In this chapter we present an innovative way of automatically organizing multimedia information to facilitate content-based browsing, thus answering the question of the first query and of the presentation of the response. We think that labor-intensive methods should be avoided as much as possible in the whole process. We focus our attention on content-based maps. The visualization capabilities of the self-organizing map provide an intuitive way of representing the distribution of data as well as the object similarities. The main idea is to visualize similar documents spatially close to each other, while the distance between different documents is bigger.
Description
In this chapter we present an innovative way of automatically organizing multimedia information to facilitate content-based browsing, thus answering the question of the first query and of the presentation of the response. We think that labor-intensive methods should be avoided as much as possible in the whole process. We focus our attention on content-based maps. The visualization capabilities of the self-organizing map provide an intuitive way of representing the distribution of data as well as the object similarities. The main idea is to visualize similar documents spatially close to each other, while the distance between different documents is bigger.
%0 Book Section
%1 Baerecke2008CIMP
%A Bärecke, Thomas
%A Kijak, Ewa
%A Detyniecki, Marcin
%A Nürnberger, Andreas
%B Computational Intelligence in Multimedia Processing: Recent Advances
%C Berlin/Heidelberg
%D 2008
%E Hassanien, Aboul-Ella
%E Kacprzyk, Janusz
%E Abraham, Ajith
%I Springer
%K clustering navigation self_organizing_maps user_interface video_browsing video_summarization
%P 493-509
%R 10.1007/978-3-540-76827-2_18
%T Organizing Multimedia Information with Maps
%U http://www.springerlink.com/content/087365717q201817
%V 96
%X In this chapter we present an innovative way of automatically organizing multimedia information to facilitate content-based browsing, thus answering the question of the first query and of the presentation of the response. We think that labor-intensive methods should be avoided as much as possible in the whole process. We focus our attention on content-based maps. The visualization capabilities of the self-organizing map provide an intuitive way of representing the distribution of data as well as the object similarities. The main idea is to visualize similar documents spatially close to each other, while the distance between different documents is bigger.
@incollection{Baerecke2008CIMP,
abstract = {In this chapter we present an innovative way of automatically organizing multimedia information to facilitate content-based browsing, thus answering the question of the first query and of the presentation of the response. We think that labor-intensive methods should be avoided as much as possible in the whole process. We focus our attention on content-based maps. The visualization capabilities of the self-organizing map provide an intuitive way of representing the distribution of data as well as the object similarities. The main idea is to visualize similar documents spatially close to each other, while the distance between different documents is bigger.},
added-at = {2009-09-10T09:22:25.000+0200},
address = {Berlin/Heidelberg},
author = {Bärecke, Thomas and Kijak, Ewa and Detyniecki, Marcin and Nürnberger, Andreas},
biburl = {https://www.bibsonomy.org/bibtex/27564ccb41ab5b31a9bcf2491a594aa70/tbaerecke},
booktitle = {Computational Intelligence in Multimedia Processing: Recent Advances},
description = {In this chapter we present an innovative way of automatically organizing multimedia information to facilitate content-based browsing, thus answering the question of the first query and of the presentation of the response. We think that labor-intensive methods should be avoided as much as possible in the whole process. We focus our attention on content-based maps. The visualization capabilities of the self-organizing map provide an intuitive way of representing the distribution of data as well as the object similarities. The main idea is to visualize similar documents spatially close to each other, while the distance between different documents is bigger.},
doi = {10.1007/978-3-540-76827-2_18},
editor = {Hassanien, Aboul-Ella and Kacprzyk, Janusz and Abraham, Ajith},
file = {:http\://webia.lip6.fr/~baerecke/docs/Baerecke2008CIMP.pdf:PDF},
interhash = {f0f2222fd7c5e9bc2ef8ed1fc8ee2905},
intrahash = {7564ccb41ab5b31a9bcf2491a594aa70},
keywords = {clustering navigation self_organizing_maps user_interface video_browsing video_summarization},
month = {April},
pages = {493-509},
publisher = {Springer},
series = {Studies in Computational Intelligence},
timestamp = {2009-09-10T09:22:25.000+0200},
title = {Organizing Multimedia Information with Maps},
url = {http://www.springerlink.com/content/087365717q201817},
volume = 96,
year = 2008
}