Artificial Intelligence & Data Warehouses
Artificial Intelligence and Data Warehousing
As the complexity and structure of databases grows as a result of enterprise-class data warehouses being able to interpret and use unstructured content (Doan, Halevy, 2005) there is a corresponding need for building linguistic models out of semantic data using artificial intelligence (AI) (Fortuna, Mohorcic, 2009). The techniques of latent semantic indexing (LSI) and contextual factor analysis are increasingly being used to find patterns in unstructured data within data warehouses (Doan, Halevy, 2005). Artificial Intelligence is also found in constraint-based approaches to defining complex Structured Query Language (SQL) systems as the path to complete queries can be optimized over time. All of these examples illustrate how critical AI is today in the managing of data warehouses that are comprised of multiple sources of data, some structured and some unstructured. The use of constraint-based modeling in conjunction with semantic query and modeling will significantly streamline the use of data warehouses, yielding insights not possible from only working with structured data.
Just as AI is significantly changing how data warehousing is being used as a strategic resource in companies, it is also fundamentally changing the nature of business today. Most significantly, the use of LSI technologies to create more effective insights into how to improve customer service as evidenced by the use of AI was part of Decision Support Systems (DSS) (Phillips-Wren, Mora, Forgionne, Gupta, 2009) is growing. Second, the creation of ontological databases that aligns to person's roles (Pinto, Marques, Santos, 2009) is also now possible. This translates into the use of AI to provide contextual guidance to decision makers based on their previous preferences and previous patterns of decisions, making DSS results optimized (Phillips-Wren, Mora, Forgionne, Gupta, 2009).
References
AnHai Doan, & Alon Y Halevy. (2005). Semantic-Integration Research in the Database Community: A Brief Survey. AI Magazine, 26(1), 83-94.
Fortuna, C., & Mohorcic, M.. (2009). Trends in the development of communication networks: Cognitive networks. Computer Networks, 53(9), 1354.
Phillips-Wren, G., Mora, M., Forgionne, G., & Gupta, J.. (2009). An integrative evaluation framework for intelligent decision support systems. European Journal of Operational Research, 195(3), 642.
Pinto, F., Marques, A., & Santos, M.. (2009). Ontology-supported database marketing. Journal of Database Marketing & Customer Strategy Management, 16(2), 76-91.
Artificial Intelligence Intelligence is the ability to learn about, to learn from and understand and interact with one's environment. Artificial intelligence is the intelligence of machines and is a multidisciplinary field which involves psychology, cognitive science, and neuroscience and computer science. It enables machines to become capable of doing those things which the human mind can do. Though the folklore of artificial intelligence dates back to a long time ago, it
Artificial Intelligence (AI) is the science and art of developing machines that simulate human intelligence. AI is frequently used for routine tasks that would normally involve human skills, such as visual perception, speech-recognition, and decision making. To me, Apple's Siri application is a good example of commonly-used AI technology. AI is particularly useful in the medical field, as it has allowed for better monitoring of patients combined with a more
IV-3). Each of these topics represents a crucial part of the larger evacuation plan, because as will be discussed in greater detail below, each single element of the plan influences and affects every other. All of this information should already be included in the embassy's emergency action plan, but it would likely be supplemented in a noncombatant evacuation plan with information and intelligence available via the Department of Defense and
The Church Committee concluded that these activities made the intelligence community a secret government that was illegal, unethical, and improper and did not reflect the people or the nation of America. Secret intelligence actions were used to disrupt, harass, and destroy domestic law-abiding citizens and groups. At the time, people were spied on with excessive intrusion with the methods being illegal. In addition, the intelligence agencies carried out secret infiltration
Lesson Plan Amp; Reflection I didn't know what state you are in so was unable to do state/district standards! Lesson Plan Age/Grade Range; Developmental Level(s): 7-8/2nd Grade; Below grade level Anticipated Lesson Duration: 45 Minutes Lesson Foundations Pre-assessment (including cognitive and noncognitive measures): All students are reading below grade level (5-7 months) as measured by standardized assessments and teacher observation Curricular Focus, Theme, or Subject Area: Reading: Fluency, word recognition, and comprehension State/District Standards: Learning Objectives: Students will develop
Branding in Service Markets Amp Aim And Objectives Themes for AMP Characteristics Composing Branding Concept Branding Evolution S-D Logic and Service Markets Branding Challenges in Service Markets Considerations for Effective Service Branding Categories and Themes Branding Theory Evolution S-D Logic and Service Markets Branding Challenges in Service Markets Considerations for Effective Service Branding Branding Concept Characteristics Characteristics Composing Branding Concept Sampling of Studies Reviewed Evolution of Branding Theory Evolution of Marketing Service-Brand-Relationship-Value Triangle Brand Identity, Position & Image Just as marketing increasingly influences most aspects of the consumer's lives, brands
Our semester plans gives you unlimited, unrestricted access to our entire library of resources —writing tools, guides, example essays, tutorials, class notes, and more.
Get Started Now