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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/27629
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| Title: | Understanding, Estimating, and Incorporating Output Quality Into Join Algorithms For Information Extraction |
| Authors: | Jain, Alpa
Ipeirotis, Panagiotis
Gravano, Luis
Doan, Anhai |
| Issue Date: | 27-Jun-2008 |
| Series/Report no.: | CeDER-08-04 |
| Abstract: | Information extraction (IE) systems are trained to extract specific relations from text databases. Real-world
applications often require that the output of multiple IE systems be joined to produce the data of interest. To
optimize the execution of a join of multiple extracted relations, it is not sufficient to consider only execution time.
In fact, the quality of the join output is of critical importance: unlike in the relational world, different join execution
plans can produce join results of widely different quality whenever IE systems are involved. In this paper, we develop
a principled approach to understand, estimate, and incorporate output quality into the join optimization process
over extracted relations. We argue that the output quality is affected by (a) the configuration of the IE systems
used to process the documents, (b) the document retrieval strategies used to retrieve documents, and (c) the actual
join algorithm used. Our analysis considers a variety of join algorithms from relational query optimization, and
predicts the output quality –and, of course, the execution time– of the alternate execution plans. We establish
the accuracy of our analytical models, as well as study the effectiveness of a quality-aware join optimizer, with a
large-scale experimental evaluation over real-world text collections and state-of-the-art IE systems. |
| URI: | http://hdl.handle.net/2451/27629 |
| Appears in Collections: | CeDER Working Papers
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