The latest issue of Journal of Documentation includes an interesting paper on content-based image retrieval. This describes a survey of operational image retrieval activity and a sample collection of user requests, the resulting images retrieved and their associated metadata. The research was undertaken as part of the ‘Bridging the semantic gap in visual information retrieval’ project funded by the Arts & Humanities Research Council. The purpose of the research is stated as:
“To provide a better-informed view of the extent of the semantic gap in image retrieval, and the limited potential for bridging it offered by current image semantic retrieval techniques.”
Enser, Peter G. B. & Sandom, Christine J. (School of Computing, Mathematical and Information Sciences, University of Brighton; Hare, Jonathon S. & Lewis, Paul; H. (School of Electronics and Computer Science, University of Southampton). Facing the reality of semantic image retrieval. JDoc 63(4), 2007, p465-481.
Marcia Zeng posted today the following message to the NKOS (Networked Knowledge Organization Systems) list:
- Everyone knows about the ‘tag cloud’ approach when showing popular tags. How about using this same idea for presenting keywords in documents and making a dynamic cloud which matches a particular event? Here are some examples I found interesting.
US Presidential Speeches Aging Tag Cloud Timeline
The tag cloud shows the popularity, frequency, and trends in the usages of words within speeches, official documents, declarations, and letters written by the Presidents of the US between 1776 – 2007 AD.
Microsoft’s evolution, in keywords
At both case, there is a timeline on the top. Move the slider around for a unique glimpse into the document of a particular time.
Information about tagline generator is at: