The Resource Big data analytics and knowledge discovery : 17th International Conference, DaWaK 2015, Valencia, Spain, September 1-4, 2015, Proceedings, Sanjay Madria, Takahiro Hara (eds.)

Big data analytics and knowledge discovery : 17th International Conference, DaWaK 2015, Valencia, Spain, September 1-4, 2015, Proceedings, Sanjay Madria, Takahiro Hara (eds.)

Label
Big data analytics and knowledge discovery : 17th International Conference, DaWaK 2015, Valencia, Spain, September 1-4, 2015, Proceedings
Title
Big data analytics and knowledge discovery
Title remainder
17th International Conference, DaWaK 2015, Valencia, Spain, September 1-4, 2015, Proceedings
Statement of responsibility
Sanjay Madria, Takahiro Hara (eds.)
Title variation
DaWaK 2015
Creator
Contributor
Editor
Subject
Genre
Language
eng
Summary
This book constitutes the refereed proceedings of the 17th International Conference on Data Warehousing and Knowledge Discovery, DaWaK 2015, held in Valencia, Spain, September 2015. The 31 revised full papers presented were carefully reviewed and selected from 90 submissions. The papers are organized in topical sections similarity measure and clustering; data mining; social computing; heterogeneos networks and data; data warehouses; stream processing; applications of big data analysis; and big data
Member of
Cataloging source
GW5XE
Dewey number
005.74
Illustrations
illustrations
Index
index present
Language note
English
LC call number
QA76.9.D3
Literary form
non fiction
http://bibfra.me/vocab/lite/meetingDate
2015
http://bibfra.me/vocab/lite/meetingName
DaWaK (Conference)
Nature of contents
dictionaries
http://library.link/vocab/relatedWorkOrContributorName
  • Madria, Sanjay
  • Hara, Takahiro
Series statement
  • Lecture notes in computer science,
  • LNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI
Series volume
9263
http://library.link/vocab/subjectName
  • Database management
  • Big data
  • Data mining
  • Big data
  • Data mining
  • Database management
  • Computer Science
  • Engineering & Applied Sciences
  • Computer Science
  • Database Management
  • Data Mining and Knowledge Discovery
  • Computer Appl. in Administrative Data Processing
  • Information Storage and Retrieval
  • Information Systems Applications (incl. Internet)
  • Computers
  • Computers
  • Computers
  • Computers
  • Data mining
  • Public administration
  • Information retrieval
  • Computers
  • Databases
Label
Big data analytics and knowledge discovery : 17th International Conference, DaWaK 2015, Valencia, Spain, September 1-4, 2015, Proceedings, Sanjay Madria, Takahiro Hara (eds.)
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-3-319-22729-0
Instantiates
Publication
Note
  • International conference proceedings
  • Includes author index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Intro; Preface; Organization; Contents; Similarity Measure and Clustering; Determining Query Readiness for Structured Data; 1 Introduction; 2 Formalizing Data Readiness Level; 2.1 Toll Booth Example -- Traffic Flow Identification; 2.2 Data Readiness Level: Intuition and Preliminaries; 2.3 The Relevance Dimension of DRL; 2.4 The Completeness Dimension of DRL; 2.5 Putting It Together: Data Readiness Level Tuples; 3 Improving Readiness Level of Data for Task at Hand; 3.1 Taxonomy of DRL-Improving Operators; 3.2 Illustration Using the Running Example; 4 Use Case: Marketing via Targeted Mailings
  • 5 Related Work6 Conclusion and Future Work; References; Efficient Cluster Detection by Ordered Neighborhoods; 1 Introduction; 2 Formal Properties; 2.1 Clustering in Neighborhoods; 2.2 Ordered Neighborhoods; 3 Mining the Neighborhoods; 3.1 Complexity Analysis; 4 Empirical Evaluation; 4.1 Experimental Setup; 4.2 Heterogeneous Datasets; 4.3 Scalability Results; 4.4 Real World Datasets; 5 Conclusion; References; Unsupervised Semantic and Syntactic Based Classification of Scientific Citations; 1 Introduction; 2 Related Work; 3 Citation Clustering; 3.1 Semantic-Based Model
  • 3.2 Syntactic-Based Model4 Experiments, Results and Evaluation; 5 Conclusion and Future Work; References; Data Mining; HI-Tree: Mining High Influence Patterns Using External and Internal Utility Values; 1 Introduction; 2 Related Work; 3 Preliminaries; 3.1 Online Frequent Itemsets Mining; 3.2 Influence Factor; 4 High Influence Tree (HI-Tree); 4.1 HI-Tree Structure; 4.2 HI-Tree Construction; 4.3 HI-Tree Mining; 5 Experimental Evaluation; 5.1 Varying Minimum Threshold; 5.2 Reduction Ratio; 5.3 Scalability Test and Rule Validation; 6 Conclusion and Future Work; References
  • Balancing Tree Size and Accuracy in Fast Mining of Uncertain Frequent Patterns1 Introduction and Related Works; 2 Background; 3 Our MUF-tree Structure; 4 Our MUF-growth Algorithm; 5 Evaluation Results; 5.1 Analytical Evaluation; 5.2 Empirical Evaluation; 6 Conclusions; References; Secure Outsourced Frequent Pattern Mining by Fully Homomorphic Encryption; 1 Introduction; 2 Related Works; 3 Preliminaries; 3.1 Frequent Pattern Mining Problem; 3.2 Secure Outsourced Mining by Fully Homomorphic Encryption; 3.3 A Variant of the Apriori Algorithm; 4 Secured Protocol Based on FHE for Pattern Mining
  • 5 Privacy Preserving Protocol for Pattern Mining5.1 The Notion of -Pattern Uncertainty; 5.2 Privacy Preserving Protocol for Counting Candidates; 6 Experimental Evaluation; 7 Conclusions and Future Work; References; Supervised Evaluation of Top-k Itemset Mining Algorithms; 1 Introduction; 2 Problem Statement and Algorithms; 2.1 Notation and Problem Statement; 2.2 Minimizing Noise (Asso); 2.3 Minimizing the Pattern Set Complexity (Hyper+); 2.4 Minimizing Multiple Cost Functions (PaNDa+ Framework); 3 Evaluation Methodology and Experiments; 3.1 Parameter Setting of Pattern Mining Algorithms
Dimensions
unknown
Extent
1 online resource (xiii, 418 pages)
File format
unknown
Form of item
online
Isbn
9783319227283
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
SpringerLink
Other control number
10.1007/978-3-319-22729-0
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)918570367
  • (OCoLC)ocn918570367
Label
Big data analytics and knowledge discovery : 17th International Conference, DaWaK 2015, Valencia, Spain, September 1-4, 2015, Proceedings, Sanjay Madria, Takahiro Hara (eds.)
Link
https://ezproxy.lib.ou.edu/login?url=http://link.springer.com/10.1007/978-3-319-22729-0
Publication
Note
  • International conference proceedings
  • Includes author index
Antecedent source
unknown
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Intro; Preface; Organization; Contents; Similarity Measure and Clustering; Determining Query Readiness for Structured Data; 1 Introduction; 2 Formalizing Data Readiness Level; 2.1 Toll Booth Example -- Traffic Flow Identification; 2.2 Data Readiness Level: Intuition and Preliminaries; 2.3 The Relevance Dimension of DRL; 2.4 The Completeness Dimension of DRL; 2.5 Putting It Together: Data Readiness Level Tuples; 3 Improving Readiness Level of Data for Task at Hand; 3.1 Taxonomy of DRL-Improving Operators; 3.2 Illustration Using the Running Example; 4 Use Case: Marketing via Targeted Mailings
  • 5 Related Work6 Conclusion and Future Work; References; Efficient Cluster Detection by Ordered Neighborhoods; 1 Introduction; 2 Formal Properties; 2.1 Clustering in Neighborhoods; 2.2 Ordered Neighborhoods; 3 Mining the Neighborhoods; 3.1 Complexity Analysis; 4 Empirical Evaluation; 4.1 Experimental Setup; 4.2 Heterogeneous Datasets; 4.3 Scalability Results; 4.4 Real World Datasets; 5 Conclusion; References; Unsupervised Semantic and Syntactic Based Classification of Scientific Citations; 1 Introduction; 2 Related Work; 3 Citation Clustering; 3.1 Semantic-Based Model
  • 3.2 Syntactic-Based Model4 Experiments, Results and Evaluation; 5 Conclusion and Future Work; References; Data Mining; HI-Tree: Mining High Influence Patterns Using External and Internal Utility Values; 1 Introduction; 2 Related Work; 3 Preliminaries; 3.1 Online Frequent Itemsets Mining; 3.2 Influence Factor; 4 High Influence Tree (HI-Tree); 4.1 HI-Tree Structure; 4.2 HI-Tree Construction; 4.3 HI-Tree Mining; 5 Experimental Evaluation; 5.1 Varying Minimum Threshold; 5.2 Reduction Ratio; 5.3 Scalability Test and Rule Validation; 6 Conclusion and Future Work; References
  • Balancing Tree Size and Accuracy in Fast Mining of Uncertain Frequent Patterns1 Introduction and Related Works; 2 Background; 3 Our MUF-tree Structure; 4 Our MUF-growth Algorithm; 5 Evaluation Results; 5.1 Analytical Evaluation; 5.2 Empirical Evaluation; 6 Conclusions; References; Secure Outsourced Frequent Pattern Mining by Fully Homomorphic Encryption; 1 Introduction; 2 Related Works; 3 Preliminaries; 3.1 Frequent Pattern Mining Problem; 3.2 Secure Outsourced Mining by Fully Homomorphic Encryption; 3.3 A Variant of the Apriori Algorithm; 4 Secured Protocol Based on FHE for Pattern Mining
  • 5 Privacy Preserving Protocol for Pattern Mining5.1 The Notion of -Pattern Uncertainty; 5.2 Privacy Preserving Protocol for Counting Candidates; 6 Experimental Evaluation; 7 Conclusions and Future Work; References; Supervised Evaluation of Top-k Itemset Mining Algorithms; 1 Introduction; 2 Problem Statement and Algorithms; 2.1 Notation and Problem Statement; 2.2 Minimizing Noise (Asso); 2.3 Minimizing the Pattern Set Complexity (Hyper+); 2.4 Minimizing Multiple Cost Functions (PaNDa+ Framework); 3 Evaluation Methodology and Experiments; 3.1 Parameter Setting of Pattern Mining Algorithms
Dimensions
unknown
Extent
1 online resource (xiii, 418 pages)
File format
unknown
Form of item
online
Isbn
9783319227283
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
c
Note
SpringerLink
Other control number
10.1007/978-3-319-22729-0
Other physical details
illustrations.
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
  • (OCoLC)918570367
  • (OCoLC)ocn918570367

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