國立虎尾科技大學 |

Towards integrative machine learning and knowledge extraction = BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Towards integrative machine learning and knowledge extraction/ edited by Andreas Holzinger ... [et al.].
其他題名:	BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
其他題名:	BIRS Workshop
其他作者:	Holzinger, Andreas.
團體作者:	Workshop on the Preservation of Stability under Discretization
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	xvi, 207 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
標題:	Data mining - Congresses. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-69775-8
ISBN:	9783319697758

Towards integrative machine learning and knowledge extraction = BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
Towards integrative machine learning and knowledge extractionBIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /[electronic resource] :BIRS Workshopedited by Andreas Holzinger ... [et al.]. - Cham :Springer International Publishing :2017. - xvi, 207 p. :ill., digital ;24 cm. - Lecture notes in computer science,103440302-9743 ;. - Lecture notes in computer science ;6140..

Towards integrative Machine Learning & Knowledge Extraction -- Machine Learning and Knowledge Extraction in Digital Pathology needs an integrative approach -- Comparison of Public-Domain Software and Services for Probabilistic Record Linkage and Address Standardization -- Better Interpretable Models for Proteomics Data Analysis Using rule-based Mining -- Probabilistic Logic Programming in Action -- Persistent topology for natural data analysis -- A survey -- Predictive Models for Differentiation between Normal and Abnormal EEG through Cross-Correlation and Machine Learning Techniques -- A Brief Philosophical Note on Information -- Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline -- A Fast Semi-Automatic Segmentation Tool for Processing Brain Tumor Images -- Topological characteristics of oil and gas reservoirs and their applications -- Convolutional and Recurrent Neural Networks for Activity Recognition in Smart Environment.

The BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets" (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of "hot topics" toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.

ISBN: 9783319697758

Standard No.: 10.1007/978-3-319-69775-8doiSubjects--Topical Terms:

528575
Data mining
--Congresses.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Towards integrative machine learning and knowledge extraction = BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers /
LDR:03284nam a2200349 a 4500 001 905054
003 DE-He213
005 20171028141530.0
006 m d
007 cr nn 008maaau
008 190308s2017 gw s 0 eng d
020 $a 9783319697758 $q (electronic bk.)
020 $a 9783319697741 $q (paper)
024 7 $a 10.1007/978-3-319-69775-8 $2 doi
035 $a 978-3-319-69775-8
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343
072 7 $a UYQ $2 bicssc
072 7 $a TJFM1 $2 bicssc
072 7 $a COM004000 $2 bisacsh
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b B619 2015
111 2 $a Workshop on the Preservation of Stability under Discretization $d (2001 : $c Fort Collins, Colo.) $3 527686
245 1 0 $a Towards integrative machine learning and knowledge extraction $h [electronic resource] : $b BIRS Workshop, Banff, AB, Canada, July 24-26, 2015 : revised selected papers / $c edited by Andreas Holzinger ... [et al.].
246 3 $a BIRS Workshop
260 $a Cham : $c 2017. $b Springer International Publishing : $b Imprint: Springer,
300 $a xvi, 207 p. : $b ill., digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743 ; $v 10344
505 0 $a Towards integrative Machine Learning & Knowledge Extraction -- Machine Learning and Knowledge Extraction in Digital Pathology needs an integrative approach -- Comparison of Public-Domain Software and Services for Probabilistic Record Linkage and Address Standardization -- Better Interpretable Models for Proteomics Data Analysis Using rule-based Mining -- Probabilistic Logic Programming in Action -- Persistent topology for natural data analysis -- A survey -- Predictive Models for Differentiation between Normal and Abnormal EEG through Cross-Correlation and Machine Learning Techniques -- A Brief Philosophical Note on Information -- Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline -- A Fast Semi-Automatic Segmentation Tool for Processing Brain Tumor Images -- Topological characteristics of oil and gas reservoirs and their applications -- Convolutional and Recurrent Neural Networks for Activity Recognition in Smart Environment.
520 $a The BIRS Workshop "Advances in Interactive Knowledge Discovery and Data Mining in Complex and Big Data Sets" (15w2181), held in July 2015 in Banff, Canada, was dedicated to stimulating a cross-domain integrative machine-learning approach and appraisal of "hot topics" toward tackling the grand challenge of reaching a level of useful and useable computational intelligence with a focus on real-world problems, such as in the health domain. This encompasses learning from prior data, extracting and discovering knowledge, generalizing the results, fighting the curse of dimensionality, and ultimately disentangling the underlying explanatory factors in complex data, i.e., to make sense of data within the context of the application domain. The workshop aimed to contribute advancements in promising novel areas such as at the intersection of machine learning and topological data analysis. History has shown that most often the overlapping areas at intersections of seemingly disparate fields are key for the stimulation of new insights and further advances. This is particularly true for the extremely broad field of machine learning.
650 0 $a Data mining $v Congresses. $3 528575
650 0 $a Machine learning. $3 561253
650 0 $a Human-computer interaction $v Congresses. $3 670020 $3 727799
650 1 4 $a Computer Science. $3 593922
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 593924
650 2 4 $a Information Systems and Communication Service. $3 669203
650 2 4 $a Probability and Statistics in Computer Science. $3 669886
650 2 4 $a Software Engineering/Programming and Operating Systems. $3 669780
650 2 4 $a Computer Systems Organization and Communication Networks. $3 669309
700 1 $a Holzinger, Andreas. $3 792501
710 2 $a SpringerLink (Online service) $3 593884
773 0 $t Springer eBooks
830 0 $a Lecture notes in computer science ; $v 6140. $3 744199
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-69775-8
950 $a Computer Science (Springer-11645)