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Data Warehousing and Knowledge Discovery

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Cover of 'Data Warehousing and Knowledge Discovery'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 An Approach on ETL Attached Data Quality Management
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    Chapter 2 Quality Measures for ETL Processes
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    Chapter 3 A Logical Model for Multiversion Data Warehouses
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    Chapter 4 OntoWarehousing – Multidimensional Design Supported by a Foundational Ontology: A Temporal Perspective
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    Chapter 5 Modeling and Querying Data Warehouses on the Semantic Web Using QB4OLAP
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    Chapter 6 Extending Drill-Down through Semantic Reasoning on Indicator Formulas
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    Chapter 7 An OLAP-Based Approach to Modeling and Querying Granular Temporal Trends
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    Chapter 8 Real-Time Data Warehousing: A Rewrite/Merge Approach
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    Chapter 9 Towards next generation BI systems : the analytical metadata challenge
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    Chapter 10 Mining Fuzzy Contextual Preferences
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    Chapter 11 BLIMP: A Compact Tree Structure for Uncertain Frequent Pattern Mining
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    Chapter 12 Discovering Statistically Significant Co-location Rules in Datasets with Extended Spatial Objects
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    Chapter 13 Discovering Community Preference Influence Network by Social Network Opinion Posts Mining
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    Chapter 14 Computing Hierarchical Skyline Queries “On-the-Fly” in a Data Warehouse
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    Chapter 15 Impact of Content Novelty on the Accuracy of a Group Recommender System
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    Chapter 16 Optimizing Queue-Based Semi-Stream Joins with Indexed Master Data
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    Chapter 17 Parallel Co-clustering with Augmented Matrices Algorithm with Map-Reduce
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    Chapter 18 Processing OLAP Queries over an Encrypted Data Warehouse Stored in the Cloud
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    Chapter 19 Reducing Multidimensional Data
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    Chapter 20 Towards an OLAP Environment for Column-Oriented Data Warehouses
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    Chapter 21 Interval OLAP: Analyzing Interval Data
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    Chapter 22 Improving the Processing of DW Star-Queries under Concurrent Query Workloads
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    Chapter 23 Building Smart Cubes for Reliable and Faster Access to Data
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    Chapter 24 Optimizing Reaction and Processing Times in Automotive Industry’s Quality Management
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    Chapter 25 Using Closed n-set Patterns for Spatio-Temporal Classification
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    Chapter 26 Short Text Classification Using Semantic Random Forest
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    Chapter 27 Data Warehousing and Knowledge Discovery
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    Chapter 28 Mining Interesting “Following” Patterns from Social Networks
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    Chapter 29 A Novel Approach Using Context-Based Measure for Matching Large Scale Ontologies
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    Chapter 30 ActMiner: Discovering Location-Specific Activities from Community-Authored Reviews
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    Chapter 31 A Scalable Algorithm for Banded Pattern Mining in Multi-dimensional Zero-One Data
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    Chapter 32 Approximation of Frequent Itemset Border by Computing Approximate Minimal Hypergraph Transversals
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    Chapter 33 Clustering Based on Sequential Multi-Objective Games
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    Chapter 34 Opening up Data Analysis for Medical Health Services: Cancer Survival Analysis with CARESS
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    Chapter 35 “Real-time” Instance Selection for Biomedical Data Classification
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    Chapter 36 Mining Churning Factors in Indian Telecommunication Sector Using Social Media Analytics
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    Chapter 37 Drift Detector for Memory-Constrained Environments
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    Chapter 38 Mean Shift Clustering Algorithm for Data with Missing Values
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    Chapter 39 Mining Recurrent Concepts in Data Streams Using the Discrete Fourier Transform
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    Chapter 40 Semi-Supervised Learning to Support the Exploration of Association Rules
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    Chapter 41 Parameter-Free Extended Edit Distance
  43. Altmetric Badge
    Chapter 42 VGEN: Fast Vertical Mining of Sequential Generator Patterns
Attention for Chapter 9: Towards next generation BI systems : the analytical metadata challenge
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Chapter title
Towards next generation BI systems : the analytical metadata challenge
Chapter number 9
Book title
Data Warehousing and Knowledge Discovery
Published in
Lecture notes in computer science, November 2014
DOI 10.1007/978-3-319-10160-6_9
Book ISBNs
978-3-31-910159-0, 978-3-31-910160-6

Varga, Jovan, Jovan Varga, Oscar Romero, Torben Bach Pedersen, Christian Thomsen

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 3%
Germany 1 3%
Brazil 1 3%
Unknown 34 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Student > Master 8 22%
Researcher 4 11%
Professor > Associate Professor 3 8%
Student > Bachelor 3 8%
Other 6 16%
Unknown 4 11%
Readers by discipline Count As %
Computer Science 23 62%
Business, Management and Accounting 3 8%
Arts and Humanities 1 3%
Unspecified 1 3%
Economics, Econometrics and Finance 1 3%
Other 3 8%
Unknown 5 14%