Machine Learning and Knowledge Discovery for Semantic Web
Description:
Machine Learning and Semantic web are covering conceptually different sides of the same story – Semantic Web’s typical approach is top-down modeling of knowledge and proceeding down towards the data while Machine Learning is almost entirely data-driven bottom-up approach trying to discover the structure in the data and express it in the more abstract ways and rich knowledge formalisms. The talk will discuss possible interaction and usage of Machine Learning and Knowledge discovery for Semantic Web with emphases on ontology construction. In the second half of the talk we will take a look at some research using machine learning for Semantic Web and demos of the corresponding prototype systems.
The presentation runs 80+ minutes but three quick points:
First, the “Semi-Automatic Data-Driven Ontology Construction, http://ontogen.ijs.si, from a slightly different point of view, could be converted into a topic map authoring tool for working with data.
Second, the “jaguar” search example at 39:29 was particularly compelling. Definitely improves the usefulness of the search results but still working at the document level. The document level is the wrong level for search, unless you just like wasting time repeating what other people have already done.
Third, there are lots of other tools and resources at: http://ailab.ijs.si/. I am going to be slowly mining this site but if you encounter something really interesting, please make a comment or drop me a note.
Definitely a group to watch.