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Tech Report kmi-08-06 Abstract


Semantic Enrichment of Folksonomies
Techreport ID: kmi-08-06
Date: 2008
Author(s): Sofia Angeletou
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The goal of this research is to explore the potential of combining the heterogeneous technologies of Semantic Web and Web2.0 in order to contribute to an open and intelligent World Wide Web. This document is the second year research report of this PhD study on integrating Web2.0 and the Semantic Web.

Publication(s):

Angeletou, S., Sabou, M., and Motta, E. (2008) Semantically Enriching Folksonomies with FLOR, Workshop: 1st International Workshop on Collective Semantics: Collective Intelligence & the Semantic Web (CISWeb 2008) at European Semantic Web Conference

Angeletou, S., Sabou, M., Specia, L., and Motta, E. (2007) Bridging the Gap Between Folksonomies and the Semantic Web: An Experience Report, Workshop: Bridging the Gap between Semantic Web and Web 2.0 at European Semantic Web Conference
 
KMi Publications Event | SSSW 2013, The 10th Summer School on Ontology Engineering and the Semantic Web Journal | 25 years of knowledge acquisition
 

Multimedia and Information Systems is...


Multimedia and Information Systems
Our research is centred around the theme of Multimedia Information Retrieval, ie, Video Search Engines, Image Databases, Spoken Document Retrieval, Music Retrieval, Query Languages and Query Mediation.

We focus on content-based information retrieval over a wide range of data spanning form unstructured text and unlabelled images over spoken documents and music to videos. This encompasses the modelling of human perception of relevance and similarity, the learning from user actions and the up-to-date presentation of information. Currently we are building a research version of an integrated multimedia information retrieval system MIR to be used as a research prototype. We aim for a system that understands the user's information need and successfully links it to the appropriate information sources, be it a report or a TV news clip. This work is guided by the vision that an automated knowledge extraction system ultimately empowers people making efficient use of information sources without the burden of filing data into specialised databases.

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