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Scalable Uncertainty Management - 6th International Conference, SUM 2012, Marburg, Germany, September 17-19, 2012, Proceedings (Paperback, 2012 ed.)
Eyke Hullermeier, Sebastian Link, Thomas Fober, Bernhard Seeger
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R1,673
Discovery Miles 16 730
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Ships in 10 - 15 working days
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This book constitutes the refereed proceedings of the 6th
International Conference on Scalable Uncertainty Management, SUM
2012, held in Marburg, Germany, in September 2012. The 41 revised
full papers and 13 revised short papers were carefully reviewed and
selected from 75 submissions. The papers cover topics in all areas
of managing and reasoning with substantial and complex kinds of
uncertain, incomplete or inconsistent information including
applications in decision support systems, machine learning,
negotiation technologies, semantic web applications, search
engines, ontology systems, information retrieval, natural language
processing, information extraction, image recognition, vision
systems, data and text mining, and the consideration of issues such
as provenance, trust, heterogeneity, and complexity of data and
knowledge.
The structural comparison of whole proteins or protein binding
sites is usually performed by making use of graphs. Even though
graphs exhibit a lot of interesting and useful properties, the
usage of other representations can come along with several
benefits. In this book the representation of a protein binding site
is tackled. Three representations are considered namely the
geometric, the feature-based and the graph-based representation.
For all three types, some completely new algorithms are developed
and presented. Moreover, existing methods are adapted to the
application of protein binding sites' comparison. In addition,
algorithms for the construction of multiple structural alignments
are presented as a structural counterpart to multiple sequence
alignment. By considering four different types of experiments,
namely classification, similarity retrieval, clustering and
construction of structural alignments, strengths and weaknesses of
the proposed methods are detected and discussed. In addition a
hybrid approach is presented which combines the benefits of a
feature-based and a geometric method leading to a significant
speed-up while still holding very good results.
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