---
title: "Wrapper Induction for Information Extraction"
authors:
  - "Nicholas Kushmerick"
  - "Daniel S. Weld"
  - "Robert B. Doorenbos"
doi: ""
url: "https://ijcai.org/proceedings/1997/106"
pdf: "https://ijcai.org/proceedings/1997/0106.pdf"
venue: "Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence"
year: 1997
pages: "729-736"
track: "Information Retrieval"
keywords:
---

# Wrapper Induction for Information Extraction

Nicholas Kushmerick, Daniel S. Weld, Robert B. Doorenbos

*Proceedings of the Fifteenth International Joint Conference on Artificial Intelligence*, pages 729-736.

## Abstract

Many Internet information resources present relational data-telephone directories, product catalogs, etc. Because these sites are formatted for people, mechanically extracting their content is difficult. Systems using such resources typically use hand-coded wrappers, procedures to extract data from information resources. We introduce wrapper induction, a method for automatically constructing wrappers, and identify HLRT, a wrapper class that is efficiently learnable, yet expressive enough to handle 48% of a recently surveyed sample of Internet resources. We use PAC analysis to bound the problem's sample complexity, and show that the system degrades gracefully with imperfect labeling knowledge.