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Web Resources
For software to be considered intelligent, it must have the ability of making decisions. By interacting with its environment through sensors and acting in
its environment through effectors. They interact by searching, comparing, learning...There have been at least 7 types of intelligent agents identified: collaborative, interface, mobile, information, reactive, hybrid, and smart.
The most common agents for SEOs are the information ones. These are important because of their power search capabilities. But each agent is given a very small, well-defined purpose. And there are several running in parallel to each other, to achieve an overall task. A.I. uses different methods to build up search agents.
Business - List of business/finance/loan/mortgage resources
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Computers - List of computer hardware/software/peripheral resources
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Internet - List of webhosting/webdesign/internet marketing resources
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Software - List of software resources
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Web Design - List of web design/development resources
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Web Hosting - List of web hosting resources
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Web Promotion - List of search engine optimization/internet marketing resources
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Web Resources - List of other web resources
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Recreation - List of travel/hotel/cruise resources
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Casino - List of online gambling/poker/blackjack/roulette resources
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Health - List of online pharmacy/hospital/health resources
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Shopping - List of online shopping/gift resources
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Miscellaneous - List of all other resources not stated above
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Artificial Neural Networks (ANN): Used for pattern recognition, and classification tasks in particular. They deal well with imprecise data, as they can classify as "not too sure". There's plenty of different kinds of neural nets: Recurrent, Hopfield Network, Bolzman Mmachine, SVM, Self-Organizing-Maps among others.
Semantic Networks (SN): These show the relationships and concepts. First a graph is created containing nodes which represent concepts and links used to represent reltionships between the concepts. There are six types of Semantic Networks: Categories, Definitional, Assertional, Implicational, Executable, Learning, Hybrid. Genetic Algorithms (GA): These are used in random search procedures. They are really efficient on problems that are very difficult to solve. Using them on dynamic data sets is difficult, because the initial pool of data may no longer be valid.
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