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Oren W Etzioni

age ~60

from Seattle, WA

Also known as:
  • Oren Q Etzioni
  • Utoni E Oren
  • Oren Etsion
  • Oren I
Phone and address:
6127 Keswick Dr, Seattle, WA 98105
2065237613

Oren Etzioni Phones & Addresses

  • 6127 Keswick Dr, Seattle, WA 98105 • 2065237613 • 2069858375
  • 6065 NE Kelden Pl, Seattle, WA 98105
  • 200 NE 42Nd St, Seattle, WA 98105
  • 5820 57Th St, Seattle, WA 98105 • 2065237613
  • Kiona, WA
  • Washington, DC

Work

  • Company:
    Allen institute for artificial intelligence
    Jan 2014
  • Position:
    Chief executive officer

Education

  • Degree:
    Doctorates, Doctor of Philosophy
  • School / High School:
    Carnegie Mellon University
    1986 to 1991
  • Specialities:
    Computer Science, Philosophy

Skills

Machine Learning • Artificial Intelligence • Data Mining • Big Data • Natural Language Processing • Computer Science • Algorithms • Text Mining • Information Retrieval • Entrepreneurship • Pattern Recognition • Text Analytics • Information Extraction

Interests

Machine Learning • Artificial Intelligence • Natural Language Processing • Data Mining

Industries

Research

Isbn (Books And Publications)

  • Software Agents

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  • Author:
    Oren Etzioni
  • ISBN #:
    0929280598
Name / Title
Company / Classification
Phones & Addresses
Oren Etzioni
Principal
Etzioni
Computer Related Services
6127 NE Keswick Dr, Seattle, WA 98105
Oren Etzioni
Partner, Venture Partner
Madrona Venture Group, LLC
Investors Nec · Investment Advice
1000 2 Ave, Seattle, WA 98104
2066743000, 2066743004

Us Patents

  • Information Search Device And Information Search Method Using Topic-Centric Query Routing

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  • US Patent:
    6701310, Mar 2, 2004
  • Filed:
    May 11, 2000
  • Appl. No.:
    09/569305
  • Inventors:
    Atsushi Sugiura - Tokyo, JP
    Oren Etzioni - Seattle WA
  • Assignee:
    NEC Corporation - Tokyo
    University of Washington - Seattle WA
  • International Classification:
    G06F 1730
  • US Classification:
    707 5, 707 1, 707 3, 707 4, 707 6, 707 10, 707102, 7071041, 7155011, 715513, 709219, 709217
  • Abstract:
    An information search device capable of selecting topic search engines (i. e. , search engines that focus on specific topics) that are appropriate to a users search keywords when searching the Web on the Internet. Terms having relevance to each topic search engine are collected from, for example, the Web, and a DB selection index for selecting search engines is produced in advance by an index generator. When a search keyword is supplied from a user, terms having relevance to the search keyword are acquired from a general-purpose Web search engine by means of a query expansion unit. The thus-acquired terms are matched with terms stored in the DB selection index, and topic search engines having a high incidence of matching are presented to the user.
  • Performing Predictive Pricing Based On Historical Data

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  • US Patent:
    7010494, Mar 7, 2006
  • Filed:
    Mar 26, 2004
  • Appl. No.:
    10/811077
  • Inventors:
    Oren Etzioni - Seattle WA, US
    Alexander Yates - Seattle WA, US
    Craig A. Knoblock - El Segundo CA, US
    Rattapoom Tuchinda - Los Angeles CA, US
  • Assignee:
    University of Washington - Seattle WA
  • International Classification:
    G06F 17/60
  • US Classification:
    705 1, 705 10, 705400, 705412
  • Abstract:
    Techniques are described for using predictive pricing information for items to assist in evaluating buying and/or selling decisions in various ways, such as on behalf of end-user item acquirers and/or intermediate item providers. The predictive pricing for an item may be based on an analysis of historical pricing information for that item and/or related items, and can be used to make predictions about future pricing information for the item. Such predictions may then be provided to users in various ways to enable comparison of current prices to predicted future prices. In some situations, predictive pricing information is used to assist customers when purchasing airline tickets and/or to assist travel agents when selling airline tickets. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.
  • Performing Predictive Pricing Based On Historical Data

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  • US Patent:
    7346520, Mar 18, 2008
  • Filed:
    Feb 10, 2006
  • Appl. No.:
    11/352420
  • Inventors:
    Oren Etzioni - Seattle WA, US
    Alexander Yates - Seattle WA, US
    Craig A. Knoblock - El Segundo CA, US
    Rattapoom Tuchinda - Los Angeles CA, US
  • Assignee:
    University of Washington - Seattle WA
  • International Classification:
    G06Q 99/00
  • US Classification:
    705 1, 705 10, 705400, 705412
  • Abstract:
    Techniques are described for using predictive pricing information for items to assist in evaluating buying and/or selling decisions in various ways, such as on behalf of end-user item acquirers and/or intermediate item providers. The predictive pricing for an item may be based on an analysis of historical pricing information for that item and/or related items, and can be used to make predictions about future pricing information for the item. Such predictions may then be provided to users in various ways to enable comparison of current prices to predicted future prices. In some situations, predictive pricing information is used to assist customers when purchasing airline tickets and/or to assist travel agents when selling airline tickets. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.
  • System And Method Of Protecting Prices

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  • US Patent:
    7797187, Sep 14, 2010
  • Filed:
    Nov 13, 2006
  • Appl. No.:
    11/599607
  • Inventors:
    Hugh Crean - Seattle WA, US
    Jay Bartot - Seattle WA, US
    David Hsu - Santa Monica CA, US
    Oren Etzioni - Seattle WA, US
    Michael Fridgen - Seattle WA, US
  • Assignee:
    Farecast, Inc. - Seattle WA
  • International Classification:
    G06F 17/30
    G06F 17/50
    G06F 17/00
    G06F 30/00
  • US Classification:
    705 10, 705400, 705 26, 705 141, 705 7, 705 5
  • Abstract:
    A method and system for protecting prices is provided. The price protection system increases consumer confidence when making purchases by reducing the risk associated with fluctuating prices. The price protection system receives a purchase specification from a consumer. Next, the price protection system determines the risk that the prices of items matching the purchase specification will change and reports a protected price to the consumer that represents the price that the price protection system will protect based on the determined risk for a protection period. Finally, the price protection system receives a request from the consumer to purchase protection of the protected price.
  • Open Information Extraction From The Web

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  • US Patent:
    7877343, Jan 25, 2011
  • Filed:
    Apr 2, 2007
  • Appl. No.:
    11/695506
  • Inventors:
    Michael J. Cafarella - Seattle WA, US
    Michele Banko - Seattle WA, US
    Oren Etzioni - Seattle WA, US
  • Assignee:
    University of Washington through its Center for Commercialization - Seattle WA
  • International Classification:
    G06E 1/00
    G06F 15/18
  • US Classification:
    706 20, 705 5, 382104
  • Abstract:
    To implement open information extraction, a new extraction paradigm has been developed in which a system makes a single data-driven pass over a corpus of text, extracting a large set of relational tuples without requiring any human input. Using training data, a Self-Supervised Learner employs a parser and heuristics to determine criteria that will be used by an extraction classifier (or other ranking model) for evaluating the trustworthiness of candidate tuples that have been extracted from the corpus of text, by applying heuristics to the corpus of text. The classifier retains tuples with a sufficiently high probability of being trustworthy. A redundancy-based assessor assigns a probability to each retained tuple to indicate a likelihood that the retained tuple is an actual instance of a relationship between a plurality of objects comprising the retained tuple. The retained tuples comprise an extraction graph that can be queried for information.
  • Performing Predictive Pricing Based On Historical Data

    view source
  • US Patent:
    7974863, Jul 5, 2011
  • Filed:
    Mar 7, 2008
  • Appl. No.:
    12/044229
  • Inventors:
    Oren Etzioni - Seattle WA, US
    Alexander Yates - Seattle WA, US
    Craig A. Knoblock - El Segundo CA, US
    Rattapoom Tuchinda - Los Angeles CA, US
  • Assignee:
    University of Washington - Seattle WA
  • International Classification:
    G06Q 99/00
  • US Classification:
    705 5, 705 11, 705 731
  • Abstract:
    Techniques are described for using predictive pricing information for items to assist in evaluating buying and/or selling decisions in various ways, such as on behalf of end-user item acquirers and/or intermediate item providers. The predictive pricing for an item may be based on an analysis of historical pricing information for that item and/or related items, and can be used to make predictions about future pricing information for the item. Such predictions may then be provided to users in various ways to enable comparison of current prices to predicted future prices. In some situations, predictive pricing information is used to assist customers when purchasing airline tickets and/or to assist travel agents when selling airline tickets.
  • Use Of Lexical Translations For Facilitating Searches

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  • US Patent:
    8489385, Jul 16, 2013
  • Filed:
    Jun 25, 2012
  • Appl. No.:
    13/532742
  • Inventors:
    Oren Etzioni - Seattle WA, US
    Kobi Reiter - Seattle WA, US
    Marcus Sammer - Seattle WA, US
    Michael Schmitz - Seattle WA, US
    Stephen Soderland - Bainbridge Island WA, US
  • Assignee:
    University of Washington - Seattle WA
  • International Classification:
    G06F 17/27
    G06F 17/28
  • US Classification:
    704 2, 704 9
  • Abstract:
    A translation graph is created using a plurality of reference sources that include translations between a plurality of different languages. Each entry in a source is used to create a wordsense entry, and each new word in a source is used to create a wordnode entry. A pair of wordnode and wordsense entries corresponds to a translation. In addition, a probability is determined for each wordsense entry and is decreased for each translation entry that includes more than a predefined number of translations into the same language. Bilingual translation entries are removed if subsumed by a multilingual translation entry. Triangulation is employed to identify pairs of common wordsense translations between a first, second, and third language. Translations not found in reference sources can also be inferred from the data comprising the translation graph. The translation graph can then be used for searches of a data collection in different languages.
  • Performing Predictive Pricing Based On Historical Data

    view source
  • US Patent:
    8566143, Oct 22, 2013
  • Filed:
    Apr 7, 2011
  • Appl. No.:
    13/082362
  • Inventors:
    Oren Etzioni - Seattle WA, US
    Alexander Yates - Seattle WA, US
    Craig A. Knoblock - El Segundo CA, US
    Rattapoom Tuchinda - Los Angeles CA, US
  • Assignee:
    Microsoft Corporation - Redmond WA
  • International Classification:
    G06Q 99/00
  • US Classification:
    705 735, 705 11, 705400
  • Abstract:
    Techniques are described for using predictive pricing information for items to assist in evaluating buying and/or selling decisions in various ways, such as on behalf of end-user item acquirers and/or intermediate item providers. The predictive pricing for an item may be based on an analysis of historical pricing information for that item and/or related items, and can be used to make predictions about future pricing information for the item. Such predictions may then be provided to users in various ways to enable comparison of current prices to predicted future prices. In some situations, predictive pricing information is used to assist customers when purchasing airline tickets and/or to assist travel agents when selling airline tickets. This abstract is provided to comply with rules requiring an abstract, and it is submitted with the intention that it will not be used to interpret or limit the scope or meaning of the claims.

Resumes

Oren Etzioni Photo 1

Chief Executive Officer

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Location:
Seattle, WA
Industry:
Research
Work:
Allen Institute For Artificial Intelligence
Chief Executive Officer

Decide 2010 - Sep 2013
Co-Founder and Chief Technology Officer

Farecast 2003 - 2008
Founder

Madrona Venture Group 2003 - 2008
Venture Partner

Go2Net 1999 - 2000
Chief Technology Officer
Education:
Carnegie Mellon University 1986 - 1991
Doctorates, Doctor of Philosophy, Computer Science, Philosophy
Harvard University 1982 - 1986
Bachelors, Bachelor of Arts, Bachelor of Science, Computer Science
Carnegie Mellon University
Master of Science, Masters, Computer Science
Skills:
Machine Learning
Artificial Intelligence
Data Mining
Big Data
Natural Language Processing
Computer Science
Algorithms
Text Mining
Information Retrieval
Entrepreneurship
Pattern Recognition
Text Analytics
Information Extraction
Interests:
Machine Learning
Artificial Intelligence
Natural Language Processing
Data Mining

Wikipedia References

Oren Etzioni Photo 2

Oren Etzioni

Googleplus

Oren Etzioni Photo 3

Oren Etzioni

Youtube

Artificial Intelligence will empower us, not ...

Artificial Intelligence advocate Oren Etzioni makes a case for the lif...

  • Duration:
    13m 18s

Why we shouldnt fear artificial intelligence ...

AI is not going to exterminate us, says longtime artificial intelligen...

  • Duration:
    3m 37s

Emeritus Lecture: Oren Etzioni (Oct 2022)

What I learned: stories and lessons from an academic lifetime Thursday...

  • Duration:
    1h 1m 32s

Directors' Conversations: Oren Etzioni, Allen...

HAI co-director John Etchemendy's guest is Oren Etzioni, Allen Institu...

  • Duration:
    41m 8s

Oren Etzioni, PhD: CEO of Allen Institute for...

Oren is a leading thinker in neural networks and Natural Language Proc...

  • Duration:
    1h 5m 36s

Heroes of NLP: Oren Etzioni

Heroes of NLP is a video interview series featuring Andrew Ng, the fou...

  • Duration:
    34m 49s

How Artificial Intelligence Will Transform Me...

-We upload new clips every day! Make sure to subscribe! #pakmanlive.

  • Duration:
    3m 15s

Ignite your AI curiosity with Oren Etzioni

AI for the common good Harnessing the power of AI will not only will i...

  • Duration:
    34m 46s

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