Michael J. Cafarella

Publications
Influence

Open Information Extraction from the Web

Michele Banko, Michael J. Cafarella, S. Soderland, M. Broadhead, Oren Etzioni
Computer Science
CACM
6 January 2007

This paper introduces Open IE (OIE), a new extraction paradigm where the system makes a single data-driven pass over its corpus and extracts a large set of relational tuples without requiring any human input. Expand

Unsupervised named-entity extraction from the Web: An experimental study

Oren Etzioni, Michael J. Cafarella, +5 authors A. Yates
Computer Science
Artif. Intell.
1 June 2005

The KnowItAll system aims to automate the tedious process of extracting large collections of facts (e.g., names of scientists or politicians) from the Web in an unsupervised, domain-independent, scalable manner. Expand

WebTables: exploring the power of tables on the web

Michael J. Cafarella, A. Halevy, Daisy Zhe Wang, Eugene Wu, Y. Zhang
Computer Science
Proc. VLDB Endow.
1 August 2008

We extracted 14.1 billion HTML tables from Google's general-purpose web crawl, and used statistical classification techniques to find the estimated 154M that contain high-quality relational data. Expand

Web-scale information extraction in knowitall: (preliminary results)

Oren Etzioni, Michael J. Cafarella, +6 authors A. Yates
Computer Science
WWW '04
17 May 2004

This paper introduces KnowItAll, a system that aims to automate the tedious process ofextracting large collections of facts from the web in an autonomous,domain-independent, and scalable manner. Expand

Data Integration for the Relational Web

Michael J. Cafarella, A. Halevy, Nodira Khoussainova
Computer Science
Proc. VLDB Endow.
1 August 2009

This paper describes Octopus, a system that combines search, extraction, data cleaning and integration, and enables users to create new data sets from those found on the Web. Expand

TextRunner: Open Information Extraction on the Web

A. Yates, Michele Banko, M. Broadhead, Michael J. Cafarella, Oren Etzioni, S. Soderland
Computer Science
NAACL
23 April 2007

We demonstrate a new kind of information extraction, called Open Information Extraction (OIE), in which the system makes a single, data-driven pass over the entire corpus and extracts a large set of relational tuples, without requiring any human input. Expand

Uncovering the Relational Web

Michael J. Cafarella, A. Halevy, Y. Zhang, Daisy Zhe Wang, Eugene Wu
Computer Science
WebDB
2008

We extracted 14.1 billion HTML ta- bles from a several-billion-page portion of Google's general-purpose web crawl, and estimate that 154 million of these tables contain high-quality relational-style data. Expand

Automatic web spreadsheet data extraction

Zhe Chen, Michael J. Cafarella
Computer Science
SS@ '13
30 August 2013

This paper introduces a system that automatically extracts relational data from spreadsheets, thereby enabling relational spreadsheet integration. Expand

KnowItNow: Fast, Scalable Information Extraction from the Web

Michael J. Cafarella, Doug Downey, S. Soderland, Oren Etzioni
Computer Science
HLT/EMNLP
6 October 2005

Numerous NLP applications rely on search-engine queries, both to extract information from and to compute statistics over the Web corpus. Expand

Automatic Optimization for MapReduce Programs

Eaman Jahani, Michael J. Cafarella, C. Ré
Computer Science
Proc. VLDB Endow.
1 March 2011

This paper covers Manimal, which automatically analyzes MapReduce programs and applies appropriate data-aware optimizations, thereby requiring no additional help at all from the programmer. Expand

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