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2020 – today
- 2025
[i16]Rudrajit Dawn, Madhusudan Ghosh, Partha Basuchowdhuri, Sudip Kumar Naskar:
Unified Graph Networks (UGN): A Deep Neural Framework for Solving Graph Problems. CoRR abs/2502.07500 (2025)- 2024
- [c104]Sohom Ghosh, Arnab Maji, Aswartha Narayana, Sudip Kumar Naskar:
IndicFinNLP: Financial Natural Language Processing for Indian Languages. LREC/COLING 2024: 9010-9018 - [c103]Payel Santra
, Madhusudan Ghosh, Debasis Ganguly, Partha Basuchowdhuri, Sudip Kumar Naskar:
"The Absence of Evidence is Not the Evidence of Absence": Fact Verification via Information Retrieval-Based In-Context Learning. DaWaK 2024: 381-387 - [c102]Sohom Ghosh, Chung-Chi Chen, Sudip Kumar Naskar:
Generator-Guided Crowd Reaction Assessment. WWW (Companion Volume) 2024: 597-600 - [i15]Atanu Mandal, Gargi Roy, Amit Barman, Indranil Dutta, Sudip Kumar Naskar:
Attentive Fusion: A Transformer-based Approach to Multimodal Hate Speech Detection. CoRR abs/2401.10653 (2024) - [i14]Amit Barman, Devangan Roy, Debapriya Paul, Indranil Dutta, Shouvik Kumar Guha, Samir Karmakar, Sudip Kumar Naskar:
Convolutional Neural Networks can achieve binary bail judgement classification. CoRR abs/2401.14135 (2024) - [i13]Sohom Ghosh, Chung-Chi Chen, Sudip Kumar Naskar:
Generator-Guided Crowd Reaction Assessment. CoRR abs/2403.09702 (2024) - [i12]Arijit Das, Tanmoy Nandi, Prasanta Saha, Suman Das, Saronyo Mukherjee, Sudip Kumar Naskar, Diganta Saha:
Effect of Leaders Voice on Financial Market: An Empirical Deep Learning Expedition on NASDAQ, NSE, and Beyond. CoRR abs/2403.12161 (2024) - [i11]Madhusudan Ghosh, Shrimon Mukherjee, Asmit Ganguly, Partha Basuchowdhuri, Sudip Kumar Naskar, Debasis Ganguly:
AlpaPICO: Extraction of PICO Frames from Clinical Trial Documents Using LLMs. CoRR abs/2409.09704 (2024) - [i10]Sohom Ghosh, Arnab Maji, N. Harsha Vardhan, Sudip Kumar Naskar:
Experimenting with Multi-modal Information to Predict Success of Indian IPOs. CoRR abs/2412.16174 (2024) - 2023
- [j19]Sohom Ghosh, Ankush Chopra, Sudip Kumar Naskar:
Learning to Rank Hypernyms of Financial Terms Using Semantic Textual Similarity. SN Comput. Sci. 4(5): 610 (2023) - [c101]Madhusudan Ghosh, Debasis Ganguly, Partha Basuchowdhuri, Sudip Kumar Naskar:
Extracting Methodology Components from AI Research Papers: A Data-driven Factored Sequence Labeling Approach. CIKM 2023: 3897-3901 - [c100]Sohom Ghosh, Sudip Kumar Naskar:
FLUEnT: Financial Language Understandability Enhancement Toolkit. COMAD/CODS 2023: 258-262 - [c99]Sohom Ghosh, Sudip Kumar Naskar:
Using Natural Language Processing to Enhance Understandability of Financial Texts. COMAD/CODS 2023: 301-302 - [c98]Sohom Ghosh, Sachin Umrao, Chung-Chi Chen, Sudip Kumar Naskar:
The Mask One At a Time Framework for Detecting the Relationship between Financial Entities. FIRE 2023: 40-43 - [c97]Rima Roy, Sohom Ghosh, Sudip Kumar Naskar:
Financial Argument Analysis in Bengali. FIRE 2023: 88-92 - [c96]Payel Santra, Madhusudan Ghosh, Shrimon Mukherjee, Debasis Ganguly, Partha Basuchowdhuri, Sudip Kumar Naskar:
Unleashing the Power of Large Language Models: A Hands-On Tutorial. FIRE 2023: 149-152 - [c95]Dhairya Suman, Atanu Mandal, Santanu Pal, Sudip Kumar Naskar:
IACS-LRILT: Machine Translation for Low-Resource Indic Languages. WMT 2023: 972-977 - [i9]Sohom Ghosh, Ankush Chopra, Sudip Kumar Naskar:
Learning Semantic Text Similarity to rank Hypernyms of Financial Terms. CoRR abs/2303.13475 (2023) - [i8]Madhusudan Ghosh, Debasis Ganguly, Partha Basuchowdhuri, Sudip Kumar Naskar:
Enhancing AI Research Paper Analysis: Methodology Component Extraction using Factored Transformer-based Sequence Modeling Approach. CoRR abs/2311.03401 (2023) - 2022
- [j18]Sohom Ghosh, Sudip Kumar Naskar:
FiNCAT-2: An enhanced Financial Numeral Claim Analysis Tool. Softw. Impacts 12: 100288 (2022) - [c94]Anubhav Sarkar, Swagata Chakraborty, Sohom Ghosh, Sudip Kumar Naskar:
Evaluating Impact of Social Media Posts by Executives on Stock Prices. FIRE 2022: 74-82 - [c93]Suparnakanti Das, Trishita Dhara, Sirshapan Mitra, Sudip Kumar Naskar:
Understanding the Robustness in Phoneme Production Mechanism in English and Bengali. ICDCN 2022: 273-277 - [c92]Rajarshi Roychoudhury, Subhrajit Dey, Md. Shad Akhtar, Amitava Das, Sudip Kumar Naskar:
A Novel Approach towards Cross Lingual Sentiment Analysis using Transliteration and Character Embedding. ICON 2022: 260-268 - [c91]Sohom Ghosh, Sudip Kumar Naskar:
FiNCAT: Financial Numeral Claim Analysis Tool. WWW (Companion Volume) 2022: 583-585 - [i7]Afia Fairoose Abedin, Amirul Islam Al Mamun, Rownak Jahan Nowrin, Amitabha Chakrabarty, Moin Mostakim, Sudip Kumar Naskar:
A Deep Learning Approach to Integrate Human-Level Understanding in a Chatbot. CoRR abs/2201.02735 (2022) - [i6]Sohom Ghosh, Sudip Kumar Naskar:
FiNCAT: Financial Numeral Claim Analysis Tool. CoRR abs/2202.00631 (2022) - [i5]Anubhav Sarkar, Swagata Chakraborty, Sohom Ghosh, Sudip Kumar Naskar:
Evaluating Impact of Social Media Posts by Executives on Stock Prices. CoRR abs/2211.01287 (2022) - 2021
- [j17]Alok Ranjan Pal, Diganta Saha, Sudip Kumar Naskar, Niladri Sekhar Dash:
In search of a suitable method for disambiguation of word senses in Bengali. Int. J. Speech Technol. 24(2): 439-454 (2021) - [j16]Sourav Mandal, Sudip Kumar Naskar:
Classifying and Solving Arithmetic Math Word Problems - An Intelligent Math Solver. IEEE Trans. Learn. Technol. 14(1): 28-41 (2021) - [c90]Kumar Gourav Das, Braja Gopal Patra, Sudip Kumar Naskar:
Profiling Celebrity Profession from Twitter Data. IALP 2021: 207-212 - [c89]Atanu Mandal, Amir Sinaeepourfard, Sudip Kumar Naskar:
VDA: Deep Learning based Visual Data Analysis in Integrated Edge to Cloud Computing Environment. ICDCN (Adjunct Volume) 2021: 7-12 - [c88]Sourav Mandal, Arif Ahmed Sekh, Sudip Kumar Naskar:
Identification of Relevant Quantities in Arithmetic Word Problems Using Siamese Neural Network. ICMC 2021: 415-426 - [c87]Sandip Dutta, Utso Majumder, Sudip Kumar Naskar:
An Efficient BERT Based Approach to Detect Aggression and Misogyny. ICON 2021: 493-498 - [c86]Sohom Ghosh, Shovon Sengupta, Sudip Kumar Naskar, Sunny Kumar Singh:
FinRead: A Transfer Learning Based Tool to Assess Readability of Definitions of Financial Terms. ICON 2021: 658-659 - [c85]Rajarshi Roychoudhury, Sudip Kumar Naskar:
Fine-tuning BERT to classify COVID19 tweets containing symptoms. SMM4H@NAACL-HLT 2021: 138-140 - [i4]Atanu Mandal, Santanu Pal, Indranil Dutta, Mahidas Bhattacharya, Sudip Kumar Naskar:
Is Attention always needed? A Case Study on Language Identification from Speech. CoRR abs/2110.03427 (2021) - 2020
- [j15]Sourav Mandal, Arif Ahmed Sekh, Sudip Kumar Naskar:
Solving arithmetic word problems: A deep learning based approach. J. Intell. Fuzzy Syst. 39(2): 2521-2531 (2020) - [j14]Shibaprasad Sen, Ankan Bhattacharyya, Mridul Mitra, Kaushik Roy, Sudip Kumar Naskar, Ram Sarkar:
Online Bangla handwritten word recognition using HMM and language model. Neural Comput. Appl. 32(14): 9939-9951 (2020) - [j13]Somnath Banerjee, Monojit Choudhury, Kunal Chakma, Sudip Kumar Naskar, Amitava Das, Sivaji Bandyopadhyay, Paolo Rosso:
MSIR@FIRE: A Comprehensive Report from 2013 to 2016. SN Comput. Sci. 1(1): 55 (2020) - [c84]Anisha Datta, Shukrity Si, Urbi Chakraborty, Sudip Kumar Naskar:
Spyder: Aggression Detection on Multilingual Tweets. TRAC@LREC 2020: 87-92 - [c83]Santanu Pal, Hongfei Xu, Nico Herbig, Sudip Kumar Naskar, Antonio Krüger, Josef van Genabith:
The Transference Architecture for Automatic Post-Editing. COLING 2020: 5963-5974 - [c82]Shukrity Si, Anisha Datta, Sudip Kumar Naskar:
A New Approach to Claim Check-Worthiness Prediction and Claim Verification. ICON 2020: 155-160 - [c81]Souvick Das, Rajat Pandit, Sudip Kumar Naskar:
A Rule Based Lightweight Bengali Stemmer. ICON 2020: 400-408 - [c80]Jimmy Laishram, Kishorjit Nongmeikapam, Sudip Kumar Naskar:
Deep Neural Model for Manipuri Multiword Named Entity Recognition with Unsupervised Cluster Feature. ICON 2020: 420-429 - [d1]Avishek Garain, Arpan Basu, Sudip Kumar Naskar:
Dataset for Word Difficulty Prediction. IEEE DataPort, 2020
- [i3]Somnath Banerjee, Sudip Kumar Naskar, Paolo Rosso, Sivaji Bandyopadhyay:
Classifier Combination Approach for Question Classification for Bengali Question Answering System. CoRR abs/2008.13597 (2020)
2010 – 2019
- 2019
- [j12]Sourav Mandal, Sudip Kumar Naskar:
Solving Arithmetic Word Problems by Object Oriented Modeling and Query-Based Information Processing. Int. J. Artif. Intell. Tools 28(4): 1940002:1-1940002:23 (2019) - [j11]Rajat Pandit, Saptarshi Sengupta, Sudip Kumar Naskar, Niladri Sekhar Dash, Mohini Mohan Sardar:
Improving Semantic Similarity with Cross-Lingual Resources: A Study in Bangla - A Low Resourced Language. Informatics 6(2): 19 (2019) - [j10]Saptarshi Sengupta, Rajat Pandit, Parag Mitra, Sudip Kumar Naskar, Mohini Mohan Sardar:
Word sense induction in bengali using parallel corpora and distributional semantics. J. Intell. Fuzzy Syst. 36(5): 4821-4832 (2019) - [j9]Rohini Basak, Sudip Kumar Naskar, Alexander F. Gelbukh:
Short-answer grading using textual entailment. J. Intell. Fuzzy Syst. 36(5): 4909-4919 (2019) - [c79]Shukrity Si, Anisha Datta, Somnath Banerjee, Sudip Kumar Naskar:
Aggression Detection on Multilingual Social Media Text. ICCCNT 2019: 1-5 - [c78]Debargha Bhattacharjee, Hariom, Sourav Mandal, Sudip Kumar Naskar:
A Simple Arithmetic Calculator to Solve Single Sentence Mathematical Word Problems. ICITAM 2019: 511-524 - [c77]Mihaela Vela, Santanu Pal, Marcos Zampieri, Sudip Kumar Naskar, Josef van Genabith:
Improving CAT Tools in the Translation Workflow: New Approaches and Evaluation. MTSummit (2) 2019: 8-15 - [c76]Preeti Mukherjee, Mainak Pal, Somnath Banerjee, Sudip Kumar Naskar:
JU_ETCE_17_21 at SemEval-2019 Task 6: Efficient Machine Learning and Neural Network Approaches for Identifying and Categorizing Offensive Language in Tweets. SemEval@NAACL-HLT 2019: 662-667 - [c75]Arpan Basu, Avishek Garain, Sudip Kumar Naskar:
Word Difficulty Prediction Using Convolutional Neural Networks. TENCON 2019: 1109-1112 - [c74]Riktim Mondal, Shankha Raj Nayek, Aditya Chowdhury, Santanu Pal, Sudip Kumar Naskar, Josef van Genabith:
JU-Saarland Submission to the WMT2019 English-Gujarati Translation Shared Task. WMT (2) 2019: 308-313 - [i2]Mihaela Vela, Santanu Pal, Marcos Zampieri, Sudip Kumar Naskar, Josef van Genabith:
Improving CAT Tools in the Translation Workflow: New Approaches and Evaluation. CoRR abs/1908.06140 (2019) - [i1]Santanu Pal, Hongfei Xu, Nico Herbig, Sudip Kumar Naskar, Antonio Krüger, Josef van Genabith:
The Transference Architecture for Automatic Post-Editing. CoRR abs/1908.06151 (2019) - 2018
- [j8]Poulami Das, Sudip Kumar Naskar, Sankar Narayan Patra:
Hardware efficient FIR filter design using Global Best Steered Quantum Inspired Cuckoo Search Algorithm. Appl. Soft Comput. 71: 1-19 (2018) - [j7]Rohini Basak, Sudip Kumar Naskar, Alexander F. Gelbukh:
A simple hybrid approach to recognizing textual entailment. J. Intell. Fuzzy Syst. 34(5): 2873-2885 (2018) - [j6]Somnath Banerjee, Sudip Kumar Naskar, Paolo Rosso, Sivaji Bandyopadhyay:
Code mixed cross script factoid question classification - A deep learning approach. J. Intell. Fuzzy Syst. 34(5): 2959-2969 (2018) - [c73]Tanik Saikh, Sudip Kumar Naskar, Asif Ekbal:
Recognizing Textual Entailment Using Weighted Dependency Relations. CICLing (2) 2018: 221-233 - [c72]Amitrajit Sarkar, Surajit Dasgupta, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
Says Who? Deep Learning Models for Joint Speech Recognition, Segmentation and Diarization. ICASSP 2018: 5229-5233 - [c71]Joybrata Panja, Sudip Kumar Naskar:
ITER: Improving Translation Edit Rate through Optimizable Edit Costs. WMT (shared task) 2018: 746-750 - [c70]Prasenjit Basu, Santanu Pal, Sudip Kumar Naskar:
Keep It or Not: Word Level Quality Estimation for Post-Editing. WMT (shared task) 2018: 759-764 - 2017
- [j5]Somnath Banerjee, Sudip Kumar Naskar, Paolo Rosso, Sivaji Bandyopadhyay:
Named Entity Recognition on Code-Mixed Cross-Script Social Media Content. Computación y Sistemas 21(4) (2017) - [c69]Tanik Saikh, Sudip Kumar Naskar, Asif Ekbal, Sivaji Bandyopadhyay:
Textual Entailment Using Machine Translation Evaluation Metrics. CICLing (1) 2017: 317-328 - [c68]Santanu Pal, Sudip Kumar Naskar, Mihaela Vela, Qun Liu, Josef van Genabith:
Neural Automatic Post-Editing Using Prior Alignment and Reranking. EACL (2) 2017: 349-355 - [c67]Sourav Mandal, Sudip Kumar Naskar:
Solving Arithmetic Mathematical Word Problems: A Review and Recent Advancements. ICITAM 2017: 95-114 - [c66]Sourav Mandal, Sudip Kumar Naskar:
Natural Language Programing with Automatic Code Generation towards Solving Addition-Subtraction Word Problems. ICON 2017: 146-154 - [c65]Joy Mahapatra, Sudip Kumar Naskar:
Unsupervised Morpheme Segmentation Through Numerical Weighting and Thresholding. ICON 2017: 298-304 - [c64]Ajay Shankar Tiwari, Sudip Kumar Naskar:
Normalization of Social Media Text using Deep Neural Networks. ICON 2017: 312-321 - [c63]Amit Majumder, Asif Ekbal, Sudip Kumar Naskar:
Feature Selection and Class-Weight Tuning Using Genetic Algorithm for Bio-molecular Event Extraction. NLDB 2017: 28-33 - [c62]Sourav Mandal, Sudip Kumar Naskar:
Towards Generating Object-Oriented Programs Automatically from Natural Language Texts for Solving Mathematical Word Problems. NLDB 2017: 222-226 - 2016
- [c61]Santanu Pal, Sudip Kumar Naskar, Mihaela Vela, Josef van Genabith:
A Neural Network based Approach to Automatic Post-Editing. ACL (2) 2016 - [c60]Santanu Pal, Sudip Kumar Naskar, Josef van Genabith:
Forest to String Based Statistical Machine Translation with Hybrid Word Alignments. CICLing (2) 2016: 38-50 - [c59]Santanu Pal, Sudip Kumar Naskar, Marcos Zampieri, Tapas Nayak, Josef van Genabith:
CATaLog Online: A Web-based CAT Tool for Distributed Translation with Data Capture for APE and Translation Process Research. COLING (Demos) 2016: 98-102 - [c58]Santanu Pal, Sudip Kumar Naskar, Josef van Genabith:
Multi-Engine and Multi-Alignment Based Automatic Post-Editing and its Impact on Translation Productivity. COLING 2016: 2559-2570 - [c57]Somnath Banerjee, Sudip Kumar Naskar, Paolo Rosso, Sivaji Bandyopadhyay:
The First Cross-Script Code-Mixed Question Answering Corpus. MultiLingMine@ECIR 2016: 56-65 - [c56]Somnath Banerjee, Kunal Chakma, Sudip Kumar Naskar, Amitava Das, Paolo Rosso, Sivaji Bandyopadhyay, Monojit Choudhury:
Overview of the Mixed Script Information Retrieval (MSIR) at FIRE-2016. FIRE Workshop 2016: 39-49 - [c55]Surajit Dasgupta, Abhash Kumar, Dipankar Das, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
Word Embeddings for Information Extraction from Tweets. FIRE (Working Notes) 2016: 71-73 - [c54]Somnath Banerjee, Kunal Chakma, Sudip Kumar Naskar, Amitava Das, Paolo Rosso, Sivaji Bandyopadhyay, Monojit Choudhury:
Overview of the Mixed Script Information Retrieval (MSIR) at FIRE-2016. FIRE (Working Notes) 2016: 94-99 - [c53]Tanik Saikh, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
JU_NLP@DPIL-FIRE2016: Paraphrase Detection in Indian Languages - A Machine Learning Approach. FIRE (Working Notes) 2016: 275-278 - [c52]Amit Majumder, Asif Ekbal, Sudip Kumar Naskar:
Biomolecular Event Extraction using a Stacked Generalization based Classifier. ICON 2016: 55-64 - [c51]Joy Mahapatra, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
Statistical Natural Language Generation from Tabular Non-textual Data. INLG 2016: 143-152 - [c50]Santanu Pal, Marcos Zampieri, Sudip Kumar Naskar, Tapas Nayak, Mihaela Vela, Josef van Genabith:
CATaLog Online: Porting a Post-editing Tool to the Web. LREC 2016 - [c49]Koushik Pahari, Alapan Kuila, Santanu Pal, Sudip Kumar Naskar, Sivaji Bandyopadhyay, Josef van Genabith:
JU-USAAR: A Domain Adaptive MT System. WMT 2016: 442-448 - 2015
- [j4]Rohini Basak, Sudip Kumar Naskar, Partha Pakray, Alexander F. Gelbukh:
Recognizing Textual Entailment by Soft Dependency Tree Matching. Computación y Sistemas 19(4) (2015) - [c48]Tanik Saikh, Sudip Kumar Naskar, Chandan Giri, Sivaji Bandyopadhyay:
Textual Entailment Using Different Similarity Metrics. CICLing (1) 2015: 491-501 - [c47]Royal Sequiera, Monojit Choudhury, Parth Gupta, Paolo Rosso, Shubham Kumar, Somnath Banerjee, Sudip Kumar Naskar, Sivaji Bandyopadhyay, Gokul Chittaranjan, Amitava Das, Kunal Chakma:
Overview of FIRE-2015 Shared Task on Mixed Script Information Retrieval. FIRE Workshops 2015: 19-25 - [c46]Soumik Mandal, Somnath Banerjee, Sudip Kumar Naskar, Paolo Rosso, Sivaji Bandyopadhyay:
Adaptive Voting in Multiple Classifier Systems for Word Level Language Identification. FIRE Workshops 2015: 47-50 - [c45]Sombuddha Choudhury, Somnath Banerjee, Sudip Kumar Naskar, Paolo Rosso, Sivaji Bandyopadhyay:
Entity Extraction from Social Media using Machine Learning Approaches. FIRE Workshops 2015: 103-106 - [c44]Alok Ranjan Pal, Diganta Saha, Sudip Kumar Naskar, Niladri Sekhar Dash:
Word sense disambiguation in Bengali: A lemmatized system increases the accuracy of the result. ReTIS 2015: 342-346 - [c43]Sukanya Dutta, Tista Saha, Somnath Banerjee, Sudip Kumar Naskar:
Text normalization in code-mixed social media text. ReTIS 2015: 378-382 - [c42]Rajat Pandit, Sudip Kumar Naskar:
A memory based approach to word sense disambiguation in Bengali using k-NN method. ReTIS 2015: 383-386 - [c41]Santanu Pal, Sudip Kumar Naskar, Josef van Genabith:
UdS-Sant: English-German Hybrid Machine Translation System. WMT@EMNLP 2015: 152-157 - [c40]Santanu Pal, Mihaela Vela, Sudip Kumar Naskar, Josef van Genabith:
USAAR-SAPE: An English-Spanish Statistical Automatic Post-Editing System. WMT@EMNLP 2015: 216-221 - 2014
- [c39]Federico Gaspari, Antonio Toral, Sudip Kumar Naskar, Declan Groves, Andy Way:
Perception vs. reality: measuring machine translation post-editing productivity. WPTP@ATMA 2014: 60-72 - [c38]Santanu Pal, Pintu Lohar, Sudip Kumar Naskar:
Role of Paraphrases in PB-SMT. CICLing (2) 2014: 242-253 - [c37]Somnath Banerjee, Alapan Kuila, Aniruddha Roy, Sudip Kumar Naskar, Paolo Rosso, Sivaji Bandyopadhyay:
A Hybrid Approach for Transliterated Word-Level Language Identification: CRF with Post-Processing Heuristics. FIRE 2014: 54-59 - [c36]Santanu Pal, Partha Pakray, Sudip Kumar Naskar:
Automatic Building and Using Parallel Resources for SMT from Comparable Corpora. HyTra@EACL 2014: 48-57 - [c35]Santanu Pal, Braja Gopal Patra, Dipankar Das, Sudip Kumar Naskar, Sivaji Bandyopadhyay, Josef van Genabith:
How Sentiment Analysis Can Help Machine Translation. ICON 2014: 89-94 - [c34]Santanu Pal, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
Word Alignment-Based Reordering of Source Chunks in PB-SMT. LREC 2014: 3565-3571 - [c33]Somnath Banerjee, Pintu Lohar, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
The First Resource for Bengali Question Answering Research. PolTAL 2014: 290-297 - [c32]Somnath Banerjee, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
Bengali Named Entity Recognition Using Margin Infused Relaxed Algorithm. TSD 2014: 125-132 - [c31]Somnath Banerjee, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
BFQA: A Bengali Factoid Question Answering System. TSD 2014: 217-224 - 2013
- [c30]Renu Balyan, Sudip Kumar Naskar, Antonio Toral, Niladri Chatterjee:
A Diagnostic Evaluation Approach for English to Hindi MT Using Linguistic Checkpoints and Error Rates. CICLing (2) 2013: 285-296 - [c29]Santanu Pal, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
A Hybrid Word Alignment Model for Phrase-Based Statistical Machine Translation. HyTra@ACL 2013: 94-101 - [c28]Sudip Kumar Naskar, Antonio Toral, Federico Gaspari, Declan Groves:
Meta-Evaluation of a Diagnostic Quality Metric for Machine Translation. MTSummit 2013 - [c27]Santanu Pal, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
MWE Alignment in Phrase Based Statistical Machine Translation. MTSummit 2013 - [c26]Antonio Toral, Sudip Kumar Naskar, Joris Vreeke, Federico Gaspari, Declan Groves:
A Web Application for the Diagnostic Evaluation of Machine Translation over Specific Linguistic Phenomena. HLT-NAACL 2013: 20-23 - 2012
- [j3]Antonio Toral, Sudip Kumar Naskar, Federico Gaspari, Declan Groves:
DELiC4MT: A Tool for Diagnostic MT Evaluation over User-defined Linguistic Phenomena. Prague Bull. Math. Linguistics 98: 121-132 (2012) - [c25]Pratyush Banerjee, Sudip Kumar Naskar, Johann Roturier, Andy Way, Josef van Genabith:
Translation Quality-Based Supplementary Data Selection by Incremental Update of Translation Models. COLING 2012: 149-166 - [c24]Pratyush Banerjee, Sudip Kumar Naskar, Johann Roturier, Andy Way, Josef van Genabith:
Domain Adaptation in SMT of User-Generated Forum Content Guided by OOV Word Reduction: Normalization and/or Supplementary Data. EAMT 2012: 169-176 - 2011
- [j2]Rejwanul Haque, Sudip Kumar Naskar, Antal van den Bosch, Andy Way:
Integrating source-language context into phrase-based statistical machine translation. Mach. Transl. 25(3): 239-285 (2011) - [c23]Sarah Ebling, Andy Way, Martin Volk, Sudip Kumar Naskar:
Combining Semantic and Syntactic Generalization in Example-Based Machine Translation. EAMT 2011 - [c22]Antonio Toral, Federico Gaspari, Sudip Kumar Naskar, Andy Way:
A Comparative Evaluation of Research vs. Online MT Systems. EAMT 2011 - [c21]Pratyush Banerjee, Hala Almaghout, Sudip Kumar Naskar, Johann Roturier, Jie Jiang, Andy Way, Josef van Genabith:
The DCU machine translation systems for IWSLT 2011. IWSLT 2011: 41-48 - [c20]Pratyush Banerjee, Sudip Kumar Naskar, Johann Roturier, Andy Way, Josef van Genabith:
Domain Adaptation in Statistical Machine Translation of User-Forum Data using Component Level Mixture Modelling. MTSummit 2011 - [c19]Sudip Kumar Naskar, Antonio Toral, Federico Gaspari, Andy Way:
A Framework for Diagnostic Evaluation of MT Based on Linguistic Checkpoints. MTSummit 2011 - 2010
- [c18]Pratyush Banerjee, Jinhua Du, Baoli Li, Sudip Kumar Naskar, Andy Way, Josef van Genabith:
Combining Multi-Domain Statistical Machine Translation Models using Automatic Classifiers. AMTA 2010 - [c17]Rejwanul Haque, Sudip Kumar Naskar, Antal van den Bosch, Andy Way:
Supertags as Source Language Context in Hierarchical Phrase-Based SMT. AMTA 2010 - [c16]Rejwanul Haque, Sudip Kumar Naskar, Andy Way, Marta R. Costa-jussà, Rafael E. Banchs:
Sentence Similarity-Based Source Context Modelling in PBSMT. IALP 2010: 257-260 - [c15]Santanu Pal, Sudip Kumar Naskar, Pavel Pecina, Sivaji Bandyopadhyay, Andy Way:
Handling Named Entities and Compound Verbs in Phrase-Based Statistical Machine Translation. MWE@COLING 2010: 46-54 - [c14]Tsuyoshi Okita, Jie Jiang, Rejwanul Haque, Hala Almaghout, Jinhua Du, Sudip Kumar Naskar, Andy Way:
MaTrEx: the DCU MT System for NTCIR-8. NTCIR 2010: 377-383 - [c13]Sandipan Dandapat, Sara Morrissey, Sudip Kumar Naskar, Harold L. Somers:
Mitigating Problems in Analogy-based EBMT with SMT and vice versa: A Case Study with Named Entity Transliteration. PACLIC 2010: 365-372 - [c12]Sergio Penkale, Rejwanul Haque, Sandipan Dandapat, Pratyush Banerjee, Ankit K. Srivastava, Jinhua Du, Pavel Pecina, Sudip Kumar Naskar, Mikel L. Forcada, Andy Way:
MATREX: The DCU MT System for WMT 2010. WMT@ACL 2010: 143-148
2000 – 2009
- 2009
- [c11]Rejwanul Haque, Sandipan Dandapat, Ankit K. Srivastava, Sudip Kumar Naskar, Andy Way:
English-Hindi Transliteration Using Context-Informed PB-SMT: the DCU System for NEWS 2009. NEWS@IJCNLP 2009: 104-107 - [c10]Rejwanul Haque, Sudip Kumar Naskar, Yanjun Ma, Andy Way:
Using Supertags as Source Language Context in SMT. EAMT 2009 - [c9]Rejwanul Haque, Sudip Kumar Naskar, Antal van den Bosch, Andy Way:
Dependency Relations as Source Context in Phrase-Based SMT. PACLIC 2009: 170-179 - [c8]Rejwanul Haque, Sudip Kumar Naskar, Josef van Genabith, Andy Way:
Experiments on Domain Adaptation for English--Hindi SMT. PACLIC 2009: 670-677 - 2008
- [c7]Sivaji Bandyopadhyay, Tapabrata Mondal, Sudip Kumar Naskar, Asif Ekbal, Rejwanul Haque, Srinivasa Rao Godhavarthy:
Bengali, Hindi and Telugu to English Ad-hoc Bilingual Task. IJCNLP 2008: 66 - 2007
- [j1]Asif Ekbal, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
Named Entity Transliteration. Int. J. Comput. Process. Orient. Lang. 20(4): 289-310 (2007) - [c6]Sivaji Bandyopadhyay, Tapabrata Mondal, Sudip Kumar Naskar, Asif Ekbal, Rejwanul Haque, Srinivasa Rao Godhavarthy:
Bengali, Hindi and Telugu to English Ad-Hoc Bilingual Task at CLEF 2007. CLEF 2007: 88-94 - [c5]Sivaji Bandyopadhyay, Tapabrata Mondal, Sudip Kumar Naskar, Asif Ekbal, Rejwanul Haque, Srinivasa Rao Godhavarthy:
Bengali, Hindi and Telugu to English Ad-hoc Bilingual Task at CLEF 2007. CLEF (Working Notes) 2007 - [c4]Sudip Kumar Naskar, Sivaji Bandyopadhyay:
Word Sense Disambiguation Using Extended WordNet. ICCTA 2007: 446-450 - [c3]Asif Ekbal, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
Language Independent Named Entity Transliteration. IICAI 2007: 1936-1950 - [c2]Sudip Kumar Naskar, Sivaji Bandyopadhyay:
JU-SKNSB: Extended WordNet Based WSD on the English All-Words Task at SemEval-1. SemEval@ACL 2007: 203-206 - 2006
- [c1]Asif Ekbal, Sudip Kumar Naskar, Sivaji Bandyopadhyay:
A Modified Joint Source-Channel Model for Transliteration. ACL 2006
Coauthor Index
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