國立高雄大學圖資館 |

語系: 繁體中文

說明(常見問題)

圖資館首頁

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Machine learning and knowledge disco...

(1998 :)

Machine learning and knowledge discovery in databasesEuropean Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings.Part II /

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Machine learning and knowledge discovery in databasesedited by Michele Berlingerio ... [et al.].
其他題名:	European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings.
其他題名:	ECML PKDD 2018
其他作者:	Berlingerio, Michele.
團體作者:
出版者:	Cham :Springer International Publishing :2019.
面頁冊數:	xxx, 866 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer eBooks
標題:	Machine learningCongresses.
電子資源:	https://doi.org/10.1007/978-3-030-10928-8
ISBN:	9783030109288$q(electronic bk.)

Machine learning and knowledge discovery in databasesEuropean Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings.Part II /
Machine learning and knowledge discovery in databasesEuropean Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings.Part II /[electronic resource] :ECML PKDD 2018edited by Michele Berlingerio ... [et al.]. - Cham :Springer International Publishing :2019. - xxx, 866 p. :ill. (some col.), digital ;24 cm. - Lecture notes in computer science,110520302-9743;. - Lecture notes in computer science ;4891..

The three volume proceedings LNAI 11051 - 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.

ISBN: 9783030109288$q(electronic bk.)

Standard No.: 10.1007/978-3-030-10928-8doiSubjects--Topical Terms:

384498
Machine learning
--Congresses.

LC Class. No.: Q325.5

Dewey Class. No.: 006.31

Machine learning and knowledge discovery in databasesEuropean Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings.Part II /
LDR:02309nmm a2200349 a 4500 001 555278
003 DE-He213
005 20190122204531.0
006 m d
007 cr nn 008maaau
008 191121s2019 gw s 0 eng d
020 $a 9783030109288$q(electronic bk.)
020 $a 9783030109271$q(paper)
024 7 $a 10.1007/978-3-030-10928-8 $2 doi
035 $a 978-3-030-10928-8
040 $a GP $c GP
041 0 $a eng
050 4 $a Q325.5
072 7 $a UYQ $2 bicssc
072 7 $a COM004000 $2 bisacsh
072 7 $a UYQ $2 thema
082 0 4 $a 006.31 $2 23
090 $a Q325.5 $b .E19 2018
111 2 $n (3rd : $d 1998 : $c Amsterdam, Netherlands) $3 194767
245 1 0 $a Machine learning and knowledge discovery in databases $h [electronic resource] : $b European Conference, ECML PKDD 2018, Dublin, Ireland, September 10-14, 2018 : proceedings. $n Part II / $c edited by Michele Berlingerio ... [et al.].
246 3 $a ECML PKDD 2018
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2019.
300 $a xxx, 866 p. : $b ill. (some col.), digital ; $c 24 cm.
490 1 $a Lecture notes in computer science, $x 0302-9743; $v 11052
490 1 $a Lecture notes in artificial intelligence
520 $a The three volume proceedings LNAI 11051 - 11053 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2018, held in Dublin, Ireland, in September 2018. The total of 131 regular papers presented in part I and part II was carefully reviewed and selected from 535 submissions; there are 52 papers in the applied data science, nectar and demo track. The contributions were organized in topical sections named as follows: Part I: adversarial learning; anomaly and outlier detection; applications; classification; clustering and unsupervised learning; deep learningensemble methods; and evaluation. Part II: graphs; kernel methods; learning paradigms; matrix and tensor analysis; online and active learning; pattern and sequence mining; probabilistic models and statistical methods; recommender systems; and transfer learning. Part III: ADS data science applications; ADS e-commerce; ADS engineering and design; ADS financial and security; ADS health; ADS sensing and positioning; nectar track; and demo track.
650 0 $a Machine learning $v Congresses. $3 384498
650 0 $a Data mining $v Congresses. $3 380776
650 1 4 $a Artificial Intelligence. $3 212515
650 2 4 $a Data Mining and Knowledge Discovery. $3 275288
650 2 4 $a Image Processing and Computer Vision. $3 274051
650 2 4 $a Computer Appl. in Social and Behavioral Sciences. $3 274376
650 2 4 $a Computing Milieux. $3 275270
650 2 4 $a Security. $3 760527
700 1 $a Berlingerio, Michele. $3 837320
710 2 $a SpringerLink (Online service) $3 273601
773 0 $t Springer eBooks
830 0 $a Lecture notes in computer science ; $v 4891. $3 383229
830 0 $a Lecture notes in artificial intelligence. $3 822012
856 4 0 $u https://doi.org/10.1007/978-3-030-10928-8
950 $a Computer Science (Springer-11645)