The Semantic Web is the idea of having data on the Web defined and linked in a way that it can be used for more effective discovery, automation, integration, and reuse across various applications. The Resource Description Framework (RDF) is considered to be an important basis for the realisation of this vision. The bib2rdf tool translates the structured data that is contained in BibTeX bibliographies into an RDF-compliant form, which makes a vast amount of bibliographical information available for Semantic Web applications.
The Java BibTeX-To-RDF Converter allows to convert BibTeX files to an RDF format according to the SWRC ontology. It has been developed by Peter Haase and Björn Schnizler in the scope of the SWAP project.
As BibTeX Parser we have used JavaBib Parser by Johannes Henkel.
With the advent of the semantic web, several projects have started to translate this bibliographic information to RDF. bibtex2rdf is a highly configurable translator from BibTeX to RDF which allows to do exactly that.
SUBMISSION DATES:
March 10, 2006: Submission of electronic abstracts and papers
April 30, 2006: Notification for conference papers
May 30, 2006: "Camera-ready" copies for conference papers
Plum lets you put all the stuff you care about, stumble across or need in one place. Collect and save from the web, your email, or your computer. Then personalize and share it with others (if you like). You can even discover other collections like yours and collect them too.
Web spam pages use various techniques to achieve
higher-than-deserved rankings in a search engine’s
results. While human experts can identify
spam, it is too expensive to manually evaluate a
large number of pages. Instead, we propose techniques
to semi-automatically separate reputable,
good pages from spam. We first select a small set
of seed pages to be evaluated by an expert. Once
we manually identify the reputable seed pages, we
use the link structure of the web to discover other
pages that are likely to be good. In this paper
we discuss possible ways to implement the seed
selection and the discovery of good pages. We
present results of experiments run on the World
Wide Web indexed by AltaVista and evaluate the
performance of our techniques. Our results show
that we can effectively filter out spam from a significant
fraction of the web, based on a good seed
set of less than 200 sites.
T. Hanika, und T. Hille. Conceptual Knowledge Structures - First International Joint Conference, CONCEPTS 2024, Cádiz, Spain, September 9-13, 2024, Proceedings, Volume 14914 von Lecture Notes in Computer Science, Seite 97--112. Springer, (2024)