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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Wei Lu Chuitian Rong Jinchuan Chen Xiaoyong Du Fung, G.P.C. Xiaofang Zhou |
| Copyright Year | 2010 |
| Abstract | Given a set of lists, where items of each list are sorted by the ascending order of their values, the objective of this paper is to figure out the common items that appear in all of the lists efficiently. This problem is sometimes known as common items extraction from sorted lists. To solve this problem, one common approach is to scan all items of all lists sequentially in parallel until one of the lists is exhausted. However, we observe that if the overlap of items across all lists is not high, such sequential access approach can be significantly improved. In this paper, we propose two algorithms, MergeSkip and MergeESkip, to solve this problem by taking the idea of skipping as many items of lists as possible. As a result, a large number of comparisons among items can be saved, and hence the efficiency can be improved. We conduct extensive analysis of our proposed algorithms on one real dataset and two synthetic datasets with different data distributions. We report all our findings in this paper. |
| Starting Page | 219 |
| Ending Page | 225 |
| File Size | 364541 |
| Page Count | 7 |
| File Format | |
| ISBN | 9781769540122 |
| e-ISBN | 9781424466009 |
| DOI | 10.1109/APWeb.2010.16 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-04-06 |
| Publisher Place | Korea (South) |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Knowledge engineering Algorithm design and analysis Computer science Data engineering Information retrieval Data mining Application software Informatics |
| Content Type | Text |
| Resource Type | Article |
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