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critical and usability trials will help us understand how people best interact with such semantically enabled knowledge management systems The user can also use the topic hierarchy to nd relevant documents, moving up or down the hierarchy to expand or re ne the search For example, if a search on a particular topic gives no useful hits, the user can look for a supertopic of the original topic Conversely, if too many hits occur, the user can look for sub-topics Besides searching and browsing by topic, the user can browse the library using other characteristics of a document, for example by requesting other documents by the same author Whatever form of search the user employs, the results presented will be able to take account of the user s pro le.

Class RContactViewSortOrder De ned in cntviewbase.h This class speci es the sort order for a contact view. It is implemented as an array of TFieldType UIDs, which de ne the elds whose contents are used to sort on, and their order.

There are many other applications for the normal distribution One of the reasons for this, but not the only one, is that sums of different random variables or means of several random variables become normal We had an indication of this when we added uniformly distributed random variables This is a consequence of the central limit theorem, which we will discuss subsequently But before we do that, we turn our attention to bivariate random variables

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For example, the search string visual impairment will produce quite different results for a user with an interest in human resources than for a user interested in medical technology The user pro le will contain a component representing the longer-term user interests and also a component derived from current activities, for example the documents read during the current session For example, a search for the word jaguar might normally return information about the South American cat, if the user s pro le indicates an interest in natural history If our user, on the basis of recently viewed documents and web pages, appears on this occasion to be interested in cars, then jaguar could be interpreted differently On a subsequent day, the system would revert to its original interpretation, for this particular user.

We want to look at sums when we add the observations from the spinning wheel We have been concerned with a single random variable, but rst note that the observations we want to add are those from different observations and so are different random variables So we turn our attention to different random variables and rst consider two different random variables Suppose we have a sample space and we have de ned two random variables, which we will call X and Y, on the sample points Now we must determine the probabilities that the random variables assume values together We need not show the sample space, but the probabilities with which the random variables take on their respective values together are shown in Table 81 This is called the joint probability distribution function The table is to be read this way: X can take on the values 1, 2, and 3 while the random variable Y can take on the values 1 and 2 The entries in the body of the table

Creation and Destruction Methods RContactViewSortOrder() This is the default constructor that creates an empty sort order. void CopyL(const RContactViewSortOrder& aSortOrder) This method discards any existing eld type data and replaces it with that from the speci ed sort order. aSortOrder the sort order whose eld types are to be used. void Close() This method closes the sort order and frees up all space allocated to it. Field Type Methods inline TInt Count() const This method returns the number of eld types used by the sort order. inline void AppendL(TFieldType aField) This method appends a eld type to the set owned by the sort order. aField the eld type to be appended. inline TFieldType operator[](TInt aIndex) const This method returns the eld type at the speci ed index. aIndex the desired index.

Table 81 X Y 1 2 1 1/12 1/3 2 1/12 1/12 3 1/3 1/12

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