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- Influence
Top 100 relevant results, sorted by most influential
Open Information Extraction from the Web
- M. Banko, Michael J. Cafarella, S. Soderland, M. Broadhead, Oren Etzioni
- Computer Science
- CACM
- 6 January 2007
Traditionally, Information Extraction (IE) has focused on satisfying precise, narrow, pre-specified requests from small homogeneous corpora (e.g., extract the location and time of seminars from a set… Expand
Identifying Relations for Open Information Extraction
- Anthony Fader, S. Soderland, Oren Etzioni
- Computer Science
- EMNLP
- 27 July 2011
Open Information Extraction (IE) is the task of extracting assertions from massive corpora without requiring a pre-specified vocabulary. This paper shows that the output of state-of-the-art Open IE… Expand
Named Entity Recognition in Tweets: An Experimental Study
- Alan Ritter, S. Clark, Mausam, Oren Etzioni
- Computer Science
- EMNLP
- 27 July 2011
People tweet more than 100 Million times daily, yielding a noisy, informal, but sometimes informative corpus of 140-character messages that mirrors the zeitgeist in an unprecedented manner. The… Expand
Open Language Learning for Information Extraction
- Mausam, Michael Schmitz, S. Soderland, R. Bart, Oren Etzioni
- Computer Science
- EMNLP-CoNLL
- 2012
Open Information Extraction (IE) systems extract relational tuples from text, without requiring a pre-specified vocabulary, by identifying relation phrases and associated arguments in arbitrary… Expand
Web document clustering: a feasibility demonstration
- Oren Zamir, Oren Etzioni
- Computer Science
- SIGIR '98
- 1 August 1998
Users of Web search engines are often forced to sift through the long ordered list of document "snippets" returned by the engines. The IR community has explored document clustering as an alternative… Expand
Extracting Product Features and Opinions from Reviews
- Ana-Maria Popescu, Oren Etzioni
- Computer Science
- HLT/EMNLP
- 6 October 2005
Consumers are often forced to wade through many on-line reviews in order to make an informed product choice. This paper introduces Opine, an unsupervised information-extraction system which mines… 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, and… 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
Manually querying search engines in order to accumulate a large bodyof factual information is a tedious, error-prone process of piecemealsearch. Search engines retrieve and rank potentially… Expand
The Tradeoffs Between Open and Traditional Relation Extraction
- M. Banko, Oren Etzioni
- Computer Science
- ACL
- 1 June 2008
Traditional Information Extraction (IE) takes a relation name and hand-tagged examples of that relation as input. Open IE is a relationindependent extraction paradigm that is tailored to massive and… Expand
Open Information Extraction: The Second Generation
- Oren Etzioni, Anthony Fader, J. Christensen, S. Soderland, Mausam
- Computer Science
- IJCAI
- 2011
How do we scale information extraction to the massive size and unprecedented heterogeneity of the Web corpus? Beginning in 2003, our KnowItAll project has sought to extract high-quality knowledge… Expand