Class blog 9

Visit Hallmark Cards or Communispace website. Discuss how a company like Hallmark Cards can best benefit from communities.

Communities are a great source of inspiration for Halmark Cards. Virtual communities help Hallmark Cards gain in-site and inspiration about what their customers want to see on their card. Hallmark Cards uses contests to entice their customers to submit ideas to them. This is the current contest, http://www.hallmarkcontests.com/index.cfm.

Hallmark also has a blog to help their communities communicate between each other.

http://www.yourhallmarkcardcompetition.blogspot.com/

This is great for Hallmark and will be great for any company that wants to use customer imput to improve the product that they show to their customer.

In Class Blog

What are the Similarities and Differences between an Artificial Neural Network (ANN) and an Expert System(ES).


My last two blogs explain these terms in more detail, but I'd like to define each of these for you so we can conceptually understand each of these terms.

An Artificial Neural Network (ANN), often just called a "neural network" (NN), is a mathematical model or computational model based on biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation.
AND

An expert system is a software program that helps an expert who is knowledgeable in a particular field. An Expert System is applied based on a bank of knowledge and a set of rules for applying the knowledge base to each particular situation that is described to the program.

Similarities
1. Both are systems designed to help define a possible outcome for the user.
2. Both systems get better as more information is imputed into their knowledge base.

Differences
1. ANN's can rely on explicit knowledge while ES's rely on implicit knowledge.

2. ANN's can solve more complex problems that other technologies cannot.

Artificial Neural Networks

1. What is an artificial neural network (ANN)?

An artificial neural network (ANN), often just called a "neural network" (NN), is a mathematical model or computational model based on biological neural networks. It consists of an interconnected group of artificial neurons and processes information using a connectionist approach to computation.

2. How to create an ANN model for a problem domain?

ANN's are created using a knowledge base about the problem. It then goes through different calculations to determine the desired output for the problem. After the knowledge base has been learned by the Neural Network it can make better decisions for the problem. If the ANN continually learns from more input into the knowledge base it has the potential to make even better decisions and make more accurate decisions for the problem.

3. How does ANN compare with expert systems? How do they differ from each other as knowledge management tools?

ANN's are important tools when explicit knowledge cannot be defined as implicit knowledge. Many Expert Systems use implicit knowledge to find the answer to any given problem. An ANN has taken hold as a system that can infer answers to problems with little implicit knowledge based on the explicit knowledge that it has.