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Browsing Business, Commerce, Economics & Computer Sciences by Author "Bhattacharyya, P."

Browsing Business, Commerce, Economics & Computer Sciences by Author "Bhattacharyya, P."

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  • IITP at EmoInt-2017: Measuring intensity of emotions using sentence embeddings and optimized features 
    Akhtar, Md.S.; Sawant, P.; Ekbal, A.; Pawar, J.D.; Bhattacharyya, P. (Proceedings of the 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, Copenhagen, Denmark. 7–11 Sep 2017. 2017; 212-218.)
    This paper describes the system that we submitted as part of our participation in the shared task on Emotion Intensity (EmoInt-2017). We propose a Long short term memory (LSTM) based architecture cascaded with Support ...
  • Improving word embedding coverage in less-resourced languages through multi-linguality and cross-linguality: A case study with aspect-based sentiment analysis 
    Akhtar, Md.S.; Sawant, P.; Sen, S.; Ekbal, A.; Bhattacharyya, P. (ACM Transactions on Asian and Low-Resource Language Information Processing. 18(2); 2019; ArticleID_3273931.)
    In the era of deep learning-based systems, efficient input representation is one of the primary requisites in solving various problems related to Natural Language Processing (NLP), data mining, text mining, and the like. ...
  • IndoWordNet Conversion to Web Ontology Language (OWL) 
    Nagvenkar, A.; Pawar, J.D.; Bhattacharyya, P. (Proc. 8. Global WordNet Conference. Ed. by: Mititelu, V.B.; Forascu, C.; Fellbaum, C. Vossen, P. Bucharest, Romania, 27-30 Jan 2016. 2016; 255-258.)
    WordNet plays a significant role in Linked Open Data (LOD) cloud. It has numerous application ranging from ontology annotation to ontology mapping. IndoWord- Net is a linkedWordNet connecting 18 Indian language WordNets ...
  • Let sense bags do talking: Cross lingual word semantic similarity for English and Hindi 
    Nagvenkar, A.; Pawar, J.D.; Bhattacharyya, P. (Proc. of the 12. Int. Conf. on Natural Language Processing (ICON-2015), Ed. by: Dipti Misra Sharma, Rajeev Sangal, Elizabeth Sherly. IIITM-Kerala, Trivandrum. 2016; 5pp.)
    Cross Lingual Word Semantic (CLWS) similarity is defined as a task to find the semantic similarity between two words across languages. Semantic similarity has been very popular in computing the similarity between two words ...
  • Logistic regression for automatic lexical level morphological paradigm selection for Konkani nouns 
    Desai, S.; Pawar, J.D.; Bhattacharyya, P. (Proc. of the 12. Int. Conf. on Natural Language Processing (ICON-2015), Ed. by: Dipti Misra Sharma, Rajeev Sangal, Elizabeth Sherly. IIITM-Kerala, Trivandrum. 2016; vp.)
    Automatic selection of morphological paradigm for a noun lemma is necessary to automate the task of building morphological analyzer for nouns with minimal human interventions. Morphological paradigms can be of two types ...
  • PanchBhoota: Hierarchical phrase based machine translation systems for five Indian languages 
    Prabhugaonkar, N.R.; Pawar, J.D.; Nagvenkar, A.S.; Bhattacharyya, P.; Kanojia, D.; Shrivastava, M. (11. Int. Conf. Natural Language Processing (ICON-2014), Goa Univ., Goa. 18-21 Dec 2014. 6pp.)
    We present our work on developing fifteen Hierarchical Phrase Based Statistical Machine Translation (HPBSMT) systems for five Indian language pairs namely Bengali-Hindi, English-Hindi, Marathi-Hindi, Tamil-Hindi, and ...
  • Solving data sparsity for aspect based sentiment analysis using cross-linguality and multi-linguality 
    Akhtar, Md.S.; Sawant, P.; Sen, S.; Ekbal, A.; Bhattacharyya, P. (16. Annual Conf. North American Chapter of the Association for Computational Linguistics: Human Language Technologies, New Orleans, Louisiana, 1-6 Jun 2018.. 1; 2018; 572-582.)
    Efficient word representations play an important role in solving various problems related to Natural Language Processing (NLP), data mining, text mining etc. The issue of data sparsity poses a great challenge in creating ...
  • The WordNet in Indian Languages 
    Dash, N.S.; Bhattacharyya, P.; Pawar, J.D. (Springer. 2017; 264pp.)

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