BIE-VWM – Searching Web and Multimedia Databases


Students gain basic knowledge concerning retrieval techniques on the web, where the web environment is viewed as a large distributed and heterogenous data repository. In particular, the students will understand the techniques for retrieving text and hypertext documents (the web pages). Moreover, they will be aware of similarity retrieval methods focused on heterogenous multimedia databases (unstructured data collections, respectively).

Lecture Program

  1. Introduction. Web infrastructure. Data distribution on the web. Web document types. Web retrieval modalities.
  2. Text retrieval - Boolean model. Implementation.
  3. Text retrieval - Vector model. Implementation.
  4. Hypertext retrieval. Hypertext ranking.
  5. Search engine optimization.
  6. Semantic web. Implementation.
  7. Recommender systems. Collaborative filtering.
  8. Multimedia databases. Text-based multimedia retrieval.
  9. Similarity as a model for content-based retrieval. Feature extraction from multimedia documents.
  10. Similarity queries and their integration into SQL.
  11. Indexing metric similarity for efficient multimedia retrieval.
  12. Approximate similarity retrieval.
  13. Advanced models - nonmetric similarities, dynamic similarities & queries, etc.

Labs Program

  1. Boolean model.
  2. Vector model.
  3. Hypertext search.
  4. Recommender systems.
  5. Similarity queries.
  6. Metric indexing.
  7. Approximate retrieval.

Last modified: 7.9.2010, 11:06