File access methods: The data contents that are present in a file can be accessed by the following two ways: • Sequential access • Random access or direct access Sequential access file: In sequential access method, the contents of the file are accessed from the beginning to the end. • The contents of the file can be read only in order; skipping contents between files is not possible. • It must read the contents from the beginning of the file, which takes more time. Temporary file: The purpose of a temporary file is to allocate a file for temporary usage. It is used to hold data temporarily for implementation of program.

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Exercise docID document text docID document text 1 hot chocolate cocoa beans 7 sweet sugar 2345 9 cocoa ghana africa 8 sugar cane brazil beans harvest ghana 9 sweet sugar beet cocoa butter butter truffles sweet chocolate 10 sweet cake icing 11 cake black forest Clustering by k-means, with preprocessing tokenization, term weighting TFIDF. Manhattan Distance. Number of cluster is 2. Centroid docID 2 and docID 9.

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Chapter 6.3, Problem 17CP

Program Plan Intro

File access methods:

The data contents that are present in a file can be accessed by the following two ways:

• Sequential access

• Random access or direct access

Sequential access file:

In sequential access method, the contents of the file are accessed from the beginning to the end.

• The contents of the file can be read only in order; skipping contents between files is not possible.

• It must read the contents from the beginning of the file, which takes more time.

Temporary file:

The purpose of a temporary file is to allocate a file for temporary usage. It is used to hold data temporarily for implementation of program.

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Exercise docID document text docID document text 1 hot chocolate cocoa beans 7 sweet sugar 2345 9 cocoa ghana africa 8 sugar cane brazil beans harvest ghana 9 sweet sugar beet cocoa butter butter truffles sweet chocolate 10 sweet cake icing 11 cake black forest Clustering by k-means, with preprocessing tokenization, term weighting TFIDF. Manhattan Distance. Number of cluster is 2. Centroid docID 2 and docID 9.

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