The Web and Media Search Lab focuses on modern social-media information retrieval problems and applied machine learning methods.
Current challenges in search and mining applications are deeply related to the heterogeneity of data and the size of data repositories. At one end we have rich information obtained from many heterogeneous sources such as Web, image and text data. At the other end there’s social media data generated by users such as tags, clicks, comments and queries, that can assist algorithms at better processing and understanding information and information needs. Thus, Big Data demands for new machine learning and data storage approaches capable of efficiently processing, accessing and locating large data repositories.
Our current research topics are:
- Image and video semantic annotation and retrieval
- Scalable indexing and retrieval of large-scale media data
- Social-media analysis for temporal search and recommender systems
Find more information about the on-going research in the Projects page.