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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. - : Elsevier, 2019 BASE Show details 19 Persian Named Entity Recognition Dashtipour, Kia; Gogate, Mandar; Adeel, Ahsan; Algarafi, Abdulrahman; Howard, Newton; Hussain, Amir. - : Institute of Electrical and Electronics Engineers Inc, 2017. : Piscataway, NJ, USA, 2017 Abstract: Named Entity Recognition (NER) is an important natural language processing (NLP) tool for information extraction and retrieval from unstructured texts such as newspapers, blogs and emails. NER involves processing unstructured text for classification of words or expressions into relevant categories. In literature, NER has been developed for various languages but limited work has been conducted to develop NER for Persian text. This is due to limited resources (such as corpus, lexicons etc.) and tools for Persian named entities. In this paper, a novel scalable system for Persian Named Entity Recognition (PNER) is presented. The proposed PNER can recognize and extract three most important named entities in Persian script: the person name, location and date. The proposed PNER has been developed by combining a grammatical rule-based approach with machine learning. The proposed framework has integrated dictionaries of Persian named entities, Persian grammar rules and a Support Vector Machine (SVM). The performance evaluation of PNER in terms of precision, recall and f-measure has achieved comparable results with the state-of-the-art NER frameworks in other languages. Keyword: Dictionaries; Grammar; Handheld computers; Natural language processing; Support vector machines; Text recognition; Tools URL: http://hdl.handle.net/1893/26709 http://dspace.stir.ac.uk/bitstream/1893/26709/1/08109733.pdf https://doi.org/10.1109/ICCI-CC.2017.8109733 BASE Hide details

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