Corroborate and Learn Facts from the Web

Intelligent Database Systems Lab

N.Y.U.S.T.I. M.

Corroborate and Learn Factsfrom the Web

Presenter : Lin, Shu-HanAuthors : Shubin Zhao, Jonathan Betz

SIGKDD (2008)


N.Y.U.S.T.I. M.

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Outline

Motivation Objective Methodology Experiments Conclusion Comments


N.Y.U.S.T.I. M.Motivation

Many “Facts” The movie

“Independence day”

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Wikipedia

Infoplease.com

moviefone.com


N.Y.U.S.T.I. M.Motivation

Combine them Mentioned

The director of movie

“Roland Emmerich”

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N.Y.U.S.T.I. M.Objectives

Cache the new “facts”: attribute + value Have the same HTML patterns

Then corroborate these new “facts” Check other website also mentioned

about these “facts” or not

Learn this factGood fact: commonly referenced.Incorrect facts: very few mentioned.

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Attribute value


N.Y.U.S.T.I. M.Methodology – Overview

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3. Extract New facts

2. Match

1. Relevant Page

Wiki、 Seed set

Search Engine


N.Y.U.S.T.I. M.

Methodology – Corroborate fact– Common fact

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A common fact “Susan”, gender: female

Threshold:

Match


N.Y.U.S.T.I. M.Methodology – Extract New facts

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Cache “Repeated HTML patterns”

3. Extract New facts


N.Y.U.S.T.I. M.Experiments

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N.Y.U.S.T.I. M.Experiments

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Conclusions

Find relevant pages about entities Extract new facts by corroborating existing facts Base on string match and HTML pattern discovery


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Comments

Advantage Idea is intuitive Language independent Search and integrate information/data on web

Drawback Can only adapt to the old entities or Lots of information hide in the articles, not only tables.

Application We can’t use it to extract the comment or new information, such as the

comments of food in the blog


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Edit distance

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Corroborate and Learn Facts from the Web