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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 19 of 19 1 Persian Sentence-level Sentiment Polarity Classification Dashtipour, Kia; Gogate, Mandar; Gelbukh, Alexander... In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03258138 ; ICOTEN, Jun 2021, Glasgow, United Kingdom (2021) BASE Show details 2 Persian Sentence-level Sentiment Polarity Classification Dashtipour, Kia; Gogate, Mandar; Gelbukh, Alexander... In: ICOTEN ; https://hal.archives-ouvertes.fr/hal-03241928 ; ICOTEN, May 2021, Glasgow, France (2021) BASE Show details 3 Extending persian sentiment lexicon with idiomatic expressions for sentiment analysis Dashtipour, Kia; Gogate, Mandar; Gelbukh, Alexander. - : Springer, 2021 BASE Show details 4 Novel Deep Convolutional Neural Network-Based Contextual Recognition of Arabic Handwritten Scripts Ahmed, Rami; Gogate, Mandar; Tahir, Ahsen. - : MDPI, 2021 BASE Show details 5 A novel context-aware multimodal framework for persian sentiment analysis Dashtipour, Kia; Gogate, Mandar; Cambria, Erik. - : Elsevier, 2021 BASE Show details 6 A semi-supervised approach for sentiment analysis of arab (ic+ izi) messages: Application to the algerian dialect Adeel, Ahsan; Guellil, Imane; Gogate, Mandar. - : Springer, 2021 BASE Show details 7 A Semi-supervised Approach for Sentiment Analysis of Arab(ic+izi) Messages: Application to the Algerian Dialect Guellil, Imane; Adeel, Ahsan; Azouaou, Faical. - 2021 BASE Show details 8 A Novel Context-Aware Multimodal Framework for Persian Sentiment Analysis Dashtipour, Kia; Gogate, Mandar; Cambria, Erik. - : Elsevier BV, 2021 BASE Show details 9 Novel Deep Convolutional Neural Network-Based Contextual Recognition of Arabic Handwritten Scripts Ahmed, Rami; Gogate, Mandar; Tahir, Ahsen. - : MDPI, 2021 BASE Show details 10 Persian Sentence-level Sentiment Polarity Classification Dashtipour, Kia; Gogate, Mandar; Gelbukh, Alexander. - : IEEE, 2021. : Piscataway, NJ, USA, 2021 BASE Show details 11 CochleaNet: A robust language-independent audio-visual model for real-time speech enhancement Gogate, Mandar; Dashtipour, Kia; Adeel, Ahsan. - : Elsevier, 2020 BASE Show details 12 Offline Arabic Handwriting Recognition Using Deep Machine Learning: A Review of Recent Advances Ahmed, Rami; Dashtipour, Kia; Gogate, Mandar. - : Springer, 2020 BASE Show details 13 Deep Neural Network Driven Binaural Audio Visual Speech Separation Gogate, Mandar; Dashtipour, Kia; Bell, Peter. - : Institute of Electrical and Electronics Engineers, 2020 BASE Show details 14 Visual Speech In Real Noisy Environments (VISION): A Novel Benchmark Dataset and Deep Learning-Based Baseline System Gogate, Mandar; Dashtipour, Kia; Hussain, Amir. - 2020 BASE Show details 15 A hybrid Persian sentiment analysis framework: Integrating dependency grammar based rules and deep neural networks Dashtipour, Kia; Gogate, Mandar; Li, Jingpeng. - : Elsevier, 2019 BASE Show details 16 A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks ... Dashtipour, Kia; Gogate, Mandar; Li, Jingpeng. - : arXiv, 2019 BASE Show details 17 Lip-reading driven deep learning approach for speech enhancement Adeel, Ahsan; Gogate, Mandar; Hussain, Amir... In: abs/1808.00046 ; 1 ; 10 (2019) BASE Show details 18 A Hybrid Persian Sentiment Analysis Framework: Integrating Dependency Grammar Based Rules and Deep Neural Networks Dashtipour, Kia; Gogate, Mandar; Li, Jingpeng; Jiang, Fengling; Kong, Bin; Hussain, Amir. - : Elsevier, 2019 Abstract: Social media hold valuable, vast and unstructured information on public opinion that can be utilized to improve products and services. The automatic analysis of such data, however, requires a deep understanding of natural language. Current sentiment analysis approaches are mainly based on word co-occurrence frequencies, which are inadequate in most practical cases. In this work, we propose a novel hybrid framework for concept-level sentiment analysis in Persian language, that integrates linguistic rules and deep learning to optimize polarity detection. When a pattern is triggered, the framework allows sentiments to flow from words to concepts based on symbolic dependency relations. When no pattern is triggered, the framework switches to its subsymbolic counterpart and leverages deep neural networks (DNN) to perform the classification. The proposed framework outperforms state-of-the-art approaches (including support vector machine, and logistic regression) and DNN classifiers (long short-term memory, and Convolutional Neural Networks) with a margin of 10–15% and 3–4% respectively, using benchmark Persian product and hotel reviews corpora. ; Output Status: Forthcoming/Available Online Keyword: Deep Learning; Dependency-based Rules; Low-Resource Natural Language Processing; Persian Sentiment Analysis URL: https://doi.org/10.1016/j.neucom.2019.10.009 http://hdl.handle.net/1893/30451 http://dspace.stir.ac.uk/bitstream/1893/30451/1/1-s2.0-S0925231219313815-main.pdf BASE Hide details 19 Persian Named Entity Recognition Dashtipour, Kia; Gogate, Mandar; Adeel, Ahsan. - : Institute of Electrical and Electronics Engineers Inc, 2017. : Piscataway, NJ, USA, 2017 BASE Show details

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