Data Science Eurecat creates, tests and demonstrates technologies and algorithms beyond the state of the art, for analyzing data that are too large, too fast or too complex for existing solutions.
Areas of Specialitzation
Data Mining and Machine learning:
Classification and clustering
Influence and reputation
Algorithms for large-scale data:
Data streams and real-time methods
Large-scale machine learning
Distributed search engines
User behavior mining:
User engagement analysis
Correlating the online world with offline metrics
The Data Science team includes people who have worked with data from the following domains:
Web | Social Media | News | Advertising and Marketing | Finance | Disasters and time-critical events | Biomedical and biology
Examine any algorithm that generates suggestions based on data from people, and ensure that the algorithm does not inadvertently discriminate against any minority or protected group.
Process any dataset containing personal and/or private data, and convert into an anonymized, sanitized dataset in which there is a provable guarantee of impossibility of identifying individuals.
Analyze any type of behavioral data about interactions of people and content online, measure the engagement of users with the content, and provide ways of boosting this engagement.
Study ans social network to determine who are the influentials and leaders on a given topic, what are the communities, and what is the reputation of different nodes. in collaboration with Digital Humanities.
Process any corpus of text or documents to automatically categorize, extract, score, measure and find content.
Analyze any type of data, in batch or in real-time, for tasks such as categorizing, clustering, finding patterns, detecting anomalies, filtering, or creating recommendations.
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