| 000 -LEADER |
|---|
| fixed length control field |
a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
|---|
| fixed length control field |
240319b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
|---|
| International Standard Book Number |
9783031007835 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
|---|
| Classification number |
006.312 |
| Item number |
KOU |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Koutra, Danai |
| 245 ## - TITLE STATEMENT |
|---|
| Title |
Individual and collective graph mining : principles, algorithms, and applications |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
|---|
| Name of publisher, distributor, etc |
Springer, |
| Date of publication, distribution, etc |
2018 |
| Place of publication, distribution, etc |
Cham : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xi, 194 p. ; |
| Other physical details |
ill., (some col.), |
| Dimensions |
24 cm |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
59.99 |
| Price type code |
€ |
| Unit of pricing |
93.50 |
| 490 ## - SERIES STATEMENT |
|---|
| Series statement |
Synthesis Lectures on Data Mining and Knowledge Discovery ; |
| Volume number/sequential designation |
v14 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
|---|
| Bibliography, etc |
Includes bibliographical references. |
| 520 ## - SUMMARY, ETC. |
|---|
| Summary, etc |
Graphs naturally represent information ranging from links between web pages, to communication in email networks, to connections between neurons in our brains. These graphs often span billions of nodes and interactions between them. Within this deluge of interconnected data, how can we find the most important structures and summarize them? How can we efficiently visualize them? How can we detect anomalies that indicate critical events, such as an attack on a computer system, disease formation in the human brain, or the fall of a company? This book presents scalable, principled discovery algorithms that combine globality with locality to make sense of one or more graphs. In addition to fast algorithmic methodologies, we also contribute graph-theoretical ideas and models, and real-world applications in two main areas : Individual Graph Mining and Collective Graph Mining. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Data Mining |
|
|---|
| Topical term or geographic name as entry element |
Knowledge Discovery Statistics |
|
|---|
| Topical term or geographic name as entry element |
Graph Mining |
| 700 ## - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Faloutsos, Christos |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
|---|
| Source of classification or shelving scheme |
|
| Item type |
Books |