Ricardo Campos is an assistant professor at the ICT Departmental Unit of the Polytechnic Institute of Tomar (IPT) and member of LIAAD-INESC TEC, the Artificial Intelligence and Decision Support Lab of U. Porto. He is PhD in Computer Science by the University of Porto (U. Porto). His PhD on temporal information retrieval led him to win the Fraunhofer Portugal Challenge 2013 and to be distinguished as an “outstanding” researcher by the INESC TEC research lab. He has over 10 years of research experience in Information Retrieval and Text Mining. In 2018, he has been awarded the best short paper award at ECIR'18 for the paper entitled "A Text Feature Based Automatic Keyword Extraction Method for Single Documents" and the 1st prize of the Arquivo.pt Award for the project Conta-me Histórias ( http://contamehistorias.pt; http://tellmestories.pt). In 2019 he has been awarded the Best Demo Paper at ECIR'19 for the paper entitled “Interactive System for Automatically Generating Temporal Narratives”, and the Recognized Reviewer Award for his reviews as a PC member of ECIR'19. He is an editorial board member of the Information Processing & Management Journal (Elsevier), co-chaired international conferences and workshops, being also a program committee member of several international conferences. More in http://www.ccc.ipt.pt/~ricardo
Vítor Mangaravite is a research intern of LIAAD/INESC TEC - INESC Technology. He has MSc and BSc in Computer Science by Universidade Federal de Minas Gerais and Universidade Federal de Ouro Preto, respectively. His research interests are Information Retrieval and Text Mining, in particular, ranking modeling, focused crawler, and information-theoretic in document-entity associations. He was the local committee member of the World Wide Web Conference (2013), the Latin American Web Congress (2014) and the International Symposium on String Processing and Information Retrieval (2014).
Arian Pasquali is a researcher associated to University of Porto and the Artificial Intelligence and Decision Support Laboratory at INESC TEC - INESC Technology. He has MSc in Computer Science by University of Porto with specialization in data mining. He has published research in the fields of IR, having been awarded the best short paper award at ECIR'18 (40th International Conference on Information Retrieval). He has also been awarded the 1st prize of the Arquivo.pt Award in 2018 for his project Conta-me Histórias (http://contamehistorias. pt), a project in the field of temporal summarization and web archives. Currently his research interests involve machine learning applied to text mining, in particular information retrieval and natural language processing.
More in http://www.dcc.fc.up.pt/~apasquali
Alípio M. Jorge is an associate professor at the Department of Computer Science of the Faculty of Science of the U. Porto and the coordinator of LIAAD/INESC TEC - INESC Technology and cid:8DEFB44D-C005-43C9-8B8C-4FB2D7BB0C54@homeScience, the Artificial Intelligence and Decision Support Lab of U. Porto since 2012. He is PhD in Computer Science by U. Porto. His research interests are Data Mining and Machine Learning, in particular association rules, web intelligence and recommender systems. He lectures on information processing and data mining. He launched the MSc. on Data Analysis and Decision Support Systems, which he coordinated from 2000 to April 2008. He leads research projects on data mining and web intelligence. He co-chaired international conferences (Discovery Science 2009, ECML/PKDD 15 and EPIA 01), workshops and seminars in data mining and artificial intelligence. He was Vice-President of the Portuguese Association for Artificial Intelligence. More in http://www.dcc.fc.up.pt/~amjorge
Célia Nunes is an Assistant Professor at the Department of Mathematics of the University of Beira Interior (UBI) and member of CMA - Center of Mathematics and Aplications, UBI. She is PhD in Mathematics by UBI, MSc. on Applied Mathematics by the University of Évora (UE) and BSc. in Mathematics - Probability and Statistics (UE). Her research interests are in Applied Mathematics and Probability and Statistics, in particular Statistical Inference in Linear Models. She has published research in the fields of Probability and Statistics and Applied Statistics and has been awarded two best paper awards: - Best Paper Award at the 5th International Conference on Applied Mathematics, Simulation, Modelling (ASM '11) for the paper entitled "Orthogonal Fixed Effects ANOVA with Random Sample Sizes"; - Best Short Paper Award at the 40th European Conference on Information Retrieval (ECIR'18) for the paper entitled "A Text Feature Based Automatic Keyword Extraction Method for Single Documents". She is also a guest reviewer of several international journals, co-chaired multiple international conferences and workshops, being also a scientific committee member of international conferences. More in http://www.mat.ubi.pt/~celia/
Adam Jatowt is an Associate Professor at the Department of Computer Science, University of Innsbruck. He has received his Ph.D. in Information Science and Technology from the University of Tokyo, Japan in 2005. After completing his PhD, he worked for a year as a postdoctoral researcher at National Institute of Information and Communications Technology (NICT). His has research interests in an area of information retrieval, knowledge extraction from text and in digital history. Adam has been serving as a PC co-chair of IPRES2011, SocInfo2013, ICADL2014 and JCDL2017 conferences as well as a demo/poster co-chair of TPDL2016 and tutorial co-chair of SIGIR2017. He was also a co-organizer of three NTCIR evaluation tasks. More in https://adammo12.github.io/adamjatowt/
Please cite the following works when using YAKE.
In-depth journal paper at Information Sciences Journal:
Campos, R., Mangaravite, V., Pasquali, A., Jatowt, A., Jorge, A., Nunes, C. and Jatowt, A. (2020). YAKE! Keyword Extraction from Single Documents using Multiple Local Features. In Information Sciences Journal. Elsevier, Vol 509, pp 257-289
Best Short Paper Award at ECIR’18:
Campos, R., & Mangaravite, V., & Pasquali, A., & Jorge, A., & Nunes, C., & Jatowt, A. (2018). A Text Feature Based Automatic Keyword Extraction Method for Single Documents. In Gabriella Pasi et al. (Eds.), Lecture Notes in Computer Science - Advances in Information Retrieval - 40th European Conference on Information Retrieval (ECIR'18). Grenoble, France. March 26 – 29. (Vol. 10772(2018), pp. 684 - 691). *
Demo paper at ECIR’18:
Campos, R., & Mangaravite, V., & Pasquali, A., & Jorge, A., & Nunes, C., & Jatowt, A. (2018). YAKE! Collection-independent Automatic Keyword Extractor. In Gabriella Pasi et al. (Eds.), Lecture Notes in Computer Science - Advances in Information Retrieval - 40th European Conference on Information Retrieval (ECIR'18). Grenoble, France. March 26 – 29. (Vol. 10772(2018), pp. 806 - 810).
Project "TEC4Growth - Pervasive Intelligence, Enhancers and Proofs of Concept with Industrial Impact/NORTE-01-0145-FEDER-000020" is financed by the North Portugal Regional Operational Programme (NORTE 2020), under the PORTUGAL 2020 Partnership Agreement, and through the European Regional Development Fund (ERDF).