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Solomonovi seminarji

A short Tutorial on Semantic Web

author: York Sure, University of Karlsruhe
coauthor: Andreas Hotho, Department of Electrical Engineering and Computer Sciences, University of Kassel

Description

The availability of electronically stored information increased drastically through the development of the World Wide Web. Currently the WWW contains more than a billion documents, but support for accessing and precessing information is limited. Most information is only presentable but not understandable by computers. Tim Berners-Lee envisioned the Semantic Web that aims at providing automated access to information due to machine-processable semantics of data. Ontologies formalize a shared understanding of a domain and therefore play a crucial role for communication among human beings and software agents.

We will present the underlying ideas of the Semantic Web and will shortly introduce ontologies as the backbone of the Semantic Web. Further we will show how much effort is necessary to setup the Semantic Web and how tools can support this process. Additionally Web and Data Mining techniques can be used to bootstrap the Semantic Web. The idea of Semantic Web Mining is to improve the results of Web Mining by exploiting the new semantic structures in the web.

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Slides
0:05 A Short Semantic Web Tutorial
2:25 Karlsruhe: Location for Semantic Technologies
4:12 KAON
5:11 slide4
6:05 Semantic Web
8:21 Machine accessible meaning (What it’s like to be a machine)
9:04 Semantic Web Layers (T. Berners-Lee et al.)
9:43 XML:
11:15 XML: Document = labelled tree
12:33 XML: limitations for semantic markup
13:51 XML  machine accessible meaning
14:25 The semantic pyramid again
15:19 RDF for semantic annotation
17:10 What does RDF Schema add?
19:25 RDF Schema syntax in XML
20:57 Conclusions about RDF(S)
21:25 Last but not least ...
22:57 Ontology
25:22 Communication Principle
27:19 Views on Ontologies
28:52 Menu
29:43 Menu
30:33 Menu
32:44 Ontology (in our sense)
37:44 Ontology & Metadata
39:01 Example: OntoWeb.org
42:22 slide27
42:33 OTK Methodology: Knowledge Meta Process
44:06 But ...
44:47 Why only semi-automatically?
46:29 Where to start?
48:45 Extracting Semantics from the Web
49:09 Ontology Learning
50:02 Example
56:21 Example
59:53 Crawling the (semantic) web for filling the ontology
61:02 Example
67:39 Semantic Web Usage Mining
68:59 Text Document Clustering of Crawled Documents
71:14 slide44
71:28 Our Vision
74:12 slide46
75:39 Acknowledgements
76:50 Selected Literature
78:42 Selected Literature
80:24 Selected Literature

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