東華大學圖書館 |

語系: 繁體中文

說明(常見問題)

回圖書館首頁

手機版館藏查詢

登入

回首頁

切換: 標籤 | MARC模式 | ISBD

Heterogeneous information network an...

Shi, Chuan.

FindBook

Google Book

Amazon

博客來

Heterogeneous information network analysis and applications

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Heterogeneous information network analysis and applications/ by Chuan Shi, Philip S. Yu.
作者:	Shi, Chuan.
其他作者:	Yu, Philip S.
出版者:	Cham :Springer International Publishing : : 2017.,
面頁冊數:	ix, 227 p. :ill., digital ;24 cm.
內容註:	1. Introduction -- 2. Summarization of the developments -- 3.Uniform relevance measure of heterogeneous objects -- 4. Path based Ranking -- 5. Ranking based Clustering -- 6. Recommendation with heterogeneous information -- 7. Information fusion with heterogeneous network -- 8. Prototype system -- 9. Future research directions -- 10. Conclusion.
Contained By:	Springer eBooks
標題:	Data mining. -
電子資源:	http://dx.doi.org/10.1007/978-3-319-56212-4
ISBN:	9783319562124

Heterogeneous information network analysis and applications
Shi, Chuan.

Heterogeneous information network analysis and applications[electronic resource] /by Chuan Shi, Philip S. Yu. - Cham :Springer International Publishing :2017. - ix, 227 p. :ill., digital ;24 cm. - Data analytics,2520-1859. - Data analytics..

1. Introduction -- 2. Summarization of the developments -- 3.Uniform relevance measure of heterogeneous objects -- 4. Path based Ranking -- 5. Ranking based Clustering -- 6. Recommendation with heterogeneous information -- 7. Information fusion with heterogeneous network -- 8. Prototype system -- 9. Future research directions -- 10. Conclusion.

This book offers researchers an understanding of the fundamental issues and a good starting point to work on this rapidly expanding field. It provides a comprehensive survey of current developments of heterogeneous information network. It also presents the newest research in applications of heterogeneous information networks to similarity search, ranking, clustering, recommendation. This information will help researchers to understand how to analyze networked data with heterogeneous information networks. Common data mining tasks are explored, including similarity search, ranking, and recommendation. The book illustrates some prototypes which analyze networked data. Professionals and academics working in data analytics, networks, machine learning, and data mining will find this content valuable. It is also suitable for advanced-level students in computer science who are interested in networking or pattern recognition.

ISBN: 9783319562124

Standard No.: 10.1007/978-3-319-56212-4doiSubjects--Topical Terms:

562972
Data mining.

LC Class. No.: QA76.9.D343

Dewey Class. No.: 006.312

Heterogeneous information network analysis and applications
LDR:02294nmm a2200337 a 4500 001 2100859
003 DE-He213
005 20170525065916.0
006 m d
007 cr nn 008maaau
008 180119s2017 gw s 0 eng d
020 $a 9783319562124 $q (electronic bk.)
020 $a 9783319562117 $q (paper)
024 7 $a 10.1007/978-3-319-56212-4 $2 doi
035 $a 978-3-319-56212-4
040 $a GP $c GP
041 0 $a eng
050 4 $a QA76.9.D343
072 7 $a UNF $2 bicssc
072 7 $a UYQE $2 bicssc
072 7 $a COM021030 $2 bisacsh
082 0 4 $a 006.312 $2 23
090 $a QA76.9.D343 $b S555 2017
100 1 $a Shi, Chuan. $3 3242867
245 1 0 $a Heterogeneous information network analysis and applications $h [electronic resource] / $c by Chuan Shi, Philip S. Yu.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2017.
300 $a ix, 227 p. : $b ill., digital ; $c 24 cm.
490 1 $a Data analytics, $x 2520-1859
505 0 $a 1. Introduction -- 2. Summarization of the developments -- 3.Uniform relevance measure of heterogeneous objects -- 4. Path based Ranking -- 5. Ranking based Clustering -- 6. Recommendation with heterogeneous information -- 7. Information fusion with heterogeneous network -- 8. Prototype system -- 9. Future research directions -- 10. Conclusion.
520 $a This book offers researchers an understanding of the fundamental issues and a good starting point to work on this rapidly expanding field. It provides a comprehensive survey of current developments of heterogeneous information network. It also presents the newest research in applications of heterogeneous information networks to similarity search, ranking, clustering, recommendation. This information will help researchers to understand how to analyze networked data with heterogeneous information networks. Common data mining tasks are explored, including similarity search, ranking, and recommendation. The book illustrates some prototypes which analyze networked data. Professionals and academics working in data analytics, networks, machine learning, and data mining will find this content valuable. It is also suitable for advanced-level students in computer science who are interested in networking or pattern recognition.
650 0 $a Data mining. $3 562972
650 0 $a Computer networks. $3 539554
650 1 4 $a Computer Science. $3 626642
650 2 4 $a Data Mining and Knowledge Discovery. $3 898250
650 2 4 $a Artificial Intelligence (incl. Robotics) $3 890894
650 2 4 $a Pattern Recognition. $3 891045
650 2 4 $a Communications Engineering, Networks. $3 891094
650 2 4 $a Computer Communication Networks. $3 775497
700 1 $a Yu, Philip S. $3 622967
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer eBooks
830 0 $a Data analytics. $3 3242868
856 4 0 $u http://dx.doi.org/10.1007/978-3-319-56212-4
950 $a Computer Science (Springer-11645)