Chapter 4 designing and analyzing

Bourgeois Learning Objectives Upon successful completion of this chapter, you will be able to: Introduction You have already been introduced to the first two components of information systems: However, those two components by themselves do not make a computer useful. Imagine if you turned on a computer, started the word processor, but could not save a document.

Chapter 4 designing and analyzing

The capital of Freedonia has a population of 9, No city in Freedonia has a population of 9, Freedonia is to the north of Sylvania. If you know the meaning of the word no, and also know that the capital of a country is a city in that country, then you should be able to conclude that the two sentences in 6 are inconsistent, regardless of where Freedonia is or what the population of its capital is.

Similarly, if you know that the relation expressed by to the north of is asymmetric, then you should be able to conclude that the two sentences in 7 are inconsistent. Broadly speaking, logic-based approaches to natural language semantics focus on those aspects of natural language which guide our judgments of consistency and inconsistency.

The syntax of a logical language is designed to make these features formally explicit. As a result, determining properties like consistency can often be reduced to symbolic manipulation, that is, to a task that can be carried out by a computer.

In order to pursue this approach, we first want to develop a technique for representing a possible situation. We do this in terms of something that logicians call a model.

A model for a set W of sentences is a formal representation of a situation in which all the sentences in W are true.

Chapter 4 designing and analyzing

The usual way of representing models involves set theory. The domain D of discourse all the entities we currently care about is a set of individuals, Chapter 4 designing and analyzing relations are treated as sets built up from D.

Our domain D will consist of three children, Stefan, Klaus and Evi, represented respectively as s, k and e.

The expression boy denotes the set consisting of Stefan and Klaus, the expression girl denotes the set consisting of Evi, and the expression is running denotes the set consisting of Stefan and Evi.

Diagram of a model containing a domain D and subsets of D corresponding to the predicates boy, girl and is running. Later in this chapter we will use models to help evaluate the truth or falsity of English sentences, and in this way to illustrate some methods for representing meaning.

Can a computer understand the meaning of a sentence? And how could we tell if it did?


This is similar to asking "Can a computer think? Suppose you are having a chat session with a person and a computer, but you are not told at the outset which is which. If you cannot identify which of your partners is the computer after chatting with each of them, then the computer has successfully imitated a human.

If a computer succeeds in passing itself off as human in this "imitation game" or "Turing Test" as it is popularly knownthen according to Turing, we should be prepared to say that the computer can think and can be said to be intelligent.

So Turing side-stepped the question of somehow examining the internal states of a computer by instead using its behavior as evidence of intelligence. By the same reasoning, we have assumed that in order to say that a computer understands English, it just needs to behave as though it did.

As a result, it can capture aspects of natural language which determine whether a set of sentences is consistent. This structure is the logical form of 8. Propositional logic allows us to represent just those parts of linguistic structure which correspond to certain sentential connectives.

We have just looked at and. Other such connectives are not, or and if In the formalization of propositional logic, the counterparts of such connectives are sometimes called boolean operators.

The basic expressions of propositional logic are propositional symbols, often written as P, Q, R, etc. There are varying conventions for representing boolean operators.

First, every propositional letter is a formula. Boolean Operator negation it is not the case that Truth conditions for the Boolean Operators in Propositional Logic. These rules are generally straightforward, though the truth conditions for implication departs in many cases from our usual intuitions about the conditional in English.

Suppose you state that Freedonia is not to the north of Sylvania, and you give as your reasons that Sylvania is to the north of Freedonia. In this case, you have produced an argument. The sentence Sylvania is to the north of Freedonia is the assumption of the argument while Freedonia is not to the north of Sylvania is the conclusion.

The step of moving from one or more assumptions to a conclusion is called inference. Informally, it is common to write arguments in a format where the conclusion is preceded by therefore.

Chapter 4 designing and analyzing

Therefore, Freedonia is not to the north of Sylvania An argument is valid if there is no possible situation in which its premises are all true and its conclusion is not true. Now, the validity of 9 crucially depends on the meaning of the phrase to the north of, in particular, the fact that it is an asymmetric relation:Informatics: The interdisciplinary study of information content, representation, technology and applications, and the methods and strategies by which information is used in organizations, networks, cultures and societies.

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The question covered by the petition shall be submitted as a separate proposition, but it may be printed on the same ballot with any other proposition submitted at the same election other than the election of .

Chapter 4 Designing and analyzing jobs Job design Job design: the process of systematically organizing work into tasks that are required to perform a specific job. ****an organization’s strategy and structure influence the ways in which jobs are designed.

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