| Abstract: |
The Web is the largest public big data repository that humankind hascreated. In this overwhelming data ocean, we need to be aware of thequality and, in particular, of the biases that exist in this data. Inthe Web, biases also come from redundancy and spam, as well as fromalgorithms that we design to improve the user experience. This problemis further exacerbated by biases that are added by these algorithms,specially in the context of search and recommendation systems. Theyinclude selection and presentation bias in many forms, interaction bias,social bias, etc. We give several examples and their relation to sparsityand privacy, stressing the importance of the user context to avoid thesebiases. |
| Biography: |
Ricardo Baeza-Yates areas of expertise are web search and data mining,information retrieval, data science and algorithms. He is CTO of NTENT, a semantic search technology company. Before he was VP of Research at Yahoo Labs, based in Barcelona, Spain, and later in Sunnyvale, California, from January 2006 to February 2016. He also is part time Professor at DTIC of the Universitat Pompeu Fabra, in Barcelona, Spain, as well as at DCC of Universidad de Chile in Santiago. Until 2004 he was Professor and founding director of the Center for Web Research at the later place. He obtained a Ph.D. in CS from the University of Waterloo, Canada, in 1989. He is co-author of the best-seller Modern Information Retrieval textbook published by Addison-Wesley in 2011 (2nd ed), that won the ASIST 2012 Book of the Year award. From 2002 to 2004 he was elected to the board of governors of the IEEE Computer Society and in 2012 he was elected for the ACM Council. Since 2010 is a founding member of the Chilean Academy of Engineering. In 2009 he was named ACM Fellow and in 2011 IEEE Fellow, among other awards and distinctions. |
