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| Content Provider | ACM Digital Library |
|---|---|
| Author | Nepomnyachiy, Sergey Suel, Torsten Dimopoulos, Constantinos |
| Abstract | A large amount of research has focused on faster methods for finding top-k results in large document collections, one of the main scalability challenges for web search engines. In this paper, we propose a method for accelerating such top-k queries that builds on and generalizes methods recently proposed by several groups of researchers based on Block-Max Indexes. In particular, we describe a system that uses a new filtering mechanism, based on a combination of block maxima and bitmaps, that radically reduces the number of documents that have to be further evaluated. Our filtering mechanism exploits the SIMD processing capabilities of current microprocessors, and it is optimized through caching policies that select and store suitable filter structures based on properties of the query load. Our experimental evaluation shows that the mechanism results in very significant speed-ups for disjunctive top-k queries under several state-of-the-art algorithms, including a speed-up of more than a factor of 2 over the fastest previously known methods. |
| Starting Page | 723 |
| Ending Page | 732 |
| Page Count | 10 |
| File Format | |
| ISBN | 9781450320344 |
| DOI | 10.1145/2484028.2484087 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2013-07-28 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Live area computation Candidate filtering mechanism Block-max inverted index Early termination Top-k query processing Posting bitset Docid-oriented block-max index |
| Content Type | Text |
| Resource Type | Article |
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