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To Search or to Crawl?: Towards a Query Optimizer for Text-centric Tasks by Panagiotis G. Ipeirotis; Eugene Agichtein; Pranay Jain; Luis Gravano is a scholarly article available to read on EtoBox.

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Text is ubiquitous and, not surprisingly, many important applications rely on textual data for a variety of tasks. As a notable example, information extraction applications derive structured relations from unstructured text; as another example, focused crawlers explore the web to locate pages about specific topics. Execution plans for text-centric tasks follow two general paradigms for processing a text database: either we can scan, or "crawl," the text database or, alternatively, we can exploit search engine indexes and retrieve the documents of interest via carefully crafted queries constructed in task-specific ways. The choice between crawl-and query-based execution plans can have a substantial impact on both execution time and output "completeness" (e.g., in terms of recall). Nevertheless, this choice is typically ad-hoc and based on heuristics or plain intuition. In this paper, we present fundamental building blocks to make the choice of execution plans for text-centric tasks in an informed, cost-based way. Towards this goal, we show how to analyze query-and crawl-based plans in terms of both execution time and output completeness. We adapt results from random-graph theory and

Author

Panagiotis G. Ipeirotis; Eugene Agichtein; Pranay Jain; Luis Gravano

Publisher

ACM

Published

2006

Language

EN