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VERSION:2.0
PRODID:-//Memento EPFL//
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SUMMARY:Supporting cognitive operations on Big Data
DTSTART:20161220T110000
DTEND:20161220T120000
DTSTAMP:20260410T074448Z
UID:26ff6b69885176124a8ef76ee687db3cee3352e01aee43ffca86e364
CATEGORIES:Conferences - Seminars
DESCRIPTION:Dr. Michalis Vlachos\, IBM\nBig Data can provide useful insigh
 ts but they also overwhelm the data users. In this talk\, I will describe 
 three basic directions to mitigate the negative effects that frequently ac
 company the handling of Big Data. First\, I will describe some novel techn
 iques for effectively performing mining operations directly on compressed 
 data.  Then\, I will describe how interpretable recommendations technolog
 ies can provide a solution to the problem of information overload. Finally
 \, I will conclude with ways of querying large structured and unstructured
  datasets using a Natural Language paradigm.\n\nBio: Michalis Vlachos is a
  member of the Cognitive Systems group at IBM Zurich Research. His interes
 ts are in the areas of data mining\, recommender systems and information r
 etrieval. He has published more than 80 scientific articles in the above a
 reas and his work has been cited more than 4000 times. His research has be
 en supported by a Fulbright scholarship\, a Marie-Curie Fellowship and an 
 ERC Starting grant on the topic of “Exact Mining from InExact Data”.\n
 \nhttps://ch.linkedin.com/in/michalis-vlachos-ba2544116\n 
LOCATION:BC 420 https://plan.epfl.ch/?room==BC%20420
STATUS:CONFIRMED
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