Abstract The INitiative for the Evaluation of XML retrieval (INEX) aims at providing an infrastructure to evaluate the effectiveness of content‐oriented XML retrieval systems. To this end, in the first round of INEX in 2002, a test collection of real world XML documents along with a set of topics and respective relevance assessments have been created with the collaboration of 36 participating organizations. In this article, we provide an overview of the first round of the INEX initiative.

Query languages for retrieval of XML documents allow for conditions referring both to the content and the structure of documents. In this paper, we investigate two different approaches for reducing index space of inverted files for XML documents. First, we consider methods for compressing index entries. Second, we develop the new XS tree data structure which contains the structural description of a document in a rather compact form, such that these descriptions can be kept in main memory. Experimental results on two large XML document collections show that very high compression rates for indexes can be achieved, but any compression increases retrieval time. On the other hand, highly compressed indexes may be feasible for applications where storage is limited, such as in PDAs or E-book devices.

No abstract available.

The automatic categorisation of web documents is becoming crucial for organising the huge amount of information available in the Internet. We are facing a new challenge due to the fact that web documents have a rich structure and are highly heterogeneous. Two ways to respond to this challenge are (1) using a representation of the content of web documents that captures these two characteristics and (2) using more effective classifiers.

We describe the design and implementation of a system for logic-based multimedia retrieval. As high-level logic for retrieval of hypermedia documents, we have developed a probabilistic object-oriented logic (POOL) which supports aggregated objects, different kinds of propositions (terms, classifications and attributes) and even rules as being contained in objects. Based on a probabilistic four-valued logic, POOL uses an implicit open world assumption, allows for closed world assumptions and is able to deal with inconsistent knowledge. POOL programs and queries are translated into probabilistic Datalog programs which can be interpreted by the HySpirit inference engine. For storing the multimedia data, we have developed a new basic IR engine which yields physical data abstraction. The overall architecture and the flexibility of each layer supports logic-based methods for multimedia information retrieval.