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Feed Distillation Using AdaBoost and Topic Maps
Paper, was published by Andreas Lommatzsch, Christian Scheel, and Wai-Lung Lee at 2008-02-07
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In this paper, we want to retain our experiences by participating in TREC 2007 Blog Track ‘Feed Distillation’. To perform the run we combine various classifiers analyzing title-, content- and splog-specific features to predict the relevance of a feed related to a topic, based on the idea of AdaBoost. The implemented classifiers are based on keywords retrieved from different thesauri such as Wordnet and Wortschatz, as well as websites providing hierarchical organized ‘ontology’ such as the ‘Open Directory Project’ and Yahoo Directory. To structure the keywords, we use Topic Maps.
Authors
Wai-Lung Lee
http://www.xing.com/profile/WaiLung_Lee
Wai-Lung is author of Feed Distillation Using.. .
This publication cites the following publications
Topic Maps is an excellent paradigm to support human thinking and to visualize networked information. As part of my PhD project, I therefore chose Topic Maps as the conceptual foundation for designing and implementing a software prototype for semantic knowledge retrieval.