Which of the following algorithms would be the most appropriate to use for deter

Question

Which of the following algorithms would be the most appropriate to use for determining how many topics exist in a large collection of papers written about different topics?

A-Priori

Locality-sensitive hashing

PCY

Hierarchical agglomerative clustering

In the PCY algorithm, if 3 pairs map to the same bucket and the minimum support is 2, which of the following statements is true?

Any pair that maps to this bucket may be frequent.

None of the items in the pair that maps to each bucket is frequent

Each of the items in the pair that maps to each bucket is frequent

All pairs that map to this bucket are frequent.

Any pair that maps to this bucket may be frequent.

None of the items in the pair that maps to each bucket is frequent

Each of the items in the pair that maps to each bucket is frequent

All pairs that map to this bucket are frequent.

Explanation / Answer

1. Option C

PCY algorithm.

PCY algorithm is Hash-based improvement to A-Priori which uses the memory to keep counts of buckets into which pairs of items are hashed, there by sort out the topics from large collection of items from the database.

2. Option B

None of the items in the pair that maps to each bucket is frequent

If the count of a bucket is >= support s, it is called a frequent bucket.

For a bucket with total count less than s, none of its pairs can be frequent. Can be eliminated as candidates

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