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Recall that our problem is this: I have a class of 65 students I regard one of my students as an expert since she never makes an error I regret to report that the remaining students are terribly ignorant of my subject, and so guess at each answer I gave a test with six true false questions; a paper I have selected at random has each of these questions answered correctly What is the probability that I have selected the expert s paper One might think this is certain, but it is not This problem can be solved in much the same way that we solved the previous two problems Begin again with a square of side 1 On the horizontal axis, we indicate the probability we have chosen the expert (1/65) and the probability we have chosen an ordinary student (64/65) The chance of choosing the expert is small, so we have exaggerated the scale in Figure 33 for reasons of clarity The relative areas then should not be judged visually

The Message Server by itself cannot send or receive any messages, as it does not contain the message-type-speci c knowledge required. Instead,

1/64

Technical Report, report CVC TR-98-003/DCS TR-1165, Yale Center for Computational Vision and Control..

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the Message Server uses MTMs that encapsulate the message-type-speci c knowledge MTMs have been created by Symbian and by phone manufacturers for a range of message types, including: email (IMAP, SMTP and POP3) fax SMS BIO messages (smart messages used for con guration and other purposes) infrared and Bluetooth OBEX messages MMS Over time, it has proved straightforward to add new MTMs for new message types the architecture has proved its worth The MTMs are responsible for creating and sending messages, for receiving messages and for some aspects of displaying messages Actually, some types of messages are received by means of watchers (SMS is one of these message types), but the general picture holds true.

1/65

We begin this section by discussing the shortcomings of current search technology, before looking at how semantic web technology can offer the user a better search experience, and describing a number of systems

Now the expert answers the six true false questions on my examination with probability 1 This has been indicated on the vertical axis The area of the corresponding rectangle is then 1 65

Although I refer to an MTM, developers should be aware that, in fact, an MTM comprises a number of parts: a server-side MTM is a plug-in derived from the CBaseServerMtm class that is loaded directly by the Message Server and is responsible for the actual message transport, such as sending and receiving, if applicable a client-side MTM is derived from the CBaseMtm class and provides an API for messaging clients, such as the Messaging Application, that are speci c to the message type a user interface MTM is derived from the CBaseMtmUi class and provides an API for use by a messaging application that has a user interface, making it easier to create a generic messaging application that can manage different types of message a user interface data MTM is derived from the CBaseMtmUiData class and encapsulates user interface data for the MTM such as icons for the Messaging Application.

Semantic Web Technologies: Trends and Research in Ontology-based Systems John Davies, Rudi Studer, Paul Warren # 2006 John Wiley & Sons, Ltd

1 65

These parts and their relationship are shown in Figure 91 Only developers creating a new MTM or working on the Message Server need to care about server-side MTMs The user interface and user interface data MTMs are used by GUI applications As we are creating a non-GUI application, we will use only the client-side MTM We are not creating a new MTM, so we do not need to go further into the structure of.

This represents the probability that I chose the expert and that all the questions are answered correctly Now the remainder of my students are almost totally ignorant of my subject and so they guess the answers to each of my questions The probability that one of these students answers all the six questions correctly is then (1/2)6 = 1/64 This has been indicated on the right-hand vertical scale in Figure 33 The rectangle corresponding to the probability that a nonexpert answers all six of the questions correctly is then P(A|E) = 64 65

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