Personal Information
Entreprise/Lieu de travail
London, United Kingdom United Kingdom
Profession
Research Scientist at Yahoo
Secteur d’activité
Education
Site Web
www.micheletrevisiol.com
À propos
I hold a PhD in Computer Science, and MS and BS in Computer Engineering.
My background includes Data Mining/Web Mining, Multimedia and Information Retrieval, User Modeling, Recommendation Systems and Online Computational Advertising.
I have vastly worked with large data collections such as Flickr, Yahoo News, Yahoo Query and Web logs, and as well on Twitter data. I have also done various researches on credit card user's transactions, Sentiment Analysis with Yahoo and Yelp data, and geographic localization of images and videos.
My specialities are Apache Hadoop/PIG, Java, Python and R.
But I also like to make websites playing with HTML5, Javascript and CSS.
Mots-clés
flickr
oral talk
domain-specific browsing graphs
sigir
browsegraph
pagerank
local ranking problem
graphs
centrality algorithms
user browsing behavior; recommendation system; imp
urbanbeers
prezi
bbva challenge
placing task
location
geotags
video annotation
image ranking
social browsing
browserank
Tout plus
Présentations
(3)J’aime
(18)Deploying Machine Learning Models to Production
Anass Bensrhir - Senior Data Scientist
•
il y a 6 ans
Learning to Rank in Solr: Presented by Michael Nilsson & Diego Ceccarelli, Bloomberg LP
Lucidworks
•
il y a 8 ans
Past present and future of Recommender Systems: an Industry Perspective
Xavier Amatriain
•
il y a 7 ans
Like Partying? Your Face Says It All. Predicting Place AMBIANCE From Profile Pictures
Daniele Quercia
•
il y a 8 ans
Random Forests R vs Python by Linda Uruchurtu
PyData
•
il y a 10 ans
Kdd 2014 Tutorial - the recommender problem revisited
Xavier Amatriain
•
il y a 9 ans
Recommender Systems (Machine Learning Summer School 2014 @ CMU)
Xavier Amatriain
•
il y a 9 ans
Recommender Systems, Matrices and Graphs
Roelof Pieters
•
il y a 9 ans
Intro to Machine Learning by Microsoft Ventures
microsoftventures
•
il y a 10 ans
Data Workflows for Machine Learning - Seattle DAML
Paco Nathan
•
il y a 10 ans
Implicit Feedback Recommendation via Implicit-to-Explicit Ordinal Logistic Regression Mapping
Denis Parra Santander
•
il y a 12 ans
Diversità per Recommender Systems
Paolo Tomeo
•
il y a 10 ans
Penguins in Sweaters, or Serendipitous Entity Search on User-generated Content
Mounia Lalmas-Roelleke
•
il y a 10 ans
Top-N Recommendations from Implicit Feedback leveraging Linked Open Data
Vito Ostuni
•
il y a 10 ans
Learning to Rank for Recommender Systems - ACM RecSys 2013 tutorial
Alexandros Karatzoglou
•
il y a 10 ans
Tutorial on People Recommendations in Social Networks - ACM RecSys 2013,Hong Kong
Anmol Bhasin
•
il y a 10 ans
Finding News Curators in Twitter
Janette Lehmann
•
il y a 10 ans
Dear NSA, let me take care of your slides.
Emiland
•
il y a 10 ans
Personal Information
Entreprise/Lieu de travail
London, United Kingdom United Kingdom
Profession
Research Scientist at Yahoo
Secteur d’activité
Education
Site Web
www.micheletrevisiol.com
À propos
I hold a PhD in Computer Science, and MS and BS in Computer Engineering.
My background includes Data Mining/Web Mining, Multimedia and Information Retrieval, User Modeling, Recommendation Systems and Online Computational Advertising.
I have vastly worked with large data collections such as Flickr, Yahoo News, Yahoo Query and Web logs, and as well on Twitter data. I have also done various researches on credit card user's transactions, Sentiment Analysis with Yahoo and Yelp data, and geographic localization of images and videos.
My specialities are Apache Hadoop/PIG, Java, Python and R.
But I also like to make websites playing with HTML5, Javascript and CSS.
Mots-clés
flickr
oral talk
domain-specific browsing graphs
sigir
browsegraph
pagerank
local ranking problem
graphs
centrality algorithms
user browsing behavior; recommendation system; imp
urbanbeers
prezi
bbva challenge
placing task
location
geotags
video annotation
image ranking
social browsing
browserank
Tout plus