The conference will have two internationally renowned keynote speakers: Hugo Zaragoza and Henning Müller.

Hugo Zaragoza

Hugo Zaragoza leads the Natural Language Retrieval group in Barcelona. He is interested in the applications of machine learning (ML) and natural language processing (NLP) for information retrieval (IR), Web search, and information access in general. From 2001 to 2006, Hugo worked at Microsoft Research (Cambridge, UK) with Stephen Robertson, mostly on probabilistic ranking methods for corporate and web search, but also on document classification, expert finding, relevance feedback, and dialogue generation for games. He also collaborated with Microsoft product groups MSN-Search and SharePoint Portal Server.

Lecture

Title: Descriptive Statistics for Informational Search Results

Abstract

In transactional or navigational searches a user is typically interesting in carrying out an action or reaching a destination. For this reason it does not matter that a query returns hundreds or millions of results: the user just needs to choose a few from "the top". However, in typical informational searches the user is interesting in gaining an "overall picture" of the "most important" aspects of the topic. Today, this forces the user to read very many of the documents. Finding the right descriptive statistics of the result set should help the user gain an overall understanding of the data, but this remains an open problem of NLP and IR.

In my talk I will review some of the work done in this area at the Yahoo! Research Barcelona lab, in the domains of Q&A and News search. Interestingly, we will show that some "deep" NLP techniques such as semantic role labeling can be used effectively to surface structures useful to the user.

Henning Müller

Henning Müller is a teacher at the University of Applied Sciences Western Switzerland (Switzerland) and the University Hospitals and University of Geneva (Switzerland). His research interests focus on visual information retrieval based on content, the interaction in information retrieval, evaluation of retrieval systems, medical image analysis and, in general, medical informatics. Previously, from 2002 to 2008 he was a teacher and postdoctoral researcher in the Department of Medical Informatics at the University of Geneva. He has authored nearly 300 publications and has participated in numerous research projects with local and international funding.

Lecture

Title: Using textual and visual information for the retrieval of images

Abstract
Images play an increasingly important role in many domains, from publishing to medicine and most of us have also large personal archives of images. Search for images is on the other much less explored than textual search. Image search has different characteristics from text search as the content can not easily be described with words in some cases and there is much subjectivity in describing images. Content-based visual retrieval extract visual features to represent the images and allows for search based on visual information and text. Both text and visual information also allow extracting some semantic information on the images. All this is fairly complementary and combined it can lead to good retrieval results. This talk will present some results of the ImageCLEF benchmark on image retrieval that also includes aspects of multi-lingual information access.