2014 LaSEWebAutomatingSearchStrategi

• (Polozov & Gulwani, 2014) ⇒ Oleksandr Polozov, and Sumit Gulwani. (2014). “LaSEWeb: Automating Search Strategies over Semi-structured Web Data.” In: Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) Journal. ISBN:978-1-4503-2956-9 doi:10.1145/2623330.2623761

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222014%22+LaSEWeb%3A+Automating+Search+Strategies+over+Semi-structured+Web+Data
• http://dl.acm.org/citation.cfm?id=2623330.2623761&preflayout=flat#citedby

Quotes

Author Keywords

• Clustering; domain-specific languages; information filtering; query languages; question answering.; [[search process; semi-structured data; structure extraction; web programming

Abstract

We show how to programmatically model processes that humans use when extracting answers to queries (e.g., " Who invented typewriter? "," List of Washington national parks ") from semi-structured Web pages returned by a search engine. This modeling enables various applications including automating repetitive search tasks, and helping search engine developers design micro-segments of factoid questions.

We describe the design and implementation of a domain-specific language that enables extracting data from a webpage based on its structure, visual layout, and linguistic patterns. We also describe an algorithm to rank multiple answers extracted from multiple webpages.

On 100,000 + queries (across 7 micro-segments) obtained from Bing logs, our system LaSEWeb answered queries with an average recall of 71%. Also, the desired answer (s) were present in top-3 suggestions for 95% + cases.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2014 LaSEWebAutomatingSearchStrategi	Oleksandr Polozov Sumit Gulwani			LaSEWeb: Automating Search Strategies over Semi-structured Web Data				10.1145/2623330.2623761		2014