Preference-based Spatial Co-location Pattern Mining (Record no. 179180)

MARC details
000 -LEADER
fixed length control field 04209nam a22005655i 4500
001 - CONTROL NUMBER
control field 978-981-16-7566-9
003 - CONTROL NUMBER IDENTIFIER
control field DE-He213
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20240423125541.0
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 220104s2022 si | s |||| 0|eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9789811675669
-- 978-981-16-7566-9
024 7# - OTHER STANDARD IDENTIFIER
Standard number or code 10.1007/978-981-16-7566-9
Source of number or code doi
050 #4 - LIBRARY OF CONGRESS CALL NUMBER
Classification number QA75.5-76.95
072 #7 - SUBJECT CATEGORY CODE
Subject category code UY
Source bicssc
072 #7 - SUBJECT CATEGORY CODE
Subject category code COM000000
Source bisacsh
072 #7 - SUBJECT CATEGORY CODE
Subject category code UY
Source thema
082 04 - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 004
Edition number 23
100 1# - MAIN ENTRY--PERSONAL NAME
Personal name Wang, Lizhen.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
245 10 - TITLE STATEMENT
Title Preference-based Spatial Co-location Pattern Mining
Medium [electronic resource] /
Statement of responsibility, etc by Lizhen Wang, Yuan Fang, Lihua Zhou.
250 ## - EDITION STATEMENT
Edition statement 1st ed. 2022.
264 #1 -
-- Singapore :
-- Springer Nature Singapore :
-- Imprint: Springer,
-- 2022.
300 ## - PHYSICAL DESCRIPTION
Extent XVI, 294 p. 1 illus.
Other physical details online resource.
336 ## -
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-- txt
-- rdacontent
337 ## -
-- computer
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-- rdamedia
338 ## -
-- online resource
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347 ## -
-- text file
-- PDF
-- rda
490 1# - SERIES STATEMENT
Series statement Big Data Management,
International Standard Serial Number 2522-0187
505 0# - FORMATTED CONTENTS NOTE
Formatted contents note Chapter 1: Introduction -- Chapter 2: Maximal Prevalent Co-location Patterns -- Chapter 3: Maximal Sub-prevalent Co-location Patterns -- Chapter 4: SPI-Closed Prevalent Co-location Patterns -- Chapter 5: Top-k Probabilistically Prevalent Co-location Patterns -- Chapter 6: Non-Redundant Prevalent Co-location Patterns -- Chapter 7: Dominant Spatial Co-location Patterns -- Chapter 8: High Utility Co-location Patterns -- Chapter 9: High Utility Co-location Patterns with Instance Utility -- Chapter 10: Interactively Post-mining User-preferred Co-location Pat-terns with a Probabilistic Model -- Chapter 11: Vector-Degree: A General Similarity Measure for Spatial Co-Location Patterns.
520 ## - SUMMARY, ETC.
Summary, etc The development of information technology has made it possible to collect large amounts of spatial data on a daily basis. It is of enormous significance when it comes to discovering implicit, non-trivial and potentially valuable information from this spatial data. Spatial co-location patterns reveal the distribution rules of spatial features, which can be valuable for application users. This book provides commercial software developers with proven and effective algorithms for detecting and filtering these implicit patterns, and includes easily implemented pseudocode for all the algorithms. Furthermore, it offers a basis for further research in this promising field. Preference-based co-location pattern mining refers to mining constrained or condensed co-location patterns instead of mining all prevalent co-location patterns. Based on the authors’ recent research, the book highlights techniques for solving a range of problems in this context, including maximal co-location pattern mining, closed co-location pattern mining, top-k co-location pattern mining, non-redundant co-location pattern mining, dominant co-location pattern mining, high utility co-location pattern mining, user-preferred co-location pattern mining, and similarity measures between spatial co-location patterns. Presenting a systematic, mathematical study of preference-based spatial co-location pattern mining, this book can be used both as a textbook for those new to the topic and as a reference resource for experienced professionals.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer science.
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Blockchains (Databases).
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data protection.
650 14 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer Science.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Blockchain.
650 24 - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Data and Information Security.
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Fang, Yuan.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
700 1# - ADDED ENTRY--PERSONAL NAME
Personal name Zhou, Lihua.
Relator term author.
Relator code aut
-- http://id.loc.gov/vocabulary/relators/aut
710 2# - ADDED ENTRY--CORPORATE NAME
Corporate name or jurisdiction name as entry element SpringerLink (Online service)
773 0# - HOST ITEM ENTRY
Title Springer Nature eBook
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9789811675652
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9789811675676
776 08 - ADDITIONAL PHYSICAL FORM ENTRY
Display text Printed edition:
International Standard Book Number 9789811675683
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE
Uniform title Big Data Management,
-- 2522-0187
856 40 - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1007/978-981-16-7566-9">https://doi.org/10.1007/978-981-16-7566-9</a>
912 ## -
-- ZDB-2-SCS
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942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type eBooks-CSE-Springer

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