- Descriptive knowledge about the information overload problem, the differences between information and contents and the flows of content. - Skills to use indexing techniques in text, audio, speech, image and video. - Skills to model Information Retrieval and Filtering techniques.

The modern information overload problem caused by the availability of enormous amounts of information through internet makes it necessary to design systems that allow us to find the information we search and filter or personalize the information according to our needs. For that matter it is fundamental to be able to automatically index not only textual contents but also audio (music, speech, etc.), image or video, using methods based on the content or even collaborative tagging as the one taking place in social networks. Examples of these multimedia management systems are Google search (and all its variants as Google Image, Google Goggles, etc.), recommender systems and user profilers like those available in Amazon, etc. Topic 1. Introduction to text processing for information retrieval Topic 2. Feature extraction techniques for speech, audio, image and video indexing Topic 3. Modeling of information retrieval tasks Topic 4. Recommender systems, user profiling and content filtering

The following learning activities and methodologies are combined: - Theory classes - Guided lab assignments - Research papers' preseentations - Final project Teachers are available during 2 hours per week for office hours.