Guest lecture by Professor Vijay Raghavan

Lecturer : 
Vijay V. Raghavan
Event type: 
Guest lecture
Event time: 
2017-05-26 10:15 to 11:00
Place: 
Exactum D123, Kumpula
Description: 

Time: Friday, May 26th at 10:15-11:00  (Coffee available at 10:00)
Place: Kumpula, Exactum D123.

Speaker: 
Vijay V. Raghavan
School of Computing and Informatics
University of Louisiana at Lafayette, USA

Title: A Framework for Real-Time Event Detection for Emergency Situations using Social Media Streams

Abstract:

In this presentation, we propose an event detection approach to aid in real-time event detection. Social media generates information about news and events in real-time. Given the vast amount of data available and the rate of information propagation, reliably identifying events can be a challenge. Most state of the art techniques are post hoc techniques, which detect an event after it happened. Our goal is to detect the onset of an event as it is happening, using the user-generated information from Twitter streams. To achieve this goal, we use a discriminative model to identify a sudden change in the pattern of conversations over time. We also use a topic evolution model to identify credible events and propose an approach to eliminate random noise that is prevalent in many of the existing topic detection approaches. The simplicity of our proposed approach allows us to perform fast and efficient event detection, permitting discovery of events within minutes of the first conversation relating to an event started. We also show that this approach is applicable for other social media datasets to detect change over the longer periods of time.

We extend the proposed event detection approach to incorporate information from multiple data sources with different velocity and volume. We study the event clusters generated from event detection approach for changes in events over time. We also propose and evaluate a location detection approach to identify the location of a user or an event based on tweets related to them.

Bio:

Dr. Vijay Raghavan is the Alfred and Helen Lamson/ BoRSF Endowed Professor in Computer Science at the Center for Advanced Computer Studies and the Director of the NSF-sponsored Industry/ University Cooperative Research Center for Visual and Decision Informatics. As the director, he co-ordinates several multi-institutional, industry-driven research projects and manages a budget of over $750K/year. His research interests are in data mining, information retrieval, machine learning and Internet computing. He has published over 275 peer-reviewed research papers- appearing in top-level journals and proceedings- that cumulatively accord him an h-index of 35, based on citations at Google Scholar. He has served as major advisor for 29 doctoral students. Besides substantial technical expertise, Dr. Raghavan has vast experience managing interdisciplinary and multi- institutional collaborative projects. He has also directed industry-sponsored research, on projects pertaining to Neuro-imaging based dementia detection and Literature-based biomedical hypotheses generation, respectively, for GE Healthcare and Araicom Research L.L.C.

He received the IEEE International Conference on Data Mining (ICDM) 2005 Outstanding Service Award. Dr. Raghavan serves as a member of the Executive Committee of the IEEE Technical Committee on Intelligent Informatics (IEEE-TCII), the Web Intelligence Consortium (WIC) Technical Committee and the Web Intelligence and Intelligent Agent Technology Conferences’ Steering Committee. He was one of the Conference Co-Chairs of IEEE 2013 Big Data Conference, its inaugural edition. For many years of service to the community, he received the WIC 2013 Outstanding Service Award. He was a member of the Steering Committee of IEEE BigData 2014 and 2015 conferences held at Washington, D.C. and Santa Clara, CA, respectively. He is one of the Editors-in-Chief of the Web Intelligence journal, an Associate Editor of the ACM Transactions on Internet Technology and the Elsevier Journal of King Saud University - Computer and Information Sciences, and a member of the International Rough Set Society Advisory Board. He is an ACM Distinguished Scientist and served as an ACM Distinguished Lecturer from 1993 - 2006. In addition, he served as a member of the Advisory Committee of the NSF Computer and Information Science and Engineering directorate (CISE-AC) during 2008 - 2010.

Welcome! 

Machine Learning Coffee seminar "Machine Learning for Image-Based Localization"

Lecturer : 
Juho Kannala, Professor of Computer Science, Aalto University
Event type: 
Event
Doctoral dissertation
Respondent: 
Opponent: 
Custos: 
Event time: 
2017-05-15 09:15
Place: 
Seminar room T5, CS building, Konemiehentie 2, Otaniemi
Description: 

Machine Learning Coffee seminars are weekly seminars held jointly by the Aalto University and the University of Helsinki. The seminars aim to gather people from different fields of science with interest in machine learning. Seminars will be held on Mondays at 9 am at Aalto University and the University of Helsinki every other week. At Aalto University, talks will be held in Konemiehentie 2, seminar room T5 and at the University of Helsinki in Kumpula, seminar room D123, unless otherwise noted. Talks will begin at 9:15 am and porridge and coffee will be served from 9:00 am.

Welcome!

Machine Learning Coffee seminar "Empirical Parameterization of Exploratory Search Systems Based on Bandit Algorithms"

Lecturer : 
Dorota Glowacka, Department of Computer Science, University of Helsinki
Event type: 
Event
Doctoral dissertation
Respondent: 
Opponent: 
Custos: 
Event time: 
2017-05-08 09:15 to 10:00
Place: 
seminar room Exactum D123, Kumpula
Description: 

Machine Learning Coffee seminars are weekly seminars held jointly by the Aalto University and the University of Helsinki. The seminars aim to gather people from different fields of science with interest in machine learning. Seminars will be held on Mondays at 9 am at Aalto University and the University of Helsinki every other week. At Aalto University, talks will be held in Konemiehentie 2, seminar room T5 and at the University of Helsinki in Kumpula, seminar room D123, unless otherwise noted. Talks will begin at 9:15 am and porridge and coffee will be served from 9:00 am.

Welcome!

Machine Learning Coffee seminar: Nintendo Wii Fit-Based Balance Testing to Detect Sleep Deprivation: Approximate Bayesian Computation Approach

Lecturer : 
Aino Tietäväinen
Event type: 
Event
Doctoral dissertation
Respondent: 
Opponent: 
Custos: 
Event time: 
2017-04-24 09:15 to 10:00
Place: 
Seminar room T5, CS building, Konemiehentie 2, Otaniemi
Description: 

Machine Learning Coffee seminars are weekly seminars held jointly by the Aalto University and the University of Helsinki. The seminars aim to gather people from different fields of science with interest in machine learning. Seminars will be held on Mondays at 9 am at Aalto University and the University of Helsinki every other week. At Aalto University, talks will be held in Konemiehentie 2, seminar room T5 and at the University of Helsinki in Kumpula, seminar room D123, unless otherwise noted. Talks will begin at 9:15 am and porridge and coffee will be served from 9:00 am.

Welcome!

 

Doctoral dissertation: Advances in Analysing Temporal Data

Lecturer : 
Orestis Kostakis
Event type: 
Doctoral dissertation
Doctoral dissertation
Respondent: 
Orestis Kostakis
Opponent: 
Professor Joao Gama, University of Porto, Portugal
Custos: 
Professor Aristides Gionis, Aalto University School of Science, Department of Computer Science
Event time: 
2017-05-26 12:00 to 15:00
Place: 
lecture hall T2, Konemiehentie 2, Espoo

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