KMi Seminars
From Tag Clouds to Tag Webs
This event took place on Wednesday 16 May 2007 at 11:15

 
Dr Simon Buckingham Shum

In this seminar I'll present results from the formative evaluation of ClaimSpotter, an experimental semantic social tagging tool developed in Bertrand Sereno's PhD, and presented at the WWW'07 CKC workshop: When they publish their work, researchers build in established ways on prior work, expressing and contesting claims and counter-arguments. Collaborative tagging holds promise as an approach to mediating this discursive process via the Web, but, although permitting diversity of opinion, 'pure' freeform tagging provides no support to analysts who want to differentiate important kinds of tag, and critically, their inter-relationships. Our experience demonstrates that collaborative, scholarly tagging requires tools designed specifically for this sensemaking task by providing enough support to initiate the annotation, while not overwhelming users with suggestions. We describe a tool called ClaimSpotter that aims at supporting this tradeoff, through a novel combination of system-initiated tag recommendations, Web interface design, and an expanded conception of how tags can be both expressed, and semantically linked. We then report a detailed study which analysed the tool's usability and the tag structures created, contributing to our understanding of the implications of adding structure to collaborative tagging.

 
KMi Seminars 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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