Personal Information
Organization / Workplace
London, United Kingdom United Kingdom
Occupation
Research Scientist at Yahoo
Industry
Education
Website
www.micheletrevisiol.com
About
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.
Tags
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
See more
- Presentations
- Documents
- Infographics
Dear NSA, let me take care of your slides.
Emiland
•
10 years ago
Recommender Systems (Machine Learning Summer School 2014 @ CMU)
Xavier Amatriain
•
9 years ago
Kdd 2014 Tutorial - the recommender problem revisited
Xavier Amatriain
•
9 years ago
Learning to Rank for Recommender Systems - ACM RecSys 2013 tutorial
Alexandros Karatzoglou
•
10 years ago
Data Workflows for Machine Learning - Seattle DAML
Paco Nathan
•
10 years ago
Learning to Rank in Solr: Presented by Michael Nilsson & Diego Ceccarelli, Bloomberg LP
Lucidworks
•
8 years ago
Random Forests R vs Python by Linda Uruchurtu
PyData
•
10 years ago
Deploying Machine Learning Models to Production
Anass Bensrhir - Senior Data Scientist
•
7 years ago
Tutorial on People Recommendations in Social Networks - ACM RecSys 2013,Hong Kong
Anmol Bhasin
•
10 years ago
Recommender Systems, Matrices and Graphs
Roelof Pieters
•
9 years ago
Past present and future of Recommender Systems: an Industry Perspective
Xavier Amatriain
•
7 years ago
Like Partying? Your Face Says It All. Predicting Place AMBIANCE From Profile Pictures
Daniele Quercia
•
8 years ago
Penguins in Sweaters, or Serendipitous Entity Search on User-generated Content
Mounia Lalmas-Roelleke
•
10 years ago
Finding News Curators in Twitter
Janette Lehmann
•
11 years ago
Intro to Machine Learning by Microsoft Ventures
microsoftventures
•
10 years ago
Top-N Recommendations from Implicit Feedback leveraging Linked Open Data
Vito Ostuni
•
10 years ago
Implicit Feedback Recommendation via Implicit-to-Explicit Ordinal Logistic Regression Mapping
Denis Parra Santander
•
12 years ago
Diversità per Recommender Systems
Paolo Tomeo
•
10 years ago