Generational analysis of tension and entropy in data structures: impact on automatic data integration and on the semantic web

Rohn, Eli

doi:10.1007/s10115-010-0314-z

Cited by 2 publications

(1 citation statement)

References 37 publications

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“…Two successive articles [31,32] performed an extensive literature review and analysis of DDLs from the 1950's to date. They conclude that existing DDLs are indistinguishable when their variety is analyzed and that all DDLs have almost identical expressive power in terms of information bits.…”

Section: Data Integration and Cas Principlesmentioning

confidence: 99%

CAS-Based Approach for Automatic Data Integration

Rohn

2013

AJOR

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Research of automatic integration of structured and semi-structured data has not resulted in success over the past fifty years. No theory of data integration exists. It is unknown what the theoretical necessary requirements are, to fully support automatic data integration from autonomous heterogeneous data sources. Therefore, it is not possible to objectively evaluate if and how much new algorithms, techniques, and specifically Data Definition Languages, move towards meeting such theoretical requirements. To overcome the serious reverse salient the field and industry are in, it will be helpful if a data integration theory would be developed. This article proposes a new look at data integration by using complex adaptive systems principles to analyze current shortcomings and propose a direction that may lead to a data integration theory.

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Section: Data Integration and Cas Principlesmentioning

confidence: 99%

CAS-Based Approach for Automatic Data Integration

Rohn

2013

AJOR

Self Cite

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Exploring the Symbiosis: Dynamic Programming and its Relationship with Data Structures

Vadiyala,

Baddam

2018

Asian j. appl. sci. eng.

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Dynamic Programming and Data Structures are two cornerstones of computer science and software development. While they are often studied independently, understanding their intricate relationship can lead to more efficient algorithm design and problem-solving. In this article, we will delve into the symbiotic connection between Dynamic Programming and Data Structures, exploring how they complement each other and contribute to the optimization of algorithmic solutions. The field of algorithmic problem-solving is dominated by dynamic programming (DP), recognized for its ability to optimize complex computations. DP is a cornerstone in this field. An investigation into dynamic programming will be carried out in this article, which will dissect its essential ideas and potential applications. In addition to providing a simple explanation, the article dives into the mutually beneficial relationship between Dynamic Programming and various data structures. It sheds light on using arrays, linked lists, trees, graphs, and other data structures to achieve optimal problem-solving. Concrete examples of the application of DP in conjunction with various data structures are provided via real-world case studies. These case studies include the Fibonacci sequence as well as Dijkstra's Algorithm. The article offers a complete guide for developers and fans eager to grasp the full power of Dynamic Programming in conjunction with data structures, which also digs into optimization strategies, obstacles, and future trends.

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Generational analysis of tension and entropy in data structures: impact on automatic data integration and on the semantic web

Cited by 2 publications

References 37 publications

CAS-Based Approach for Automatic Data Integration

CAS-Based Approach for Automatic Data Integration

Exploring the Symbiosis: Dynamic Programming and its Relationship with Data Structures

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