Showing papers by "Eugene Agichtein published in 2000"
01 Jun 2000
TL;DR: This paper develops a scalable evaluation methodology and metrics for the task, and presents a thorough experimental evaluation of Snowball and comparable techniques over a collection of more than 300,000 newspaper documents.
Abstract: Text documents often contain valuable structured data that is hidden Yin regular English sentences. This data is best exploited infavailable as arelational table that we could use for answering precise queries or running data mining tasks.We explore a technique for extracting such tables from document collections that requires only a handful of training examples from users. These examples are used to generate extraction patterns, that in turn result in new tuples being extracted from the document collection.We build on this idea and present our Snowball system. Snowball introduces novel strategies for generating patterns and extracting tuples from plain-text documents.At each iteration of the extraction process, Snowball evaluates the quality of these patterns and tuples without human intervention,and keeps only the most reliable ones for the next iteration. In this paper we also develop a scalable evaluation methodology and metrics for our task, and present a thorough experimental evaluation of Snowball and comparable techniques over a collection of more than 300,000 newspaper documents.
1,399 citations
01 Jan 2000
TL;DR: This paper introduces a new pattern and tuple generation scheme for Snowball, with different strengths and weaknesses than those of the original system, and shows preliminary results on how the two versions of Snowball can be combined more accurately.
Abstract: Text documents often contain valuable structured data that is hidden in regular English sentences. This data is best exploited if available as a relational table that we could use for answering precise queries or for running data mining tasks. Our Snowball system extracts these relations from document collections starting with only a handful of user-provided example tuples. Based on these tuples, Snowball generates patterns that are used, in turn, to find more tuples. In this paper we introduce a new pattern and tuple generation scheme for Snowball, with different strengths and weaknesses than those of our original system. We also show preliminary results on how we can combine the two versions of Snowball to extract tuples more accurately.
16 citations