Knowledge Representation
What is knowledge? Is knowledge the same thing as facts? some define knowledge as “the fact or condition of knowing something with familiarity gained through experience or association.”
People gain knowledge through experience—they see, hear, touch, feel, and taste the world around them. We can associate something we see with something we hear, thereby gaining new knowledge about the world.
An alternate definition for knowledge is “the fact or condition of being aware of something.” How do we make a computer aware of something? Suppose we know that the sun is hot, balls are round, and the sky is blue. These facts are knowledge about the world. How do we store this knowledge in our brain? How could we store this knowledge in a computer? This problem, called knowledge representation, is one of the first, most fundamental issues that researchers in artificial intelligence had to face. And the answer they found was symbols. Figure below illustrates the hierarchic of the knowledge
A symbol is a number or character string that represents an object or idea. Strings and numbers are used because computers are very good at processing them. This is called the internal representation of the knowledge. However, people are most comfortable using a natural language like English to represent knowledge. Thus, for practical reasons, we need mappings from facts to an internal computer representation and also to a form that people can understand.
The question here? Is the natural language is the best for computer and why?
There are many different kinds of knowledge we may want to represent: simple facts or complex relationships, mathematical formulas or rules for natural language syntax, associations between related concepts, inheritance hierarchies between classes of objects.
Consequently, choosing a knowledge representation for any particular application involves tradeoffs between the needs of people and computers. In addition to being easy to use, a good knowledge representation also must be easily modified and extended, either by changing the knowledge manually or through automatic machine learning techniques.
We explore here some common kinds of knowledge and the most popular approaches for storing that knowledge in computers.
a) Procedural Representation
Perhaps the most common technique for representing knowledge in computers is procedural knowledge. Procedural code not only encodes facts (constants or bound variables) but also defines the sequence of operations for using and manipulating those facts. Thus, program code is a perfectly natural way of encoding procedural knowledge.
Programs written in scripting languages such as Visual Basic, JavaScript, and LotusScript are examples of a procedural knowledge representation
What are the disadvantages of procedural knowledge representation?
b) Relational Representation
Another way to represent information is in relational form, such as that used in relational database systems. Relational databases provide a powerful and flexible mechanism for storing knowledge, which is why they have almost completely taken over the business of storing information in commercial business systems.
Knowledge is represented by tuples or records of information about an item, with each tuple containing a set of fields or columns defining specific attributes and values of that item. By storing a collection of information in a table, we can use relational calculus to manipulate the data, based on the relations defined, and query the information stored in the table. Structured Query Language (SQL) is the most popular language for manipulating relational data.
المادة المعروضة اعلاه هي مدخل الى المحاضرة المرفوعة بواسطة استاذ(ة) المادة . وقد تبدو لك غير متكاملة . حيث يضع استاذ المادة في بعض الاحيان فقط الجزء الاول من المحاضرة من اجل الاطلاع على ما ستقوم بتحميله لاحقا . في نظام التعليم الالكتروني نوفر هذه الخدمة لكي نبقيك على اطلاع حول محتوى الملف الذي ستقوم بتحميله .
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