Link Mining: Models, Algorithms, and Applications (Record no. 110648)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04769nam a22005055i 4500 |
| 001 - CONTROL NUMBER | |
| control field | 978-1-4419-6515-8 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | DE-He213 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20140220084510.0 |
| 007 - PHYSICAL DESCRIPTION FIXED FIELD--GENERAL INFORMATION | |
| fixed length control field | cr nn 008mamaa |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 100917s2010 xxu| s |||| 0|eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9781441965158 |
| -- | 978-1-4419-6515-8 |
| 024 7# - OTHER STANDARD IDENTIFIER | |
| Standard number or code | 10.1007/978-1-4419-6515-8 |
| Source of number or code | doi |
| 050 #4 - LIBRARY OF CONGRESS CALL NUMBER | |
| Classification number | QH324.2-324.25 |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | PSD |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | UB |
| Source | bicssc |
| 072 #7 - SUBJECT CATEGORY CODE | |
| Subject category code | SCI056000 |
| Source | bisacsh |
| 082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 570.285 |
| Edition number | 23 |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Yu, Philip S. |
| Relator term | editor. |
| 245 10 - TITLE STATEMENT | |
| Title | Link Mining: Models, Algorithms, and Applications |
| Medium | [electronic resource] / |
| Statement of responsibility, etc | edited by Philip S. Yu, Jiawei Han, Christos Faloutsos. |
| 264 #1 - | |
| -- | New York, NY : |
| -- | Springer New York : |
| -- | Imprint: Springer, |
| -- | 2010. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | X, 430p. 181 illus. |
| Other physical details | online resource. |
| 336 ## - | |
| -- | text |
| -- | txt |
| -- | rdacontent |
| 337 ## - | |
| -- | computer |
| -- | c |
| -- | rdamedia |
| 338 ## - | |
| -- | online resource |
| -- | cr |
| -- | rdacarrier |
| 347 ## - | |
| -- | text file |
| -- | |
| -- | rda |
| 505 0# - FORMATTED CONTENTS NOTE | |
| Formatted contents note | Link-Based Clustering -- Machine Learning Approaches to Link-Based Clustering -- Scalable Link-Based Similarity Computation and Clustering -- Community Evolution and Change Point Detection in Time-Evolving Graphs -- Graph Mining and Community Analysis -- A Survey of Link Mining Tasks for Analyzing Noisy and Incomplete Networks -- Markov Logic: A Language and Algorithms for Link Mining -- Understanding Group Structures and Properties in Social Media -- Time Sensitive Ranking with Application to Publication Search -- Proximity Tracking on Dynamic Bipartite Graphs: Problem Definitions and Fast Solutions -- Discriminative Frequent Pattern-Based Graph Classification -- Link Analysis for Data Cleaning and Information Integration -- Information Integration for Graph Databases -- Veracity Analysis and Object Distinction -- Social Network Analysis -- Dynamic Community Identification -- Structure and Evolution of Online Social Networks -- Toward Identity Anonymization in Social Networks -- Summarization and OLAP of Information Networks -- Interactive Graph Summarization -- InfoNetOLAP: OLAP and Mining of Information Networks -- Integrating Clustering with Ranking in Heterogeneous Information Networks Analysis -- Mining Large Information Networks by Graph Summarization -- Analysis of Biological Information Networks -- Finding High-Order Correlations in High-Dimensional Biological Data -- Functional Influence-Based Approach to Identify Overlapping Modules in Biological Networks -- Gene Reachability Using Page Ranking on Gene Co-expression Networks. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | With the recent flourishing research activities on Web search and mining, social network analysis, information network analysis, information retrieval, link analysis, and structural data mining, research on link mining has been rapidly growing, forming a new field of data mining. Traditional data mining focuses on "flat" or “isolated” data in which each data object is represented as an independent attribute vector. However, many real-world data sets are inter-connected, much richer in structure, involving objects of heterogeneous types and complex links. Hence, the study of link mining will have a high impact in various important applications such as Web and text mining, social network analysis, collaborative filtering, and bioinformatics. Link Mining: Models, Algorithms and Applications focuses on the theory and techniques as well as the related applications for link mining, especially from an interdisciplinary point of view. Due to the high popularity of linkage data, extensive applications ranging from governmental organizations to commercial businesses to people's daily life call for exploring the techniques of mining linkage data. This book provides a comprehensive coverage of the link mining models, techniques and applications. Each chapter is contributed from some well known researchers in the field. Link Mining: Models, Algorithms and Applications is designed for researchers, teachers, and advanced-level students in computer science. This book is also suitable for practitioners in industry. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Medicine. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data mining. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Bioinformatics. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Biology |
| General subdivision | Data processing. |
| 650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Biomedicine. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Bioinformatics. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Data Mining and Knowledge Discovery. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computational Biology/Bioinformatics. |
| 650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Computer Appl. in Life Sciences. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Han, Jiawei. |
| Relator term | editor. |
| 700 1# - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Faloutsos, Christos. |
| Relator term | editor. |
| 710 2# - ADDED ENTRY--CORPORATE NAME | |
| Corporate name or jurisdiction name as entry element | SpringerLink (Online service) |
| 773 0# - HOST ITEM ENTRY | |
| Title | Springer eBooks |
| 776 08 - ADDITIONAL PHYSICAL FORM ENTRY | |
| Display text | Printed edition: |
| International Standard Book Number | 9781441965141 |
| 856 40 - ELECTRONIC LOCATION AND ACCESS | |
| Uniform Resource Identifier | http://dx.doi.org/10.1007/978-1-4419-6515-8 |
| 912 ## - | |
| -- | ZDB-2-SBL |
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