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FIRE 2019: Kolkata, India - Working Notes
- Parth Mehta, Paolo Rosso, Prasenjit Majumder, Mandar Mitra:
Working Notes of FIRE 2019 - Forum for Information Retrieval Evaluation, Kolkata, India, December 12-15, 2019. CEUR Workshop Proceedings 2517, CEUR-WS.org 2019
Artificial Intelligence for Legal Assistance (AILA)
- Paheli Bhattacharya, Kripabandhu Ghosh, Saptarshi Ghosh, Arindam Pal, Parth Mehta, Arnab Bhattacharya, Prasenjit Majumder:
Overview of the FIRE 2019 AILA Track: Artificial Intelligence for Legal Assistance. 1-12 - Ravina More, Jay Patil, Abhishek Palaskar, Aditi Pawde:
Removing Named Entities to Find Precedent Legal Cases. 13-18 - Baban Gain, Dibyanayan Bandyopadhyay, Arkadipta De, Tanik Saikh, Asif Ekbal:
IITP at AILA 2019: System Report for Artificial Intelligence for Legal Assistance Shared Task. 19-24 - Sara Renjit, Sumam Mary Idicula:
CUSAT NLP@AILA-FIRE2019: Similarity in Legal Texts using Document Level Embeddings. 25-30 - Soumil Mandal, Sourya Dipta Das:
Unsupervised Identification of Relevant Cases & Statutes Using Word Embeddings. 31-35 - S. Kayalvizhi, D. Thenmozhi, Chandrabose Aravindan:
Legal Assistance using Word Embeddings. 36-39 - Zicheng Zhao, Hui Ning, Liang Liu, Chengzhe Huang, Leilei Kong, Yong Han, Zhongyuan Han:
FIRE2019@AILA: Legal Information Retrieval Using Improved BM25. 40-45 - Yunqiu Shao, Ziyi Ye:
THUIR@AILA 2019: Information Retrieval Approaches for Identifying Relevant Precedents and Statutes. 46-51 - Moemedi Lefoane, Tshepho Koboyatshwene, Goaletsa Rammidi, V. Lakshmi Narasimham:
Legal Statutes Retrieval: A Comparative Approach on Performance of Title and Statutes Descriptive Text. 52-57 - R. Ramesh Kannan, R. Rajalakshmi:
DLRG@AILA 2019: Context - Aware Legal Assistance System. 58-63 - Jiaming Gao, Hui Ning, Huilin Sun, Ruifeng Liu, Zhongyuan Han, Leilei Kong, Haoliang Qi:
FIRE2019@AILA: Legal Retrieval Based on Information Retrieval Model. 64-69
Author profiling and deception detection in Arabic (APDA)
- Francisco M. Rangel Pardo, Paolo Rosso, Anis Charfi, Wajdi Zaghouani, Bilal Ghanem, Javier Sánchez-Junquera:
Overview of the Track on Author Profiling and Deception Detection in Arabic. 70-83 - Chiyu Zhang, Muhammad Abdul-Mageed:
BERT-Based Arabic Social Media Author Profiling. 84-91 - Hamada A. Nayel:
NAYEL@APDA: Machine Learning Approach for Author Profiling and Deception Detection in Arabic Texts. 92-99 - Haritha Ananthakrishnan, Akshaya Ranganathan, D. Thenmozhi, Chandrabose Aravindan:
Arabic Author Profiling and Deception Detection using Traditional Learning Methodologies with Word Embedding. 100-104 - Yutong Sun, Hui Ning, Kaisheng Chen, Leilei Kong, Yunpeng Yang, Jiexi Wang, Haoliang Qi:
Author Profiling in Arabic Tweets: An Approach based on Multi-Classification with Word and Character Features. 105-109 - Jorge Cabrejas, Jose Vicente Martí, Antonio Pajares, Víctor Sanchis:
Deception Detection in Arabic Texts Using N-grams Text Mining. 110-114 - Al Hafiz Akbar Maulana Siagian, Masayoshi Aritsugi:
DBMS-KU Approach for Author Profiling and Deception Detection in Arabic. 115-121 - F. Javier Fernández-Bravo Peñuela:
Deception Detection in Arabic Tweets and News. 122-126 - Isabella Karabasz, Paolo Cellini, Gonzalo Galiana:
Predicting Author Characteristics of Arabic Tweets through Author Profiling. 127-135 - Sharmila Devi V, Kannimuthu S, Ravikumar G, Anand Kumar M:
KCE DALab-APDA@FIRE2019: Author Profiling and Deception Detection in Arabic using Weighted Embedding. 136-143 - Khaled Alrifai, Ghaida Rebdawi, Nada Ghneim:
Arabic Tweeps Traits Prediction AT2P. 144-151 - Francisco Eros Blázquez del Rio, Manuel Conde Rodríguez, Jose M. Escalante:
Detection of deceptions in Twitter and News Headlines written in Arabic. 152-159 - Chanchal Suman, Purushottam Kumar
, Sriparna Saha, Pushpak Bhattacharyya:
Gender Age and Dialect Recognition using Tweets in a Deep Learning Framework - Notebook for FIRE 2019. 160-166
Hate Speech and Offensive Content Identification in Indo-European Languages (HASOC)
- Sandip Modha, Thomas Mandl, Prasenjit Majumder, Daksh Patel:
Overview of the HASOC track at FIRE 2019: Hate Speech and Offensive Content Identification in Indo-European Languages. 167-190 - Bin Wang, Yunxia Ding, Shengyan Liu, Xiaobing Zhou:
YNU_Wb at HASOC 2019: Ordered Neurons LSTM with Attention for Identifying Hate Speech and Offensive Language. 191-198 - Tharindu Ranasinghe, Marcos Zampieri, Hansi Hettiarachchi:
BRUMS at HASOC 2019: Deep Learning Models for Multilingual Hate Speech and Offensive Language Identification. 199-207 - Shubhanshu Mishra, Sudhanshu Mishra:
3Idiots at HASOC 2019: Fine-tuning Transformer Neural Networks for Hate Speech Identification in Indo-European Languages. 208-213 - Victor Nina-Alcocer:
Vito at HASOC 2019: Detecting Hate Speech and Offensive Content through Ensembles. 214-220 - Zhibin Lu, Jian-Yun Nie:
RALIGRAPH at HASOC 2019: VGCN-BERT: Augmenting BERT with Graph Embedding for Offensive Language Detection. 221-228 - Arup Baruah
IIITG-ADBU at HASOC 2019: Automated Hate Speech and Offensive Content Detection in English and Code-Mixed Hindi Text. 229-236 - Md. Abul Bashar, Richi Nayak:
QutNocturnal@HASOC'19: CNN for Hate Speech and Offensive Content Identification in Hindi Language. 237-245 - Punyajoy Saha, Binny Mathew, Pawan Goyal, Animesh Mukherjee:
HateMonitors: Language Agnostic Abuse Detection in Social Media. 246-253 - Aiqi Jiang:
QMUL-NLP at HASOC 2019: Offensive Content Detection and Classification in Social Media. 254-262 - Dana Ruiter, Md. Ataur Rahman
LSV-UdS at HASOC 2019: The Problem of Defining Hate. 263-270 - Vandan Mujadia, Pruthwik Mishra, Dipti Misra Sharma:
IIIT-Hyderabad at HASOC 2019: Hate Speech Detection. 271-278 - Jean-Christophe Mensonides, Pierre-Antoine Jean, Andon Tchechmedjiev, Sébastien Harispe:
IMT Mines Ales at HASOC 2019: Automatic Hate Speech Detection. 279-284 - Ritesh Kumar, Atul Kr. Ojha:
KMI-Panlingua at HASOC 2019: SVM vs BERT for Hate Speech and Offensive Content Detection. 285-292 - Pedro Alonso, Rajkumar Saini, György Kovács:
TheNorth at HASOC 2019: Hate Speech Detection in Social Media Data. 293-299 - Marco Casavantes, Roberto López-Santillán, Luis Carlos González-Gurrola, Manuel Montes-y-Gómez:
UACh-INAOE at HASOC 2019: Detecting Aggressive Tweets by Incorporating Authors' Traits as Descriptors. 300-307 - Anita Saroj, Rajesh Kumar Mundotiya, Sukomal Pal:
IRLab@IITBHU at HASOC 2019: Traditional Machine Learning for Hate Speech and Offensive Content Identification. 308-314 - Apurva Parikh, Harsh Desai, Abhimanyu Singh Bisht:
DA Master at HASOC 2019: Identification of Hate Speech using Machine Learning and Deep Learning approaches for social media post. 315-319 - Kaushik Amar Das, Ferdous Ahmed Barbhuiya:
Team FalsePostive at HASOC 2019: Transfer-Learning for Detection and Classification of Hate Speech. 320-327 - Kirti Kumari, Jyoti Prakash Singh:
AI ML NIT Patna at HASOC 2019: Deep Learning Approach for Identification of Abusive Content. 328-335 - Hamada A. Nayel, H. L. Shashirekha:
DEEP at HASOC2019: A Machine Learning Framework for Hate Speech and Offensive Language Detection. 336-343 - Akanksha Mishra, Sukomal Pal:
IIT Varanasi at HASOC 2019: Hate Speech and Offensive Content Identification in Indo-European Languages. 344-351 - Urmi Saha, Abhijeet Dubey, Pushpak Bhattacharyya:
IIT Bombay at HASOC 2019: Supervised Hate Speech and Offensive Content Detection in Indo-European Languages. 352-358 - Baidya Nath Saha, Apurbalal Senapati:
CIT Kokrajhar Team: LSTM based Deep RNN Architecture for Hate Speech and Offensive Content (HASOC) Identification in Indo-European Languages. 359-365 - Sreelakshmi K, Premjith B, Soman K. P:
Amrita CEN at HASOC 2019: Hate Speech Detection in Roman and Devanagiri Scripted Text. 366-369 - R. Rajalakshmi, B. Yashwant Reddy:
DLRG@HASOC 2019: An Enhanced Ensemble Classifier for Hate and Offensive Content Identification. 370-379
Irony Detection in Arabic Tweets (IDAT)
- Bilal Ghanem, Jihen Karoui, Farah Benamara, Véronique Moriceau, Paolo Rosso:
IDAT@FIRE2019: Overview of the Track on Irony Detection in Arabic Tweets. 380-390 - Chiyu Zhang, Muhammad Abdul-Mageed:
Multi-Task Bidirectional Transformer Representations for Irony Detection. 391-400 - Hamada A. Nayel, Walaa Medhat, Metwally Rashad:
BENHA@IDAT: Improving Irony Detection in Arabic Tweets using Ensemble Approach. 401-408 - Leila Moudjari, Karima Akli-Astouati:
An Embedding-based Approach for Irony Detection in Arabic tweets. 409-415 - Tharindu Ranasinghe, Hadeel Saadany, Alistair Plum, Salim Mandhari, Emad Mohamed, Constantin Orasan, Ruslan Mitkov:
RGCL at IDAT: Deep Learning models for Irony Detection in Arabic Language. 416-425 - Nikita Kanwar, Rajesh Kumar Mundotiya, Megha Agarwal, Chandradeep Singh:
Emotion based voted classifier for Arabic irony tweet identification. 426-432 - Muhammad Khalifa, Noura Hussein:
Ensemble Learning for Irony Detection in Arabic Tweets. 433-438 - S. Kayalvizhi, D. Thenmozhi, B. Senthil Kumar, Chandrabose Aravindan:
SSN_NLP@IDAT-FIRE-2019: Irony Detection in Arabic Tweets using Deep Learning and Features-based Approaches. 439-444 - Ali Allaith, Muhammad Shahbaz, Mohammed Alkoli:
Neural Network Approach for Irony Detection from Arabic Text on Social Media. 445-450
Classification of Insincere Questions (CIQ)
- Vandan Mujadia, Pruthwik Mishra, Dipti Misra Sharma:
Classification of Insincere Questions with ML and Neural Approaches. 451-455 - Chandni M, Priyanga V. T, Premjith B, Soman K. P:
Amrita CEN CIQ: Classification of Insincere Questions. 456-462 - Akshaya Ranganathan, Haritha Ananthakrishnan, D. Thenmozhi, Chandrabose Aravindan:
Classification of Insincere Questions using SGD Optimization and SVM Classifiers. 463-467 - Akanksha Mishra, Sukomal Pal:
IIT-BHU at CIQ 2019: Classification of Insincere Questions. 468-472 - Sourya Dipta Das, Ayan Basak, Soumil Mandal:
Fine Grained Insincere Questions Classification using Ensembles of Bidirectional LSTM-GRU Model. 473-481 - Zhongyuan Han, Jiaming Gao, Huilin Sun, Ruifeng Liu, Chengzhe Huang, Leilei Kong, Haoliang Qi:
An Ensemble Learning-based Model for Classification of Insincere Questions. 482-488
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