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ORCIDCLEF 2019: Lugano, Switzerland - Working Notes
- Linda Cappellato, Nicola Ferro, David E. Losada, Henning Müller:
Working Notes of CLEF 2019 - Conference and Labs of the Evaluation Forum, Lugano, Switzerland, September 9-12, 2019. CEUR Workshop Proceedings 2380, CEUR-WS.org 2019
CENTRE@CLEF - CLEF/NTCIR/TREC Reproducibility
- Nicola Ferro, Norbert Fuhr, Maria Maistro, Tetsuya Sakai, Ian Soboroff:
CENTRE@CLEF2019: Overview of the Replicability and Reproducibility Tasks. - Timo Breuer, Philipp Schaer:
Replicability and Reproducibility of Automatic Routing Runs.
CheckThat! - Automatic Identification and Verification of Claims
- Pepa Atanasova, Preslav Nakov, Georgi Karadzhov, Mitra Mohtarami, Giovanni Da San Martino:
Overview of the CLEF-2019 CheckThat! Lab: Automatic Identification and Verification of Claims. Task 1: Check-Worthiness. - Maram Hasanain, Reem Suwaileh, Tamer Elsayed, Alberto Barrón-Cedeño, Preslav Nakov:
Overview of the CLEF-2019 CheckThat! Lab: Automatic Identification and Verification of Claims. Task 2: Evidence and Factuality. - Bahadir Altun, Mücahid Kutlu:
TOBB-ETU at CLEF 2019: Prioritizing Claims Based on Check-Worthiness. - Lucia Georgiana Coca, Ciprian-Gabriel Cusmuliuc, Adrian Iftene:
CheckThat! 2019 UAICS. - Rudra Dhar, Subhabrata Dutta, Dipankar Das:
A Hybrid Model to Rank Sentences for Check-worthiness. - Luca Favano, Mark J. Carman, Pier Luca Lanzi:
TheEarthIsFlat's Submission to CLEF'19CheckThat! Challenge. - Bilal Ghanem, Goran Glavas, Anastasia Giachanou, Simone Paolo Ponzetto, Paolo Rosso, Francisco M. Rangel Pardo:
UPV-UMA at CheckThat! Lab: Verifying Arabic Claims using a Cross Lingual Approach. - Jakub Gasior, Piotr Przybyla
:
The IPIPAN Team Participation in the Check-Worthiness Task of the CLEF2019 CheckThat! Lab. - Casper Hansen, Christian Hansen, Jakob Grue Simonsen, Christina Lioma:
Neural Weakly Supervised Fact Check-Worthiness Detection with Contrastive Sampling-Based Ranking Loss. - Fatima Haouari, Zien Sheikh Ali, Tamer Elsayed:
bigIR at CLEF 2019: Automatic Verification of Arabic Claims over the Web. - Ritesh Kumar, Shivansh Prakash, Shashank Kumar, Rajendra Pamula:
Check That! Automatic Identification and Verification of Claims: IIT(ISM) @CLEF'19 Check Worthiness. - Salar Mohtaj, Tilo Himmelsbach, Vinicius Woloszyn, Sebastian Möller:
Using External Knowledge Bases and Coreference Resolution for Detecting Check-Worthy Statements. - Ting Su, Craig Macdonald, Iadh Ounis:
Entity Detection for Check-worthiness Prediction: Glasgow Terrier at CLEF CheckThat! 2019. - Ibtissam Touahri, Azzeddine Mazroui:
Automatic Verification of Political Claims Based on Morphological Features.
CLEF eHealth
- Evangelos Kanoulas, Dan Li, Leif Azzopardi, René Spijker:
CLEF 2019 Technology Assisted Reviews in Empirical Medicine Overview. - Mariana L. Neves, Daniel Butzke, Antje Dörendahl, Nora Leich, Benedikt Hummel, Gilbert Schönfelder, Barbara Grune:
Overview of the CLEF eHealth 2019 Multilingual Information Extraction. - Nizar Ahmed, Aliriza Aribas, Adil Alpkocak:
DEMIR at CLEF eHealth 2019: Information Retrieval based Classification of Animal Experiments Summaries. - Amal Alharbi, Mark Stevenson:
Ranking Studies for Systematic Reviews Using Query Adaptation: University of Sheffield's Approach to CLEF eHealth 2019 Task 2. - Saadullah Amin, Guenter Neumann, Katherine Dunfield, Anna Vechkaeva, Kathryn Annette Chapman, Morgan Kelly Wixted:
MLT-DFKI at CLEF eHealth 2019: Multi-label Classification of ICD-10 Codes with BERT. - Giorgio Maria Di Nunzio:
Classification of Animal Experiments: A Reproducible Study. IMS Unipd at CLEF eHealth Task 1. - Giorgio Maria Di Nunzio:
A Distributed Effort Approach for Systematic Reviews. IMS Unipd At CLEF 2019 eHealth Task 2. - S. Kayalvizhi, D. Thenmozhi, Chandrabose Aravindan:
Deep Learning Approach for Semantic Indexing of Animal Experiments Summaries in German Language. - Dan Li, Evangelos Kanoulas:
Automatic Thresholding by Sampling Documents and Estimating Recall. - Mario Sänger, Leon Weber, Madeleine Kittner, Ulf Leser:
Classifying German Animal Experiment Summaries with Multi-lingual BERT at CLEF eHealth 2019 Task 1.
eRisk - Early Risk Prediction on the Internet
- David E. Losada, Fabio Crestani, Javier Parapar:
Overview of eRisk at CLEF 2019: Early Risk Prediction on the Internet (extended overview). - Pegah Abed-Esfahani, Derek Howard, Marta Maslej, Sejal Patel, Vamika Mann, Sarah Goegan, Leon French:
Transfer Learning for Depression: Early Detection and Severity Prediction from Social Media Postings. - Mario Ezra Aragón, Adrián Pastor López-Monroy, Manuel Montes-y-Gómez:
INAOE-CIMAT at eRisk 2019: Detecting Signs of Anorexia using Fine-Grained Emotions. - Sergio Gastón Burdisso, Marcelo Errecalde, Manuel Montes-y-Gómez:
UNSL at eRisk 2019: a Unified Approach for Anorexia, Self-harm and Depression Detection in Social Media. - Elena Fano, Jussi Karlgren, Joakim Nivre:
Uppsala University and Gavagai at CLEF eRISK: Comparing Word Embedding Models. - Razan Masood, Faneva Ramiandrisoa, Ahmet Aker:
UDE at eRisk 2019: Early Risk Prediction on the Internet. - Elham Mohammadi, Hessam Amini, Leila Kosseim:
Quick and (maybe not so) Easy Detection of Anorexia in Social Media Posts. - Nona Naderi, Julien Gobeill, Douglas Teodoro, Emilie Pasche, Patrick Ruch:
A Baseline Approach for Early Detection of Signs of Anorexia and Self-harm in Reddit Posts. - Rosa María Ortega-Mendoza, Delia Irazú Hernández Farías, Manuel Montes-y-Gómez:
LTL-INAOE's Participation at eRisk 2019: Detecting Anorexia in Social Media through Shared Personal Information. - Flor Miriam Plaza del Arco, Pilar López-Úbeda, Manuel Carlos Díaz-Galiano, Luis Alfonso Ureña López, María Teresa Martín Valdivia:
Integrating UMLS for Early Detection of Sings of Anorexia. - Waleed Ragheb, Jérôme Azé, Sandra Bringay, Maximilien Servajean:
Attentive Multi-stage Learning for Early Risk Detection of Signs of Anorexia and Self-harm on Social Media. - Akshaya Ranganathan, Haritha A, D. Thenmozhi, Chandrabose Aravindan:
Early Detection of Anorexia using RNN-LSTM and SVM Classifiers. - Pablo Ráez García Retamero, Isabel Segura-Bedmar:
Early Risk Prediction by means of DeepLearning. - Paul Van Rijen, Douglas Teodoro, Nona Naderi, Luc Mottin, Julien Knafou, Matt Jeffryes, Patrick Ruch:
A Data-Driven Approach for Measuring the Severity of the Signs of Depression using Reddit Posts. - Alina Trifan, José Luís Oliveira:
BioInfo@UAVR at eRisk 2019: delving into Social Media Texts for the Early Detection of Mental and Food Disorders.
LifeCLEF - Biodiversity Identification and Prediction
- Hervé Goëau, Pierre Bonnet, Alexis Joly:
Overview of LifeCLEF Plant Identification Task 2019: diving into Data Deficient Tropical Countries. - Stefan Kahl, Fabian-Robert Stöter, Hervé Goëau, Hervé Glotin, Bob Planqué, Willem-Pier Vellinga, Alexis Joly:
Overview of BirdCLEF 2019: Large-Scale Bird Recognition in Soundscapes. - Christophe Botella, Maximilien Servajean, Pierre Bonnet, Alexis Joly:
Overview of GeoLifeCLEF 2019: Plant Species Prediction using Environment and Animal Occurrences. - Costel-Sergiu Atodiresei, Adrian Iftene:
Location-Based Species Recommendation - GeoLifeCLEF 2019 Challenge. - Jisheng Bai, Bolun Wang, Chen Chen, Jianfeng Chen, Zhonghua Fu:
Inception-v3 Based Method of LifeCLEF 2019 Bird Recognition. - Sophia Chulif, Kiat Jing Heng, Teck Wei Chan, Mohammad Abdullah Al Monnaf, Yang Loong Chang:
Plant Identication on Amazonian and Guiana Shield Flora: NEUON submission to LifeCLEF 2019 Plant. - Nanda H. Krishna, Praveen Kumar R, Ram Kaushik R, Palaniappan Mirunalini, Chandrabose Aravindan, S. M. Jaisakthi:
Species Recommendation using Machine Learning - GeoLifeCLEF 2019. - Chih-Yuan Koh, Jaw-Yuan Chang, Chiang-Lin Tai, Da-Yo Huang, Han-Hsing Hsieh, Yi-Wen Liu:
Bird Sound Classification Using Convolutional Neural Networks. - Mario Lasseck:
Bird Species Identification in Soundscapes. - Pascal Monestiez, Christophe Botella:
Species Recommendation using Intensity Models and Sampling Bias Correction (GeoLifeCLEF 2019: Lof_of_Lof team). - Mathilde Negri, Maximilien Servajean, Benjamin Deneu, Alexis Joly:
Location-Based Plant Species Prediction Using A CNN Model Trained On Several Kingdoms - Best Method Of GeoLifeCLEF 2019 Challenge. - Dat Nguyen Thanh, Georges Quénot, Lorraine Goeuriot:
Non-local DenseNet for Plant CLEF 2019 Contest. - Lukás Picek, Milan Sulc, Jiri Matas:
Recognition of the Amazonian flora by InceptionNetworks with Test-time Class Prior Estimation. - Sara Si-Moussi, Mickael Hedde, Wilfried Thuiller:
Plant Recommendation using Environment and Biotic Associations.
ImageCLEF - Multimedia Retrieval in CLEF
- Yashin Dicente Cid, Vitali Liauchuk, Dzmitri Klimuk, Aleh Tarasau, Vassili Kovalev, Henning Müller:
Overview of ImageCLEFtuberculosis 2019 - Automatic CT-based Report Generation and Tuberculosis Severity Assessment. - Jon Chamberlain, Antonio Campello, Jessica P. Wright, Louis G. Clift, Adrian F. Clark, Alba García Seco de Herrera:
Overview of ImageCLEFcoral 2019 Task. - Duc-Tien Dang-Nguyen, Luca Piras, Michael Riegler, Liting Zhou, Mathias Lux, Minh-Triet Tran, Tu-Khiem Le, Van-Tu Ninh, Cathal Gurrin:
Overview of ImageCLEFlifelog 2019: Solve My Life Puzzle and Lifelog Moment Retrieval. - Obioma Pelka, Christoph M. Friedrich, Alba García Seco de Herrera, Henning Müller:
Overview of the ImageCLEFmed 2019 Concept Detection Task. - Konstantinos Karampidis, Nikos Vasilopoulos, Carlos Cuevas, Carlos Roberto del-Blanco, Ergina Kavallieratou, Narciso García:
Overview of the ImageCLEFsecurity 2019: File Forgery Detection Tasks. - Asma Ben Abacha, Sadid A. Hasan, Vivek V. Datla, Joey Liu, Dina Demner-Fushman, Henning Müller:
VQA-Med: Overview of the Medical Visual Question Answering Task at ImageCLEF 2019. - Aisha Al-Sadi, Bashar Talafha, Mahmoud Al-Ayyoub, Yaser Jararweh, Fumie Costen:
JUST at ImageCLEF 2019 Visual Question Answering in the Medical Domain. - Imane Allaouzi, Mohamed Ben Ahmed, Badr Benamrou:
An Encoder-Decoder Model for Visual Question Answering in the Medical Domain. - João Rafael Almeida, Pedro Freire, Olga Fajarda, José Luís Oliveira:
A Weighted Rule-Based Model for File Forgery Detection: UA.PT Bioinformatics at ImageCLEF 2019. - Mohit Bansal, Tanmay Gadgil, Rishi Shah, Parag Verma:
Medical Visual Question Answering at Image CLEF 2019- VQA Med. - Fatma Ben Abdallah, Ghada Feki, Anis Ben Ammar, Chokri Ben Amar:
Big Data For Lifelog Moments Retrieval Improvement. - Kirill Bogomasov, Daniel Braun, Andreas Burbach, Ludmila Himmelspach, Stefan Conrad:
Feature and Deep Learning Based Approaches for Automatic Report Generation and Severity Scoring of Lung Tuberculosis from CT Images. - Kirill Bogomasov, Philipp Grawe, Stefan Conrad:
A two-staged Approach for Localization and Classification of Coral Reef Structures and Compositions. - Rabia Bounaama, Mohammed El Amine Abderrahim:
Tlemcen University at ImageCLEF 2019 Visual Question Answering Task. - Cristina M. R. Caridade, André R. S. Marçal:
Automatic Classification of Coral Images using Color and Textures. - Minh-Son Dao, Anh-Khoa Vo, Trong-Dat Phan, Koji Zettsu:
BIDAL@imageCLEFlifelog2019: The Role of Content and Context of Daily Activities in Insights from Lifelogs. - Yashin Dicente Cid, Henning Müller:
Lung Graph-Model Classification with SVM and CNN for Tuberculosis Severity Assessment and Automatic CT Report Generation. - Mihai Dogariu, Bogdan Ionescu:
Multimedia Lab @ ImageCLEF 2019 Lifelog Moment Retrieval Task. - Amilcare Gentili:
ImageCLEF2019: Tuberculosis - Severity Scoring and CT Report with Neural Networks, Transfer Learning and Ensembling. - Amilcare Gentili, Paolo Gentili:
ImageCLEF2019 Security - Forged File Discovery and Stego Image Discovery Tasks. - Ana Jorge Gonçalves, Eduardo Pinho, Carlos Costa:
Informative and Intriguing Visual Features: UA.PT Bioinformatics in ImageCLEF Caption 2019. - Zhen Guo, Xuwen Wang, Yu Zhang, Jiao Li:
ImageSem at ImageCLEFmed Caption 2019 Task: a Two-stage Medical Concept Detection Strategy. - Abdelkader Hamadi, Noreddine Belhadj Cheikh, Yamina Zouatine, Si Mohamed Bekkai Menad, Mohamed Redha Djebbara:
ImageCLEF 2019: Deep Learning for Tuberculosis CT Image Analysis. - Trung-Hieu Hoang, Mai-Khiem Tran, Vinh-Tiep Nguyen, Minh-Triet Tran:
Solving Life Puzzle with Visual Context-based Clustering and Habit Reference. - Siarhei Kazlouski:
ImageCLEF 2019: CT Image Analysis for TB Severity Scoring and CT Report Generation using Autoencoded Image Features. - Tomasz Kornuta, Deepta Rajan, Chaitanya Shivade, Alexis Asseman, Ahmet S. Ozcan:
Leveraging Medical Visual Question Answering with Supporting Facts. - Vasiliki Kougia, John Pavlopoulos, Ion Androutsopoulos:
AUEB NLP Group at ImageCLEFmed Caption 2019. - Nguyen-Khang Le, Dieu-Hien Nguyen, Vinh-Tiep Nguyen, Minh-Triet Tran:
Lifelog Moment Retrieval with Advanced Semantic Extraction and Flexible Moment Visualization for Exploration. - Vitali Liauchuk:
ImageCLEF 2019: Projection-based CT Image Analysis for TB Severity Scoring and CT Report Generation. - Shengyan Liu, Xiaozhi Ou, Jiao Che, Xiaobing Zhou, Haiyan Ding:
An Xception-GRU Model for Visual Question Answering in the Medical Domain. - Fernando Llopis, Andrés Fuster Guilló, Jorge Azorín López, Irene Llopis:
Using improved Optical Flow Model to Detect Tuberculosis. - Sam Maksoud, Arnold Wiliem, Brian C. Lovell:
Recurrent Attention Networks for Medical Concept Prediction. - Naoya Mamada:
Image Steganalysis with Very Deep Convolutional Neural Networks. - Abdela Ahmed Mossa, Abdulkerim Mohammed Yibre, Ulus Çevik:
Multi-View CNN with MLP for Diagnosing Tuberculosis Patients Using CT Scans and Clinically Relevant Metadata. - Van-Tu Ninh, Tu-Khiem Le, Liting Zhou, Luca Piras, Michael Riegler, Mathias Lux, Minh-Triet Tran, Cathal Gurrin, Duc-Tien Dang-Nguyen:
LIFER 2.0: Discovering Personal Lifelog Insights using an Interactive Lifelog Retrieval System. - Anup Pattnaik, Sarthak Kanodia, Rahul Chowdhury, Smita Mohanty:
Predicting Tuberculosis Related Lung Deformities from CT Scan Images Using 3D CNN. - Ricardo F. Ribeiro, António J. R. Neves, José Luís Oliveira:
UA.PT Bioinformatics at ImageCLEF 2019: Lifelog Moment Retrieval based on Image Annotation and Natural Language Processing. - Kavitha S, Nandhinee P. R, Harshana S, Jahnavi Srividya S, Harrinei K:
ImageCLEF 2019: A 2D Convolutional Neural Network Approach for Severity Scoring of Lung Tuberculosis using CT Images. - S. M. Jaisakthi, Palaniappan Mirunalini, Chandrabose Aravindan:
Coral Reef Annotation and Localization using Faster R-CNN. - Lei Shi, Feifan Liu, Max P. Rosen:
Deep Multimodal Learning for Medical Visual Question Answering. - Sonit Singh, Sarvnaz Karimi, Kevin Ho-Shon, Len Hamey:
Biomedical Concept Detection in Medical Images: MQ-CSIRO at 2019 ImageCLEFmed Caption Task. - Priyanshu Sinha, Saptarshi Purkayastha, Judy Gichoya:
Full Training versus Fine Tuning for Radiology Images Concept Detection Task for the ImageCLEF 2019 Challenge. - Avi Turner, Assaf Spanier:
LSTM in VQA-Med, is It Really Needed? JCE Study on the ImageCLEF 2019 Dataset. - M. Srinivas, Akshay Nayak, Abhishek Bhatt:
Forged File Detection and Steganographic content Identification (FFDASCI) using Deep Learning Techniques. - Aljoscha Steffens, Antonio Campello, James Ravenscroft, Adrian F. Clark, Hani Hagras:
Deep Segmentation: using Deep Convolutional Networks for Coral Reef pixel-wise Parsing. - Augustus Tabarcea, Valentin Rosca, Adrian Iftene:
ImageCLEFmed Tuberculosis 2019: Predicting CT Scans Severity Scores using Stage-Wise Boosting in Low-Resource Environments. - Stefan Taubert, Stefan Kahl, Danny Kowerko, Maximilian Eibl:
Automated Lifelog Moment Retrieval based on Image Segmentation and Similarity Scores. - Abhishek Thanki, Krishnamoorthi Makkithaya:
MIT Manipal at ImageCLEF 2019 Visual Question Answering in Medical Domain. - Maxime Tournadre, Guillaume Dupont, Vincent Pauwels, Bezeid Cheikh Mohamed Lmami, Alexandru-Lucian Gînsca:
A Multimedia Modular Approach to Lifelog Moment Retrieval. - Minh H. Vu, Raphael Sznitman, Tufve Nyholm, Tommy Löfstedt:
Ensemble of Streamlined Bilinear Visual Question Answering Models for the ImageCLEF 2019 Challenge in the Medical Domain. - Xinyi Wang, Ningning Liu:
AI600 Lab at ImageCLEF 2019 Concept Detection Task. - Jing Xu, Wei Liu, Chao Liu, Yu Wang, Ying Chi, Xuansong Xie, Xian-Sheng Hua:
Concept Detection based on Multi-label Classification and Image Captioning Approach - DAMO at ImageCLEF 2019. - Xin Yan, Lin Li, Chulin Xie, Jun Xiao, Lin Gu:
Zhejiang University at ImageCLEF 2019 Visual Question Answering in the Medical Domain. - Pengfei Zhou, Cong Bai, Jie Xia:
ZJUTCVR Team at ImageCLEFlifelog2019 Lifelog Moment Retrieval Task. - Yangyang Zhou, Xin Kang, Fuji Ren:
TUA1 at ImageCLEF 2019 VQA-Med: a Classification and Generation Model based on Transfer Learning. - Hasib Zunair, Aimon Rahman, Nabeel Mohammed:
Estimating Severity from CT Scans of Tuberculosis Patients using 3D Convolutional Nets and Slice Selection.
PAN Lab on Digital Text Forensics and Stylometry
- Matti Wiegmann, Benno Stein, Martin Potthast:
Overview of the Celebrity Profiling Task at PAN 2019. - Eva Zangerle, Michael Tschuggnall, Günther Specht, Benno Stein, Martin Potthast:
Overview of the Style Change Detection Task at PAN 2019. - Francisco M. Rangel Pardo, Paolo Rosso:
Overview of the 7th Author Profiling Task at PAN 2019: Bots and Gender Profiling in Twitter. - Mike Kestemont, Efstathios Stamatatos, Enrique Manjavacas, Walter Daelemans, Martin Potthast, Benno Stein:
Overview of the Cross-domain Authorship Attribution Task at PAN 2019. - Shaina Ashraf, Omer Javed, Muhammad Adeel, Haider Iqbal, Rao Muhammad Adeel Nawab:
Bots and Gender Prediction Using Language Independent Stylometry-based Approach. - Hamed Babaei Giglou, Mostafa Rahgouy, Taher Rahgooy, Mohammad Karami Sheykhlan, Erfan Mohammadzadeh:
Author Profiling: Bot and Gender Prediction using a Multi-Aspect Ensemble Approach. - Andrea Bacciu, Massimo La Morgia, Alessandro Mei, Eugenio Nerio Nemmi, Valerio Neri, Julinda Stefa:
Bot and Gender Detection of Twitter Accounts Using Distortion and LSA. - Andrea Bacciu, Massimo La Morgia, Alessandro Mei, Eugenio Nerio Nemmi, Valerio Neri, Julinda Stefa:
Cross-Domain Authorship Attribution Combining Instance Based and Profile-Based Features. - Martijn Bartelds, Wietse de Vries:
Improving Cross-domain Authorship Attribution by Combining Lexical and Syntactic Features. - Angelo Basile:
An Open-Vocabulary Approach to Authorship Attribution. - Flora Bolonyai, Jakab Buda, Eszter Katona:
Bot Or Not: A Two-Level Approach In Author Profiling. - Rabia Bounaama, Mohammed El Amine Abderrahim:
Tlemcen University: Bots and Gender Profiling Task. - Maximilian Bryan, J. Nathanael Philipp:
Unsupervised Pretraining for Text Classification using Siamese Transfer Learning. - Andrea Cimino, Felice Dell'Orletta:
A Hierarchical Neural Network Approach for Bots and Gender Profiling. - José Eleandro Custódio, Ivandré Paraboni:
Multi-channel Open-set Cross-domain Authorship Attribution. - Rafael Felipe Sandroni Dias, Ivandré Paraboni:
Combined CNN+RNN Bot and Gender Profiling. - Daniel Yacob Espinosa, Helena Gómez-Adorno, Grigori Sidorov:
Bots and Gender Profiling using Character Bigrams. - Tiziano Fagni, Maurizio Tesconi:
Profiling Twitter Users Using Autogenerated Features Invariant to Data Distribution. - Johan Fernquist:
A Four Feature Types Approach for Detecting Bot and Gender of Twitter Users. - Michael Färber, Agon Qurdina, Lule Ahmedi:
Identifying Twitter Bots Using a Convolutional Neural Network. - Pablo Gamallo, Sattam Almatarneh:
Naive-Bayesian Classification for Bot Detection in Twitter. - Anastasia Giachanou, Bilal Ghanem:
Bot and Gender Detection using Textual and Stylistic Information. - Flurin Gishamer:
Using Hashtags and POS-Tags for Author Profiling. - Régis Goubin, Dorian Lefeuvre, Alaa Alhamzeh, Jelena Mitrovic, Elöd Egyed-Zsigmond, Leopold Ghemmogne Fossi:
Bots and Gender Profiling using a Multi-layer Architecture. - Yaakov HaCohen-Kerner, Natan Manor, Michael Goldmeier:
Bots and Gender Profiling of Tweets using Word and Character N-Grams. - Oren Halvani, Philipp Marquardt:
An Unsophisticated Neural Bots and Gender Profiling System. - Catherine Ikae, Sukunya Nath, Jacques Savoy:
UniNE at PAN-CLEF 2019: Bots and Gender Task. - Víctor Jiménez-Villar, Javier Sánchez-Junquera, Manuel Montes-y-Gómez, Luis Villaseñor Pineda, Simone Paolo Ponzetto:
Bots and Gender Profiling using Masking Techniques. - Fredrik Johansson:
Supervised Classification of Twitter Accounts Based on Textual Content of Tweets. - Fredrik Johansson, Tim Isbister:
FOI Cross-Domain Authorship Attribution for Criminal Investigations. - Youngjun Joo, Inchon Hwang:
Author Profiling on Social Media: An Ensemble Learning Approach using Various Features. - Dijana Kosmajac, Vlado Keselj:
Twitter User Profiling: Bot and Gender Identification. - György Kovács, Vanda Balogh, Purvanshi Mehta, Kumar Shridhar, Pedro Alonso, Marcus Liwicki:
Author Profiling using Semantic and Syntactic Features. - Jesus López-Santillán, Luis Carlos González-Gurrola, Manuel Montes-y-Gómez, Graciela Ramírez Alonso, Olanda Prieto-Ordaz:
An Evolutionary Approach to Build User Representations for Profiling of Bots and Humans in Twitter. - Asad Mahmood, Padmini Srinivasan:
Twitter Bots and Gender Detection using Tf-idf. - Matej Martinc, Blaz Skrlj, Senja Pollak:
Who is Hot and Who is Not? Profiling Celebs on Twitter. - Matej Martinc, Blaz Skrlj, Senja Pollak:
Fake or Not: Distinguishing between Bots, Males and Females. - Carolina Martín del Campo Rodríguez, Daniel Alejandro Pérez Alvarez, Christian Efraín Maldonado Sifuentes, Grigori Sidorov, Ildar Z. Batyrshin, Alexander F. Gelbukh:
Authorship Attribution through Punctuation n-grams and Averaged Combination of SVM. - Luis Gabriel Moreno-Sandoval, Edwin A. Puertas Del Castillo, Flor Miriam Plaza del Arco, Alexandra Pomares Quimbaya, Jorge Andrés Alvarado-Valencia, Luis Alfonso Ureña López:
Celebrity Profiling on Twitter using Sociolinguistic Features. - Lukas Muttenthaler, Gordon Lucas, Janek Amann:
Authorship Attribution in Fan-fictional Texts given Variable Length Character and Word n-grams. - Sukanya Nath:
Style Change Detection by Threshold Based and Window Merge Clustering Methods. - Rodrigo Ribeiro Oliveira, Cláudio Moisés Valiense de Andrade, José Solenir Lima Figuerêdo, João B. Rocha-Junior, Rodrigo Tripodi Calumby, Iago Machado da Conceição Silva, Almir Moreira da Silva Neto:
Bot and Gender Identification: Textual Analysis of Tweets. - Cristian Onose, Claudiu-Marcel Nedelcu, Dumitru-Clementin Cercel, Stefan Trausan-Matu:
A Hierarchical Attention Network for Bots and Gender Profiling. - Björn Pelzer:
Celebrity Profiling with Transfer Learning. - Juraj Petrík, Daniela Chudá:
Bots and Gender Profiling with Convolutional Hierarchical Recurrent Neural Network. - Juraj Petrík, Daniela Chudá:
Twitter Feeds Profiling with TF-IDF. - Juan Pizarro:
Using N-grams to detect Bots on Twitter. - Marco Polignano, Marco Giuseppe de Pinto, Pasquale Lops, Giovanni Semeraro:
Identification Of Bot Accounts In Twitter Using 2D CNNs On User-generated Contents. - Jose R. Prieto Fontcuberta, Gretel Liz De la Peña Sarracén:
Bots and Gender Profiling using a Deep Learning Approach. - Piotr Przybyla:
Detecting Bot Accounts on Twitter by Measuring Message Predictability. - Edwin A. Puertas Del Castillo, Luis Gabriel Moreno-Sandoval, Flor Miriam Plaza del Arco, Jorge Andrés Alvarado-Valencia, Alexandra Pomares Quimbaya, Luis Alfonso Ureña López:
Bots and Gender Profiling on Twitter using Sociolinguistic Features. - Victor Radivchev, Alex Nikolov, Alexandrina Lambova:
Celebrity Profiling using TF-IDF, Logistic Regression, and SVM. - Mostafa Rahgouy, Hamed Babaei Giglou, Taher Rahgooy, Mohammad Karami Sheykhlan, Erfan Mohammadzadeh:
Cross-domain Authorship Attribution: Author Identification using a Multi-Aspect Ensemble Approach. - Radarapu Rakesh, Yogesh Vishwakarma, Akkajosyula Surya Sai Gopal, Anand Kumar M:
Bot and Gender Identification from Twitter. - Usman Saeed, Farid Shirazi:
Bots and Gender Classification on Twitter. - Muhammad Hammad Fahim Siddiqui, Iqra Ameer, Alexander F. Gelbukh, Grigori Sidorov:
Bots and Gender Profiling on Twitter. - Mahendrakar Srinivasarao, Siddharth Manu:
Bots and Gender Profiling using Character and Word N-Grams. - Todor Staykovski:
Stacked Bots and Gender Prediction from Twitter Feeds. - Muhammad Usman Asif, Muhammad Naeem, Zeeshan Ramzan, Fahad Najib:
Word Distance Approach for Celebrity Profiling. - Alex I. Valencia-Valencia, Helena Gómez-Adorno, Christopher Stephens Rhodes, Gibran Fuentes Pineda:
Bots and Gender Identification Based on Stylometry of Tweet Minimal Structure and n-grams Model. - Hans van Halteren:
Bot and Gender Recognition on Tweets using Feature Count Deviations. - Hans van Halteren:
Cross-Domain Authorship Attribution with Federales. - Inna Vogel, Peter Jiang:
Bot and Gender Identification in Twitter using Word and Character N-Grams. - Chaoyuan Zuo, Yu Zhao, Ritwik Banerjee:
Style Change Detection with Feed-forward Neural Networks.
ProtestNews - Extracting Protests from News
- Ali Hürriyetoglu, Erdem Yörük, Deniz Yuret, Çagri Yoltar, Burak Gürel, Firat Durusan, Osman Mutlu, Arda Akdemir:
Overview of CLEF 2019 Lab ProtestNews: Extracting Protests from News in a Cross-context setting. - Erkan Basar, Simge Ekiz, Antal van den Bosch:
A Comparative Study on Generalizability of Information Extraction Models on Protest News. - Angelo Basile, Tommaso Caselli:
ProTestA: Identifying and Extracting Protest Events in News Notebook for ProtestNews Lab at CLEF 2019. - Chedi Bechikh Ali:
Linguistic Parameters and Word Embeddings for Protest News Detection in Text. - Elizaveta Maslennikova:
ELMo Word Representations For News Protection. - Anaïs Ollagnier, Hywel T. P. Williams:
Classification and Event Identification Using Word Embedding. - Benjamin J. Radford:
Multitask Models for Supervised Protest Detection in Texts. - Ali Safaya:
Event Sentence Detection Task Using Attention Model. - Gabriella Skitalinskaya, Jonas Klaff, Maximilian Spliethöver:
CLEF ProtestNews Lab 2019: Contextualized Word Embeddings for Event Sentence Detection and Event Extraction. - D. Thenmozhi, Chandrabose Aravindan, Abishek Shyamsunder, Adithya Viswanathan, Akash Kumar Pujari:
Extracting Protests from News Using LSTM models with different Attention Mechanisms.
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