Prof. Vincenzo Piuri
University of Milan, Italy
Title: To be announced
Abstract: To be announced
Short Biography: Vincenzo Piuri is Full Professor at the University of Milan, Italy (since 2000), where he was also Department Chair (2007-2012). He was Associate Professor at Politecnico di Milano, Italy (1992-2000), visiting professor at the University of Texas at Austin, USA (summers 1996-1999), and visiting researcher at George Mason University, USA (summers 2012-2016).
He founded a start-up company, Sensure srl, in the area of intelligent systems for industrial applications (leading it from 2007 until 2010) and was active in industrial research projects with several companies.
He received his M.S. and Ph.D. in Computer Engineering from Politecnico di Milano, Italy.
His main research and industrial application interests are: intelligent systems, computational intelligence, pattern analysis and recognition, machine learning, signal and image processing, biometrics, intelligent measurement systems, industrial applications, distributed processing systems, internet-of-things, cloud computing, fault tolerance, application-specific digital processing architectures, and arithmetic architectures. His research was performed in national and European projects funded by industries, the European Union, the Italian Ministry of Research, and the National Research Council of Italy. He published innovative results in more than 400 papers in international journals, international conference proceedings, books, and book chapters.
Prof. Michalis Vazirgiannis
(DASCIM), LIX, Ecole Polytechnique, Palaiseau, France
Title: "Graph-of-word: boosting text mining with graphs"
Abstract: The Bag-of-words model has been the dominant approach for IR and Text mining for many years assuming the word independence and the frequencies as the main elements for feature selection and query to document similarity computation. Although the long and successful usage, bag-of-words ignores words' order and distance within the document – weakening thus the expressive power of the distance metrics. We propose graph-of-word, an alternative approach that capitalizes on a graph representation of documents and challenges the word independence assumption by taking into account words' order and distance. We applied graph-of-word in various tasks such as ad-hoc Information Retrieval, Single-Document Keyword Extraction, Text Categorization and Sub-event Detection in Textual Streams. In all cases the graph of word approach, assisted by graph degeneracy at times, outperforms the state of the art base lines.
Short Biography: Dr. Vazirgiannis is a Professor at LIX, Ecole Polytechnique in France.
He holds a degree in Physics and a PhD in Informatics from Athens University(Greece) and a Master degree in AI from HerioWatt Univ Edinburgh. He has conducted research in GMD-IPSI, Max Planck MPI (Germany), in INRIA/FUTURS (Paris). He has been a teaching in AUEB (Greece), Ecole Polytechnique, Telecom-Paristech, ENS (France), Tsinghua, Jiaotong Shanghai (China) and in Deusto University (Spain).
His current research interests are on machine learning and combinatorial methods for Graph analysis (including community detection, graph clustering and embeddings, influence maximization), Text mining including Graph of Words, word embeddings with applications to web advertising and marketing, event detection and summarization. He has active cooperation with industrial partners in the area of data analytics and machine learning for large scale data repositories in different application domains. He has supervised fifteen completed PhD theses. He has published three books and more than a 150 papers in international refereed journals and conferences.
He has organized large scale conferences in the area of Data Mining and Machine Learning (such as ECML/PKDD) while he participates in the senior PC of AI and ML conferences – such as AAAI and IJCAI, He has received the ERCIM and the Marie Curie EU fellowships and since 2015 he leads the AXA Data Science chair.
Dr Yiannis Kompatsiaris
Multimedia, Knowledge and Social Media Analytics Lab, Information Technologies Institute, Greece
Title: "Media Analytics for Fake News Detection: Content, Context and Social approaches"
Abstract: The publication and spread of misleading content is a problem of increasing magnitude, complexity and consequences in a world that is increasingly relying on user-generated content for news sourcing. To this end, media analysis techniques could serve as an assisting tool to spot and debunk misleading content on the Web. The objective of this talk is to present various approaches towards content verification, starting with semi-supervised misleading multimedia content detection on Twitter in real time. Image splicing detection on the Web and on images disseminated through social media will follow next. Contextual information will be examined for verifying Web videos by analyzing their online context such as comments, description, likes/dislikes and uploader information.
Finally, social features will be presented in a framework that combines community detection with key-player identification to retrieve communities who share specific type of information with a case study in terrorism related content.
Short Biography: Dr. Ioannis (Yiannis) Kompatsiaris is a Senior Researcher (Researcher A') with the Information Technologies Institute / Centre for Research and Technology Hellas and the Head of the Multimedia Knowledge and Social Media Analytics Laboratory. His research interests include semantic multimedia analysis, indexing and retrieval, social media and big data analysis, knowledge structures, reasoning and personalization for multimedia applications, eHealth, security and environmental applications. He received his Ph.D. degree in 3-D model based image sequence coding from the Aristotle University of Thessaloniki in 2001.
He is the co-author of 129 papers in refereed journals, 46 book chapters, 8 patents and more than 420 papers in international conferences. He has been the co-organizer of various international conferences and workshops and has served as a regular reviewer, associate and guest editor for a number of journals and conferences.
He is a Senior Member of IEEE and member of ACM.