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Modeling and Evaluation of Co-Evolution in Collective Web Memories

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Prytkova,  Natalia
International Max Planck Research School, MPI for Informatics, Max Planck Society;
Databases and Information Systems, MPI for Informatics, Max Planck Society;

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Citation

Prytkova, N. (2011). Modeling and Evaluation of Co-Evolution in Collective Web Memories. Master Thesis, Universität des Saarlandes, Saarbrücken.


Cite as: https://hdl.handle.net/11858/00-001M-0000-0010-1493-D
Abstract
The constantly evolving Web reects the evolution of society in the cyberspace. Projects like the Open Directory Project (dmoz.org) can be understood as a collective memory of society on the Web. The main assumption is that such collective Web memories evolve when a certain cognition level about a concept has been exceeded. In the scope of our work we analyse the New York Times archive for concept detection. There are several approaches to the concept modelling. We introduce an alternative model for concepts, which does not make any additional assumptions about types of contained entities or the number of entities in the corpus. Moreover, the proposed distributed concept computation algorithm enables the large scale archive analysis. We also introduce a model of cognition level and explain how it can be employed to predict changes in the category system of DMOZ.