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There is generalagreementthat the quality of Machine Learning and
Kno-
edgeDiscoveryoutputstronglydependsnotonlyonthequalityofsourcedata
andsophisticationoflearningalgorithms,butalsoonadditional,task/domain
speci?c input provided by domain experts for the particular
session. There is however less agreement on whether, when and how
such input can and should e?ectively be formalized and reused as
explicit prior knowledge. In the ?rst ofthe two parts into which
the book is divided, we aimed to - vestigate current developments
and new insights on learning techniques that exploit prior
knowledge and on promising application areas. With respect to
application areas, experiments on bio-informatics / medical and Web
data environments are described. This part comprises a selection of
extended c- tributionstothe workshopPrior Conceptual Knowledge
inMachine Learning and Knowledge Discovery (PriCKL), held at
ECML/PKDD 2007 18th - ropean Conference on Machine Learning and
11th European Conference on
PrinciplesandPracticeofKnowledgeDiscoveryinDatabases).Theworkshop
is part of the activities of the "SEVENPRO - Semantic Virtual
Engineering for Product Design" project of the European 6th
Framework Programme. The second part of the book has been motivated
by the speci?cation of Web 2.0. We observe Web 2.0 as a powerful
means of promoting the Web as a social medium, stimulating
interpersonal communication and fostering the sharing of content,
information, semantics and knowledge among people. Chapters are
authored by participants to the workshop Web Mining 2.0,
heldatECML/PKDD2007.Theworkshophostedresearchontheroleofweb
mininginandfortheWeb2.0.Itispartoftheactivitiesoftheworkinggroups
"UbiquitousData-InteractionandDataCollection"and"HumanComputer
Interaction and Cognitive Modelling" of the Coordination Action
"KDubiq - Knowledge Discovery in Ubiquitous Environments" of the
European 6th Framework Programme.
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Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part I (Paperback, 2013 ed.)
Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezny
|
R1,700
Discovery Miles 17 000
|
Ships in 10 - 15 working days
|
This three-volume set LNAI 8188, 8189 and 8190 constitutes the
refereed proceedings of the European Conference on Machine Learning
and Knowledge Discovery in Databases, ECML PKDD 2013, held in
Prague, Czech Republic, in September 2013. The 111 revised research
papers presented together with 5 invited talks were carefully
reviewed and selected from 447 submissions. The papers are
organized in topical sections on reinforcement learning; Markov
decision processes; active learning and optimization; learning from
sequences; time series and spatio-temporal data; data streams;
graphs and networks; social network analysis; natural language
processing and information extraction; ranking and recommender
systems; matrix and tensor analysis; structured output prediction,
multi-label and multi-task learning; transfer learning; bayesian
learning; graphical models; nearest-neighbor methods; ensembles;
statistical learning; semi-supervised learning; unsupervised
learning; subgroup discovery, outlier detection and anomaly
detection; privacy and security; evaluation; applications; and
medical applications.
|
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part II (Paperback, 2013 ed.)
Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezny
|
R1,697
Discovery Miles 16 970
|
Ships in 10 - 15 working days
|
This three-volume set LNAI 8188, 8189 and 8190 constitutes the
refereed proceedings of the European Conference on Machine Learning
and Knowledge Discovery in Databases, ECML PKDD 2013, held in
Prague, Czech Republic, in September 2013. The 111 revised research
papers presented together with 5 invited talks were carefully
reviewed and selected from 447 submissions. The papers are
organized in topical sections on reinforcement learning; Markov
decision processes; active learning and optimization; learning from
sequences; time series and spatio-temporal data; data streams;
graphs and networks; social network analysis; natural language
processing and information extraction; ranking and recommender
systems; matrix and tensor analysis; structured output prediction,
multi-label and multi-task learning; transfer learning; bayesian
learning; graphical models; nearest-neighbor methods; ensembles;
statistical learning; semi-supervised learning; unsupervised
learning; subgroup discovery, outlier detection and anomaly
detection; privacy and security; evaluation; applications; and
medical applications.
This book constitutes the thoroughly refereed post-proceedings of
the 22nd International Conference on Inductive Logic Programming,
ILP 2012, held in Dubrovnik, Croatia, in September 2012. The 18
revised full papers were carefully reviewed and selected from 41
submissions. The papers cover the following topics:
propositionalization, logical foundations, implementations,
probabilistic ILP, applications in robotics and biology,
grammatical inference, spatial learning and graph-based learning.
The 18th International Conference on Inductive Logic Programming
was held in Prague, September 10-12, 2008. ILP returned to Prague
after 11 years, and it is tempting to look at how the topics of
interest have evolved during that time. The ILP community clearly
continues to cherish its beloved ?rst-order logic representation
framework. This is legitimate, as the work presented at ILP 2008
demonstrated that there is still room for both extending
established ILP approaches (such as inverse entailment) and
exploring novel logic induction frameworks (such as brave
induction). Besides the topics lending ILP research its unique
focus, we were glad to see in this year's proceedings a good n- ber
of papers contributing to areas such as statistical relational
learning, graph mining, or the semantic web. To help open ILP to
more mainstream research areas, the conference featured three
excellent invited talks from the domains of the semantic web (Frank
van Harmelen), bioinformatics (Mark Craven) and cognitive sciences
(Josh Tenenbaum). We deliberately looked for speakers who are not
directly involved in ILP research. We further invited a tutorial on
stat- tical relational learning (Kristian Kersting) to meet the
strong demand to have the topic presented from the ILP perspective.
Lastly, Stefano Bertolo from the European Commission was invited to
give a talk on the ideal niches for ILP in the current EU-supported
research on intelligent content and semantics.
|
Machine Learning and Knowledge Discovery in Databases - European Conference, ECML PKDD 2013, Prague, Czech Republic, September 23-27, 2013, Proceedings, Part III (Paperback, 2013 ed.)
Hendrik Blockeel, Kristian Kersting, Siegfried Nijssen, Filip Zelezny
|
R1,696
Discovery Miles 16 960
|
Ships in 10 - 15 working days
|
This three-volume set LNAI 8188, 8189 and 8190 constitutes the
refereed proceedings of the European Conference on Machine Learning
and Knowledge Discovery in Databases, ECML PKDD 2013, held in
Prague, Czech Republic, in September 2013. The 111 revised research
papers presented together with 5 invited talks were carefully
reviewed and selected from 447 submissions. The papers are
organized in topical sections on reinforcement learning; Markov
decision processes; active learning and optimization; learning from
sequences; time series and spatio-temporal data; data streams;
graphs and networks; social network analysis; natural language
processing and information extraction; ranking and recommender
systems; matrix and tensor analysis; structured output prediction,
multi-label and multi-task learning; transfer learning; bayesian
learning; graphical models; nearest-neighbor methods; ensembles;
statistical learning; semi-supervised learning; unsupervised
learning; subgroup discovery, outlier detection and anomaly
detection; privacy and security; evaluation; applications; and
medical applications.
There is generalagreementthat the quality of Machine Learning and
Kno-
edgeDiscoveryoutputstronglydependsnotonlyonthequalityofsourcedata
andsophisticationoflearningalgorithms, butalsoonadditional,
task/domain speci?c input provided by domain experts for the
particular session. There is however less agreement on whether,
when and how such input can and should e?ectively be formalized and
reused as explicit prior knowledge. In the ?rst ofthe two parts
into which the book is divided, we aimed to - vestigate current
developments and new insights on learning techniques that exploit
prior knowledge and on promising application areas. With respect to
application areas, experiments on bio-informatics / medical and Web
data environments are described. This part comprises a selection of
extended c- tributionstothe workshopPrior Conceptual Knowledge
inMachine Learning and Knowledge Discovery (PriCKL), held at
ECML/PKDD 2007 18th - ropean Conference on Machine Learning and
11th European Conference on
PrinciplesandPracticeofKnowledgeDiscoveryinDatabases).Theworkshop
is part of the activities of the "SEVENPRO - Semantic Virtual
Engineering for Product Design" project of the European 6th
Framework Programme. The second part of the book has been motivated
by the speci?cation of Web 2.0. We observe Web 2.0 as a powerful
means of promoting the Web as a social medium, stimulating
interpersonal communication and fostering the sharing of content,
information, semantics and knowledge among people. Chapters are
authored by participants to the workshop Web Mining 2.0,
heldatECML/PKDD2007.Theworkshophostedresearchontheroleofweb
mininginandfortheWeb2.0.Itispartoftheactivitiesoftheworkinggroups
"UbiquitousData-InteractionandDataCollection"and"HumanComputer
Interaction and Cognitive Modelling" of the Coordination Action
"KDubiq - Knowledge Discovery in Ubiquitous Environments" of the
European 6th Framework Programme.
|
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