초록

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Abstract ▼ AI-Helper

Similarity search is important in many applications including data cleaning, near duplicate detection, plagiarism detection and collaborative filtering. Existing methods make use of a filter-and-verification framework. They first generate candidate strings and then verify the candidates. It is very ...

Similarity search is important in many applications including data cleaning, near duplicate detection, plagiarism detection and collaborative filtering. Existing methods make use of a filter-and-verification framework. They first generate candidate strings and then verify the candidates. It is very important to generate candidates as small as possible. The prefix-filtering technique is widely used to reduce the number of candidates. In this paper, we show that we can generate candidates using partial elements in the prefix of a query. Based on the observation, we propose a technique that reduces the number of candidates significantly. Experimental results show that our technique achieves high efficiency.

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