco Herrera:
What do people think about this monument? Understanding negative reviews via deep learning, clustering and descriptive rules. J. Ambient Intell. Humaniz. Comput. 11(1): 39-52 (2020)
[c20]
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Iti Chaturvedi, Erik Cambria, Sandro Cavallari, Roy E. Welsch:
Genetic Programming for Domain Adaptation in Product Reviews. CEC 2020: 1-8
[c19]
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Iti Chaturvedi, Edoardo Ragusa, Paolo Gastaldo, Erik Cambria:
COAL: Convolutional Online Adaptation Learning for Opinion Mining. ICDM (Workshops) 2020: 15-22
[c18]
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Iti Chaturvedi, Jin Xiang:
Constrained Manifold Learning for Videos. IJCNN 2020: 1-8

2010 – 2019

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2019
[j9]
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Ana Valdivia, Emiliya Hrabova, Iti Chaturvedi, María Victoria Luzón, Luigi Troiano, Erik Cambria, Francisco Herrera:
Inconsistencies on TripAdvisor reviews: A unified index between users and Sentiment Analysis Methods. Neurocomputing 353: 3-16 (2019)
[j8]
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Iti Chaturvedi, Ranjan Satapathy, Sandro Cavallari, Erik Cambria:
Fuzzy commonsense reasoning for multimodal sentiment analysis. Pattern Recognit. Lett. 125: 264-270 (2019)
2018
[j7]
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Iti Chaturvedi, Erik Cambria, Roy E. Welsch, Francisco Herrera:
Distinguishing between facts and opinions for sentiment analysis: Survey and challenges. Inf. Fusion 44: 65-77 (2018)
[j6]
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Iti Chaturvedi, Edoardo Ragusa, Paolo Gastaldo, Rodolfo Zunino, Erik Cambria:
Bayesian network based extreme learning machine for subjectivity detection. J. Frankl. Inst. 355(4): 1780-1797 (2018)
[c17]
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  - conf/aaai/YoungCCZBH18
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Tom Young, Erik Cambria, Iti Chaturvedi, Hao Zhou, Subham Biswas, Minlie Huang:
Augmenting End-to-End Dialogue Systems With Commonsense Knowledge. AAAI 2018: 4970-4977
[c16]
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Qian Chen, Edoardo Ragusa, Iti Chaturvedi, Erik Cambria, Rodolfo Zunino:
Text-Image Sentiment Analysis. CICLing (2) 2018: 169-180
[c15]
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Qian Chen, Iti Chaturvedi, Soujanya Poria, Erik Cambria, Lorenzo Malandri:
Learning Visual Concepts in Images Using Temporal Convolutional Networks. SSCI 2018: 1280-1284
[r1]
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Iti Chaturvedi, Soujanya Poria, Erik Cambria:
Sentiment Analysis, Basic Tasks of. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018
2017
[j5]
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Ranjan Satapathy, Iti Chaturvedi, Erik Cambria, Shirley S. Ho, Jin-Cheon Na:
Subjectivity Detection in Nuclear Energy Tweets. Computación y Sistemas 21(4) (2017)
[c14]
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Iti Chaturvedi, Erik Cambria, Sandro Cavallari, Vincent Wenchen Zheng:
Learning Word Vectors in Deep Walk using Convolution. FLAIRS 2017: 323-328
[c13]
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Aparup Khatua, Erik Cambria, Apalak Khatua, Iti Chaturvedi:
Let's Chat about Brexit! A Politically-Sensitive Dialog System Based on Twitter Data. ICDM Workshops 2017: 393-398
[c12]
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Ranjan Satapathy, Claudia Guerreiro, Iti Chaturvedi, Erik Cambria:
Phonetic-Based Microtext Normalization for Twitter Sentiment Analysis. ICDM Workshops 2017: 407-413
[i1]
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  - journals/corr/abs-1710-06536
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Iti Chaturvedi, Soujanya Poria, Erik Cambria:
Basic tasks of sentiment analysis. CoRR abs/1710.06536 (2017)
2016
[j4]
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Iti Chaturvedi, Yew-Soon Ong, Ivor W. Tsang, Roy E. Welsch, Erik Cambria:
Learning word dependencies in text by means of a deep recurrent belief network. Knowl. Based Syst. 108: 144-154 (2016)
[c11]
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Soujanya Poria, Iti Chaturvedi, Erik Cambria, Amir Hussain:
Convolutional MKL Based Multimodal Emotion Recognition and Sentiment Analysis. ICDM 2016: 439-448
[c10]
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Iti Chaturvedi, Erik Cambria, Soujanya Poria, Rajiv Bajpai:
Bayesian Deep Convolution Belief Networks for Subjectivity Detection. ICDM Workshops 2016: 916-923
[c9]
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Soujanya Poria, Iti Chaturvedi, Erik Cambria, Federica Bisio:
Sentic LDA: Improving on LDA with semantic similarity for aspect-based sentiment analysis. IJCNN 2016: 4465-4473
[c8]
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Iti Chaturvedi, Erik Cambria, David Vilares:
Lyapunov filtering of objectivity for Spanish Sentiment Model. IJCNN 2016: 4474-4481
2015
[j3]
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  - journals/sigpro/ChaturvediOA15
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Iti Chaturvedi, Yew-Soon Ong, Rajesh Vellore Arumugam:
Deep transfer learning for classification of time-delayed Gaussian networks. Signal Process. 110: 250-262 (2015)
[c7]
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  - conf/cicling/CambriaPBBC15
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Erik Cambria, Soujanya Poria, Federica Bisio, Rajiv Bajpai, Iti Chaturvedi:
The CLSA Model: A Novel Framework for Concept-Level Sentiment Analysis. CICLing (2) 2015: 3-22
[c6]
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  - conf/icdm/MondalCDBB15
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Anupam Mondal, Iti Chaturvedi, Dipankar Das, Rajiv Bajpai, Sivaji Bandyopadhyay:
Lexical Resource for Medical Events: A Polarity Based Approach. ICDM Workshops 2015: 1302-1309
2013
[b1]
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Iti Chaturvedi:
Bayesian framework for building gene regulatory networks including delays. Nanyang Technological University, Singapore, 2013
2011
[c5]
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  - conf/prib/ZhengCR11
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Jie Zheng, Iti Chaturvedi, Jagath C. Rajapakse:
Integration of Epigenetic Data in Bayesian Network Modeling of Gene Regulatory Network. PRIB 2011: 87-96
[c4]
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Jagath C. Rajapakse, Iti Chaturvedi:
Stability of Inferring Gene Regulatory Structure with Dynamic Bayesian Networks. PRIB 2011: 237-246
2010
[j2]
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Iti Chaturvedi, Jagath C. Rajapakse:
Building gene networks with time-delayed regulations. Pattern Recognit. Lett. 31(14): 2133-2137 (2010)
[c3]
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Jagath C. Rajapakse, Iti Chaturvedi:
Gene regulatory networks with variable-order dynamic Bayesian networks. IJCNN 2010: 1-5

2000 – 2009

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2008
[c2]
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Iti Chaturvedi, Jagath C. Rajapakse:
Fusion of Gene Regulatory and Protein Interaction Networks Using Skip-Chain Models. PRIB 2008: 214-224
2007
[c1]
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Iti Chaturvedi, Meena K. Sakharkar, Jagath C. Rajapakse:
Validation of Gene Regulatory Networks from Protein-Protein Interaction Data: Application to Cell-Cycle Regulation. PRIB 2007: 300-310
2005
[j1]
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Kishore R. Sakharkar, Iti Chaturvedi, Vincent T. K. Chow, Chee Keong Kwoh, Pandjassarame Kangueane, Meena Kishore Sakharkar:
u-Genome: A Database on Genome Design in Unicellular Genomes. Silico Biol. 5(5-6): 611-615 (2005)

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