Table of Contents

• Overview of the FIRE 2018 Track: Information Retrieval from Microblogs during Disasters (IRMiDis)Moumita Basu, Saptarshi Ghosh, Kripabandhu Ghosh. 1-10 [doi]
• Measuring Fact Check-ability in MicroblogsAnurag Banerjee. 11-14 [doi]
• DAIICT-Hildesheim @ Information Retrieval from Microblogs during Disasters (IRMiDis 2018)Noushin Fadaei, Chanjong Im, Sandip Modha, Thomas Mandl. 15-17 [doi]
• Fully Automatic Approach to Identify Factual or Fact-checkable TweetsSarthak Anand, Rajat Gupta, Rajiv Ratn Shah, Ponnurangam Kumaraguru. 18-23 [doi]
• IIT BHU at FIRE 2018 IRMiDis Track - Obtaining Factual Tweets during Natural DisastersHarshit Mehrotra, Sukomal Pal. 24-27 [doi]
• A String Kernel based Information Retrieval Approach for Tweet-validation through NewsMuhammad Rafi, Fizza Abid, Anum Mirza, Hamza Mustafa Khan. 28-33 [doi]
• Identify Fact-checkable TweetsSiddharth Ghelani, Divyank Barnwal, Rohit Krishna. 34-38 [doi]
• Overview of the second shared task on Indian Native Language Identification (INLI)Anand Kumar M, Barathi Ganesh H. B., Ajay S. G, Soman K. P. 39-50 [doi]
• INLI@FIRE-2018: A Native Language Identification System using Convolutional Neural NetworksAjees A. P, Sumam Mary Idicula. 51-58 [doi]
• Statistical testing based feature selection for Native Language Identification INLI@FIRE2018B. Bharathi, Bhuvana J. 59-67 [doi]
• A Machine Learning Approach to Indian Native Language IdentificationD. Thenmozhi, S. Kayalvizhi, Chandrabose Aravindan. 68-76 [doi]
• Corplab INLI@FIRE-2018: Identification of Indian Native Language using Pairwise CouplingSoumik Mondal, Athul Harilal, Alexander Binder. 77-81 [doi]
• CIC-IPN@INLI2018: Indian Native Language IdentificationIlia Markov, Grigori Sidorov. 82-88 [doi]
• Team WebArch at FIRE-2018 Track on Indian Native Language IdentificationAman Gupta. 89-94 [doi]
• NLPRL@INLI-2018: Hybrid gated LSTM-CNN model for Indian Native Language IdentificationRajesh Kumar Mundotiya, Manish Singh, Anil Kumar Singh. 95-101 [doi]
• IIITV@INLI-2018 : Hyperdimensional Computing for Indian Native Language IdentificationAshish Patel, Pratik Shah. 102-109 [doi]
• Mangalore University INLI@FIRE2018: Artificial Neural Network and Ensemble based Models for INLIHamada A. Nayel, H. L. Shashirekha. 110-118 [doi]
• Overview of Arnekt IECSIL at FIRE-2018 Track on Information Extraction for Conversational Systems in Indian LanguagesBarathi Ganesh H. B., Soman K. P, Reshma U, Mandar Kale, Prachi Mankame, Gouri Kulkarni, Anitha Kale, Anand Kumar M. 119-128 [doi]
• CUSAT_TEAM@IECSIL-FIRE-2018: A Named Entity Recognition System for Indian LanguagesAjees A. P, Sumam Mary Idicula. 129-136 [doi]
• HiLT@IECSIL-FIRE-2018: A Named Entity Recognition System for Indian LanguagesSagar, Srinivas P. Y. K. L, Rusheel Koushik Gollakota, Amitava Das. 137-144 [doi]
• IIT(BHU)@IECSIL-FIRE2018: Language Independent Automatic Framework for Entity Extraction in Indian LanguagesAkanksha Mishra, Rajesh Kumar Mundotiya, Sukomal Pal. 145-152 [doi]
• Khushleen@IECSIL-FIRE-2018: Indic Language Named Entity Recognition using Bidirectional LSTMs with Subword InformationKhushleen Kaur. 153-157 [doi]
• idrbt-team-a@IECSIL-FIRE-2018 Named Entity Recognition of Indian Languages using bi-LSTMS. Nagesh Bhattu, N. Satya Krishna, Durvasula V. L. N. Somayajulu. 158-165 [doi]
• idrbt-team-a@IECSIL-FIRE-2018 : Relation Categorization for Social Media News TextN. Satya Krishna, S. Nagesh Bhattu, Durvasula V. L. N. Somayajulu. 166-173 [doi]
• raiden11@IECSIL-FIRE-2018 : Named Entity Recognition for Indian LanguagesAyush Gupta, Meghna Ayyar, Ashutosh Kumar Singh, Rajiv Ratn Shah. 174-186 [doi]
• SSN_NLP@IECSIL-FIRE-2018: Deep Learning Approach to Named Entity Recognition and Relation Extraction for Conversational Systems in Indian LanguagesD. Thenmozhi, Senthil Kumar, Chandrabose Aravindan. 187-201 [doi]
• MAPonSMS - Overview of the Multilingual SMS-based Author Profiling task at FIRE'18Muhammad Sharjeel, Mehwish Fatima, Saba Anwar, Rao Muhammad Adeel Nawab. 202-212 [doi]
• KCE_DAlab@MAPonSMS-FIRE2018: Effective word and character-based features for Multilingual Author ProfilingSharmila Devi V, Kannimuthu S, Ravikumar G, Anand Kumar M. 213-222 [doi]
• Multi-lingual Author Profiling on SMS Messages using Machine Learning Approach with Statistical Feature SelectionD. Thenmozhi, A. Kalaivani, Chandrabose Aravindan. 223-231 [doi]
• Gender and Age Prediction Multilingual Author Profiles Based on CommentsAli Nemati. 232-239 [doi]
• Multi-lingual Author Profiling using Stylistic FeaturesAbdul Sittar, Iqra Ameer. 240-246 [doi]
• Using Bag-of-Words and Psycho-Linguistic features for MAPonSMSAsmara Safdar, Osama Akhter, Osama Inayat, Abdullah Khalid. 247-256 [doi]
• MAPonSMS18: Multilingual Author Profiling using Combination of FeaturesRamsha Imran, Muntaha Iqbal. 257-264 [doi]
• Multilingual Author Profiling from SMSDeepanshu Gaur, Meghna Ayyar, Ashutosh Kumar Singh, Rajiv Ratn Shah. 265-276 [doi]
• A Statistical Approach to Gender and Age Range Classification in Multilingual CorpusÒscar Garibo i Orts, Francisco Rangel. 277-281 [doi]
• EventXtract-IL: Event Extraction from Newswires and Social Media Text in Indian Languages @ FIRE 2018 - An OverviewPattabhi R. K. Rao, Sobha Lalitha Devi. 282-290 [doi]
• A Neural Network based Event Extraction System for Indian LanguagesAlapan Kuila, Sarath chandra Bussa, Sudeshna Sarkar. 291-301 [doi]
• Rule based Event Extraction System from Newswires and Social Media Text in Indian Languages (EventXtract-IL) for English and Hindi DataAnita Saroj, Rajesh kumar Munodtiya, Sukomal Pal. 302-307 [doi]
• Overview of Verb Phrase Translation in Machine Translation: English to Tamil and Hindi to TamilR. Vijay Sundar Ram, Sobha Lalitha Devi. 308-315 [doi]
• NMT based Tamil TranslationAditya Kumar Pathak, Himanshu Choudhary, Rajiv Ratn Shah. 316-322 [doi]
• Deep Learning Approach to English-Tamil and Hindi-Tamil Verb Phrase TranslationsD. Thenmozhi, B. Senthil Kumar, Chandrabose Aravindan. 323-331 [doi]
• A Transfer-rule based Verb Phrase Translation from English to TamilParameswari K, Nagaraju V, Angeline Linda K. 332-336 [doi]