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Improve db+ir efficiency by lifting the probabilistic lever phd 2nd year report (2007).
| Content Provider | CiteSeerX |
|---|---|
| Author | Wu, Hengzhi Tombros, Anastasios |
| Abstract | 1 The report presents our studies to improve the efficiency of DB+IR integrating technology. The three main contributions are: 1. we propose a novel top-k mechanism called lazy top-k, the general top operation in DB+IR system is discussed, and a histogram inverted index are designed to support the lazy top-k algorithms; 2. by studying the probabilistic datalog implementation for link-based retrieval, we carry out the discussion on PRA optimisation, for our best knowledge, this is the first PRA optimisation investigation so far; 3. we compare different approaches of integrating DB and IR technologies, through experiment, we show that probabilistic SQL approach is more advanced in probabilistic aggregation and probabilistic estimation than traditional SQL. |
| File Format | |
| Publisher Date | 2007-01-01 |
| Access Restriction | Open |
| Subject Keyword | Db Ir Main Contribution Probabilistic Estimation Probabilistic Lever Phd First Pra Optimisation Investigation Link-based Retrieval Probabilistic Sql Approach Ir Technology Lazy Top-k General Top Operation Different Approach Probabilistic Aggregation Pra Optimisation Lazy Top-k Algorithm Improve Db Ir Efficiency Db Ir System Probabilistic Datalog Implementation Novel Top-k Mechanism Year Report Traditional Sql |
| Content Type | Text |
