Filtering the Web to Feed Data Warehouses

by Witold Abramowicz, Pawel J. Kalczynski, Krzysztof Wecel

Overview

Information is a key factor in business today, and data warehousing has become a major activity in the development and management of information systems to support the proper flow of information. Unfortunately, the majority of information systems are based on structured information stored in organizational databases, which means that the company is isolated from the business environment by concentrating on their internal data sources only. It is therefore vital that organizations take advantage of external business information, which can be retrieved from Internet services and mechanically organized within the existing information structures. Such a continuously extending integrated collection of documents and data could facilitate decision-making processes in the organization. Filtering the Web to Feed Data Warehouses discusses areas such as:

- how to use data warehouse for filtering Web content

- how to retrieve relevant information from diverse sources on the Web

- how to handle the time aspect

- how to mechanically establish links among data warehouse structures and documents filtered from external sources

- how to use collected information to increase corporate knowledge

and gives a comprehensive example, illustrating the idea of supplying data warehouses with relevant information filtered from the Web.

Product Details

ISBN-13:	9781447111078
Publisher:	Springer London
Publication date:	09/10/2012
Edition description:	Softcover reprint of the original 1st ed. 2002
Pages:	267
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

1 Introduction.- 1.1 Information Systems.- 1.2 Information Filtering Systems.- 1.3 Database Systems.- 1.4 Organization of this Book.- 2 Data Warehouse: Corporate Knowledge Repository.- 2.1 Introduction.- 2.2 Data Warehouse Definition and Features.- 2.3 Data Warehouse System.- 2.4 Deploying Data Warehouse in the Organization.- 2.5 Knowledge Management in Data Warehouses.- 2.6 Evolution of the Data Warehouse.- 2.7 Chapter Summary.- 2.8 References.- 3 Knowledge Representation Standards.- 3.1 Introduction.- 3.2 Markup Languages.- 3.3 Dublin Core.- 3.4 Warwick Framework.- 3.5 Meta Content Framework.- 3.6 Resource Description Framework.- 3.7 Common Warehouse Metamodel.- 3.8 Chapter Summary.- 3.9 References.- 4 Information Filtering And Retrieval From Web Sources.- 4.1 Introduction.- 4.2 Information Retrieval Systems.- 4.3 Information Filtering Systems.- 4.4 Internet Sources of Business Information.- 4.5 Filtering the Web to Feed Business Information Systems.- 4.6 Chapter Summary.- 4.7 References.- 5 Enhanced Data Warehouse.- 5.1 Introduction.- 5.2 Justification of the Need for Integration.- 5.3 Preliminary Vision of the System.- 5.4 Software Agents.- 5.5 Proposed Solution: enhanced Data Warehouse.- 5.6 Formal Model of eDW.- 5.7 System Implementation.- 5.8 Chapter Summary.- 5.9 References.- 6 Profiling.- 6.1 Introduction.- 6.2 Personalization and Data Warehouse Profiles.- 6.3 Algorithms Specification.- 6.4 Profiling Server.- 6.5 Chapter Summary.- 6.6 References.- 7 Source Exploitation.- 7.1 Introduction.- 7.2 Sample Business Content Providers.- 7.3 Information Ants to Filter Information from Internet Sources.- 7.4 Indexing Parser.- 7.5 Transparent Filtering in the eDW System.- 7.6 Chapter Summary.- 7.7 References.- 8 Building Data Warehouse Library.- 8.1 Introduction.- 8.2 Time Indexing.- 8.3 Experiment with Time Indexing.- 8.4 Future Trends: Multimedia Indexing.- 8.5 Chapter Summary.- 8.6 References.- 9 Context Queries And Enhanced Reports.- 9.1 Introduction.- 9.2 Context Queries.- 9.3 enhanced Report.- 9.4 Reporting Application.- 9.5 Histograms: The Helpful Tool for Analysis.- 9.6 Chapter Summary.- 9.7 References.- 10 Conclusions.- 10.1 Concluding Remarks.- 10.2 Improvements.- 10.3 Open Issues and Future Work.