Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
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Advances in Mining Graphs, Trees and Sequences (Paperback)
Loot Price: R2,723
Discovery Miles 27 230
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Advances in Mining Graphs, Trees and Sequences (Paperback)
Series: Frontiers in Artificial Intelligence and Applications, v. 124
Expected to ship within 10 - 15 working days
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Total price: R2,743
Discovery Miles: 27 430
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Ever since the early days of machine learning and data mining, it
has been realized that the traditional attribute-value and item-set
representations are too limited for many practical applications in
domains such as chemistry, biology, network analysis and text
mining. This has triggered a lot of research on mining and learning
within alternative and more expressive representation formalisms
such as computational logic, relational algebra, graphs, trees and
sequences. The motivation for using graphs, trees and sequences. Is
that they are 1) more expressive than flat representations, and 2)
potentially more efficient than multi-relational learning and
mining techniques. At the same time, the data structures of graphs,
trees and sequences are among the best understood and most widely
applied representations within computer science. Thus these
representations offer ideal opportunities for developing
interesting contributions in data mining and machine learning that
are both theoretically well-founded and widely applicable. The goal
of this book is to collect recent outstanding studies on mining and
learning within graphs, trees and sequences in studies worldwide.
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