2012Unpublished venueRequires access

On the foundations of probabilistic information integration

Fereidoon Sadri

Open publisher page 10 citations

Abstract

Information integration has been a subject of research for several decades and still remains a very active research area. Many new applications depend or benefit from large scale integration. Examples include large research projects in life sciences, need for data sharing among government agencies, reliance of corporations on business intelligence (which requires data integration from many heterogeneous sources), and integration of information on the web. The importance of information integration with uncertainty has been observed in recent years. Frequently, information from multiple sources are uncertain and possibly inconsistent. Further the process of integration often depends on approximate schema mappings, another source of uncertainty. An integration system is useful only to the extent that the information it produces can be trusted. Hence, providing a measure of certainty for integrated information is of crucial importance in many important applications.

About this research paper

What this paper is about

Information integration has been a subject of research for several decades and still remains a very active research area. Many new applications depend or benefit from large scale integration. Examples include large research projects in life sciences, need for data sharing among government agencies, reliance of corporations on business intelligence (which requires data integration from many heterogeneous sources), and integration of information on the web. The importance of information integration with uncertainty has been observed in recent years. Frequently, information from multiple sources are uncertain and possibly inconsistent. Further the process of integration often depends on approximate schema mappings, another source of uncertainty. An integration system is useful only to the extent that the information it produces can be trusted. Hence, providing a measure of certainty for integrated information is of crucial importance in many important applications.

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OpenAlex reports 10 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Information integration has been a subject of research for several decades and still remains a very active research area. Many new applications depend or benefit from large scale integration. Examples include large research projects in life sciences, need for data sharing among government agencies, reliance of corporations on business intelligence (which requires data integration from many heterogeneous sources), and integration of information on the web. The importance of information integration with uncertainty has been observed in recent years. Frequently, information from multiple sources are uncertain and possibly inconsistent. Further the process of integration often depends on approximate schema mappings, another source of uncertainty. An integration system is useful only to the extent that the information it produces can be trusted. Hence, providing a measure of certainty for integrated information is of crucial importance in many important applications.

Key concepts: Information integration, Data integration, Computer science, Probabilistic logic, Information sharing, Schema (genetic algorithms), Enterprise information integration, Certainty

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