Through a job announcement of STI Innsbruck I was made aware of the LarKC project.

To quote the job announcement:

Current Semantic Web reasoning systems do not scale to the requirements of their hottest applications, such as analyzing data from millions of mobile devices, dealing with terabytes of scientific data, and content management in enterprises with thousands of knowledge workers.

The Large Knowledge Collider (LarKC, for short, pronounced “lark”), a platform for massive distributed incomplete reasoning will remove these scalability barriers. This will be achieved by:

• Enriching the current logic-based Semantic Web reasoning methods with methods from information retrieval, machine learning, information theory, databases, and probabilistic reasoning,
• Employing cognitively inspired approaches and techniques such as spreading activation, focus of attention, reinforcement, habituation, relevance reasoning, and bounded rationality.
• Building a distributed reasoning platform and realizing it both on a high-performance computing cluster and via “computing at home”.

The project consortium is an interdisciplinary team of engineers and researchers in Computing Science, Web Science and Cognitive Science, well qualified to realize this ambitious vision. The Large Knowledge Collider will be an open architecture. Researchers and practitioners from outside the consortium will be encouraged to develop and plug in their own components to drive parts of the system. This will make the Large Knowledge Collider a generic platform, and not just a single reasoning engine.

What more shall I say than: Way to go LarKC!

I tried to figure out some additional information about the project.

What I’ve found is this blog entry. A colleague of mine discovered a presentation given at a workshop.

After some silent time in the field of information retrieval in the semantic web, search in the next generation web seems to be an upcoming topic in different research communities. Recently two calls for papers have been posted. Both are CFPs from workshops. One is hosted on the European Semantic Web Conference (ESWC) the other one is hosted the European Conference on Information Retrieval (ECIR).

If you are interested in research related to information retrieval / search and semantic web you might be interested in these two meetings:

• Semantic Search 2008 Workshop
• Exploiting Semantic Annotations in Information Retrieval

From September 24 to September 26 I was in Halle (at the river Saale) in Germany attending FGIR 2007. FGIR is part of LWA, an annual event of several interest groups of the German Computer Society. The venue was located at the computer science instate of the Martin Luther university. The community represented by the different interest groups (all of them in some form related to knowledge) was very interesting and for 20€ of registration feed you even got refreshments and snacks .
We had two papers there: In the presented first we focused in detail on the evolution of the associative retrieval component (which was first presented at i-Semantics). Besides simply presenting the obtained results in this paper we argued why our chosen approach to evaluation of an information retrieval on the Semantic Desktop is valid. With the German interest group for information retrieval we had the perfect audience for this talk.
The other paper presented is a survey of current approaches to information retrieval in the Semantic Web and on the Semantic Desktop. In this paper we also try to find a definition what information on the Semantic Web actually is.

The SPARQL Query Language for RDF is back to the status of Candidate Recommendation. Some of you may know it already had this status on April 6, 2006. It was returned to being a Working Draft on October 4, 2006.

Swoogle - a search engine for semantic web documents (a.k.a. ontologies) - is now available in an improved 2007 version:

The biggest change is that Swoogle?s IR index is now updated incrementally, as new or modified Semantic Web documents are processed. When Swoogle processes an RDF document, it analyzes it to extract metadata, and then adds or updates the metadata in Swoogle?s database as well as (re-) indexes information about the document in Swoogle?s IR engine. Previously, these information in the database was updated as documents were found but the IR index was regenerated periodically in an off line batch process. Consequently, the two were not completely synchronized. They are now, at least on a daily basis.

Recently I discovered a nice survey on semantic web search engines. If you are interested in this topic (as I am) you should not miss it:

A Categorization Scheme for Semantic Web Search Engines (Esmaili & Abolhassani, 2006)

In addition check at the references on the Search on the Semantic Web page (of course there is some overlap - search on the semantic web is a young discipline ).

A fellow-worker of mine pointed me to the following article: Domain Specific Searches using Conceptual Spectra by Bonino et al. (2004). What they do is interesting. They allow for searching documents by concepts using semantic annotation. Documents are annotated with concepts, these annotation links are weighted. This process has to be done manually. The search is carried out using a vector space model. For (graphically) analyzing the relations between documents and concepts they introduce the the notion of a Conceptual Spectrum. A conceptual spectrum visualizes the relations to concepts of one document according to the weight of the annotation link.