This demonstrator showcases the PuppyIR framework by incorporating numerous child specific components developed as part of the PuppyIR project. The Demonstrator is for Emma’s Children’s Hospital in Amsterdam and provides children with a novel and exciting interface to help support their information needs while in hospital or visiting the hospital.
EmSe will be demonstrated at the 34th European Conference on Information Retrieval (ECIR) in Barcelona on 1-5 April 2012
Today on Radio 1: An interview by Deborah Blekkenhorst on our attempts to search the deep web. And… no, the deep web is not the part of the web where terrorists hang out. (in Dutch)
Dutch broadcaster BNN tests the intuitive train planner developed at the Database Group. Their verdict: “ingenious”, and “approved for elderly”. Picture of Kien Tjin-Kam-Jet proudly in the back (in Dutch). See the treinplanner in action at: http://treinplanner.info
Score Region Algebra: A flexible framework for structured information retrieval
by Vojkan Mihajlovic
The scope of the research presented in this thesis is the retrieval of relevant information from structured documents. The thesis describes a framework for information retrieval in documents that have some form of annotation used for describing logical and semantical document structure, such as XML and SGML. The development of the structured information retrieval framework follows the ideas from both database and information retrieval worlds. It uses a three-level database architecture and implements relevance scoring mechanisms inherited from information retrieval models.
To develop the structured retrieval framework, the problem of structured information retrieval is analyzed and elementary requirements for structured retrieval systems are specified. These requirements are: (1) entity selection – the selection of different entities in structured documents, such as elements, terms, attributes, image and video references, which are parts of the user query; (2) entity relevance score computation – the computation of relevance scores for different structured elements with respect to the content they contain; (3) relevance score combination – the combination of relevance scores from (different) elements in a document structure, resulting in a common element relevance score; (4) relevance score propagation – the propagation of scores from different elements to common ancestor or descendant elements following the query. These four requirements are supported when developing a database logical algebra in harmony with the retrieval models used for ranking. In the specification of the logical algebra we face a challenge of a transparent instantiation of retrieval models, i.e., the specification of different retrieval models without affecting the algebra operators.