Semantic Discovery: Discovering Complex Relationships in Semantic Web

A NSF Medium ITR project

Semantic Annotation and Browsing Demo for ISWC2006

The goal is to identify known entities in text and provide annotations and browsing based on their type. For example, person names can be identified and details on each person can be provided from the ontology. Semantic browsing uses data from the ontology towards browsing using relationships of the data in the ontology. In this demo, semantic browsing is best exemplified by allowing to browse to other pages containing a particular name of a topic and its sub-topics from an ontology

The Details

• Service for Spotting Entities in Text
  It uses data containing names of Universities, People, and Topics
  Example: consider an URL as input, say, http://iswc2006.semanticweb.org/, the spotted names with their uri are eturned by a entity-spotting-service (here is a cached copy)
• Data used by this demo includes:
  • Topic Names from the Semantic Web Topics Ontology - built using collaborative efforts with wiki (this ontology includes ESWC Topics)
  • A dataset of Universities, and another with more Universities and synonyms thereof
  • Person Names of authors of previous WWW and Sem.Web conferences from a subset of SwetoDblp
• The prototype is almost completed; but, here is a canned-demo of Semantic Browsing through People Names or Topics

Live Demo

These pages are making use of semantic annotation + browsing:

• Industry Day and each of the nine pages linked from it
• Keynotes: Tom Gruber, Jane Fountain, Rudi Studer
• Papers: Ontology-Driven Automatic Entity Disambiguation in Unstructured Text, Framework for Schema-Driven Relationship Discovery from Unstructured text, and other papers accessible from the full list of Accepted Papers in Research Track
• Funding Panel

People Involved

• Students: Boanerges Aleman-Meza, Matthew Eavenson, Zixin Wu, Meena Nagarajan
• Faculty: Amit Sheth, and Budak Arpinar
• Other contributions as follows:
  
  • Delroy Cameron, and Sheron Decker provided the 'expertise dataset' from the Expertise Finder project (here's a local-copy of the dataset)
  • Maciej Janik provided a dataset of Wikipedia Entries for terms that appear in content of ISWC'06 webpages. The wikipedia entries were extracted by a crawling process
  • Bilal Gonen's MS thesis contains extensive details about semantic browsing
    

The contact person for details/problems/questions/etc on this page is Boanerges Aleman-Meza (balemanuga.edu)

This material is based upon work supported by the National Science Foundation under Grant No. IIS-0325464 titled "SemDis: Discovering Complex Relationships in Semantic Web". Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.