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00000cam a2200000Mu 4500 |
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EBOOKCENTRAL_on1347029277 |
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OCoLC |
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20240329122006.0 |
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m o d |
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cr ||||||||||| |
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221015s2017 xx o ||| 0 eng d |
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|a EBLCP
|b eng
|c EBLCP
|d REDDC
|d EBLCP
|d OCLCF
|d OCLCQ
|d OCLCO
|d OCLCL
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| 020 |
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|a 9788793379848
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| 020 |
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|a 8793379846
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| 035 |
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|a (OCoLC)1347029277
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| 050 |
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4 |
|a QA76.9.D343
|b .K863 2016
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| 082 |
0 |
4 |
|a 006.3/12
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| 049 |
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|a UAMI
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| 100 |
1 |
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|a Kumbhar, V. S.
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| 245 |
1 |
0 |
|a Web Mining
|h [electronic resource] :
|b A Synergic Approach Resorting to Classifications and Clustering.
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| 260 |
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|a Aalborg :
|b River Publishers,
|c 2017.
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| 300 |
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|a 1 online resource (232 p.).
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| 490 |
1 |
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|a River Publishers Series in Information Science and Technology Ser.
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| 500 |
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|a Description based upon print version of record.
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| 505 |
0 |
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|a Front Cover -- Half Title -- RIVER PUBLISHERS SERIES IN INFORMATION SCIENCE AND TECHNOLOGY -- Title Page -- Web Mining: A Synergic Approach Resorting to Classifications and Clustering -- Copyright Page -- Contents -- Preface -- Acknowledgment -- List of Figures -- List of Tables -- List of Graphs -- List of Abbreviations -- Chapter 1 -- Introduction -- 1.1 Basic Notion of Data Mining -- 1.2 Knowledge Discovery:The Very Rationale Behind Data Mining -- 1.3 Challenges in the Development of Data Mining -- 1.3.1 Scalability -- 1.3.2 High Dimensionality -- 1.3.3 Heterogeneous and Complex Data
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| 505 |
8 |
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|a 1.3.4 Data Ownership and Distribution -- 1.3.5 Non-Traditional Analysis -- 1.4 Importance of Data Mining -- 1.5 Classification of Data Mining Systems -- 1.5.1 The Databases Mined -- 1.5.2 The Knowledge Mined -- 1.5.3 The Techniques Utilized -- 1.5.4 The Application Adopted -- 1.6 Generic Architecture of Data Mining System -- 1.7 Major Issues in Data Mining -- 1.7.1 Mining Methodology and User Interaction Issues -- 1.7.2 Performance Issues -- 1.7.3 Issues Relating to the Diversity of Database Types -- 1.8 Data Mining Strategies -- 1.8.1 Classification -- 1.8.2 Association -- 1.8.3 Clustering
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| 505 |
8 |
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|a 1.8.3.1 k-Means algorithm -- 1.8.4 Estimation -- 1.9 Data Mining: Ever Increasing Range of Applications -- 1.9.1 Games -- 1.9.2 Business -- 1.9.3 Science and Engineering -- 1.9.4 Human Rights -- 1.9.5 Medical Data Mining -- 1.9.6 Spatial Data Mining -- 1.9.7 Challenges in Spatial Mining -- 1.9.8 Temporal Data Mining -- 1.9.9 Sensor Data Mining -- 1.9.10 Visual Data Mining -- 1.9.11 Music Data Mining -- 1.9.12 Pattern Mining -- 1.9.13 Subject-based Data Mining -- 1.9.14 Knowledge Grid -- 1.10 Trends in Data Mining -- 1.10.1 Application Exploration
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| 505 |
8 |
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|a 1.10.2 Scalable and Interactive Data Mining Methods -- 1.10.3 Integration of Data Mining with Database Systems, Data Warehouse Systems, and Web Database Systems -- 1.10.4 Standardization of Data Mining Query Language -- 1.10.5 Visual Data Mining -- 1.10.6 New Methods for Mining Complex Types of Data -- 1.10.7 Biological Data Mining -- 1.10.8 Data Mining and Software Engineering -- 1.10.9 Web Mining -- 1.10.10 Distributed Data Mining -- 1.10.11 Real-Time Data Mining -- 1.10.12 Multi-Database Data Mining -- 1.10.13 Privacy Protection and Information Security in Data Mining
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| 505 |
8 |
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|a 1.11 Classification Techniques in Data Mining -- 1.11.1 Definition of the Classification -- 1.11.2 Issues Regarding Classification -- 1.11.3 Evaluation Methods for Classification -- 1.11.4 Classifications Techniques -- 1.11.4.1 Tree structure -- 1.11.4.2 Rule-based algorithm -- 1.11.4.3 Distance-based algorithms -- 1.11.4.4 Neural networks-based algorithms -- 1.11.4.5 Statistical-based algorithms -- 1.12 Applications of Classifications -- 1.12.1 Target Marketing -- 1.12.2 Disease Diagnosis -- 1.12.3 Supervised Event Detection -- 1.12.4 Multimedia Data Analysis -- 1.12.5 Biological Data Analysis
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| 500 |
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|a 1.12.6 Document Categorization and Filtering
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| 590 |
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|a ProQuest Ebook Central
|b Ebook Central Academic Complete
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| 650 |
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0 |
|a Web databases.
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| 650 |
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0 |
|a Data mining.
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| 650 |
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0 |
|a Cluster analysis.
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| 650 |
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6 |
|a Bases de données sur le Web.
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| 650 |
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6 |
|a Exploration de données (Informatique)
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| 650 |
|
6 |
|a Classification automatique (Statistique)
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| 650 |
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7 |
|a Cluster analysis
|2 fast
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| 650 |
|
7 |
|a Data mining
|2 fast
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| 650 |
|
7 |
|a Web databases
|2 fast
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| 700 |
1 |
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|a Oza, K. S.
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| 700 |
1 |
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|a Kamat, R. K.
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| 758 |
|
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|i has work:
|a Web mining (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCYJHCq8C3pyGgPRKk4pqMd
|4 https://id.oclc.org/worldcat/ontology/hasWork
|
| 776 |
0 |
8 |
|i Print version:
|a Kumbhar, V. S.
|t Web Mining
|d Aalborg : River Publishers,c2017
|
| 830 |
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0 |
|a River Publishers Series in Information Science and Technology Ser.
|
| 856 |
4 |
0 |
|u https://ebookcentral.uam.elogim.com/lib/uam-ebooks/detail.action?docID=30169259
|z Texto completo
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| 938 |
|
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|a ProQuest Ebook Central
|b EBLB
|n EBL30169259
|
| 994 |
|
|
|a 92
|b IZTAP
|
