�ݺ�ߣshows by User: ipeirotis

�ݺ�ߣshows by User: ipeirotis / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: ipeirotis / Tue, 22 Apr 2014 21:04:23 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: ipeirotis Quizz: Targeted Crowdsourcing with a Billion (Potential) Users /slideshow/quizz-33826994/33826994 quizz-www2014-140422210423-phpapp02
We describe Quizz, a gamified crowdsourcing system that simultaneously assesses the knowledge of users and acquires new knowledge from them. Quizz operates by asking users to complete short quizzes on specific topics; as a user answers the quiz questions, Quizz estimates the user’s competence. To acquire new knowledge, Quizz also incorporates questions for which we do not have a known answer; the answers given by competent users provide useful signals for selecting the correct answers for these questions. Quizz actively tries to identify knowledgeable users on the Internet by running advertising campaigns, effectively leveraging “for free” the targeting capabilities of existing, publicly available, ad placement services. Quizz quantifies the contributions of the users using information theory and sends feedback to the advertising system about each user. The feedback allows the ad targeting mechanism to further optimize ad placement. Our experiments, which involve over ten thousand users, confirm that we can crowdsource knowledge curation for niche and specialized topics, as the advertising network can automatically identify users with the desired expertise and interest in the given topic. We present controlled experiments that examine the effect of various incentive mechanisms, highlighting the need for having short-term rewards as goals, which incentivize the users to contribute. Finally, our cost-quality analysis indicates that the cost of our approach is below that of hiring workers through paid-crowdsourcing platforms, while offering the additional advantage of giving access to billions of potential users all over the planet, and being able to reach users with specialized expertise that is not typically available through existing labor marketplaces.]]>
We describe Quizz, a gamified crowdsourcing system that simultaneously assesses the knowledge of users and acquires new knowledge from them. Quizz operates by asking users to complete short quizzes on specific topics; as a user answers the quiz questions, Quizz estimates the user’s competence. To acquire new knowledge, Quizz also incorporates questions for which we do not have a known answer; the answers given by competent users provide useful signals for selecting the correct answers for these questions. Quizz actively tries to identify knowledgeable users on the Internet by running advertising campaigns, effectively leveraging “for free” the targeting capabilities of existing, publicly available, ad placement services. Quizz quantifies the contributions of the users using information theory and sends feedback to the advertising system about each user. The feedback allows the ad targeting mechanism to further optimize ad placement. Our experiments, which involve over ten thousand users, confirm that we can crowdsource knowledge curation for niche and specialized topics, as the advertising network can automatically identify users with the desired expertise and interest in the given topic. We present controlled experiments that examine the effect of various incentive mechanisms, highlighting the need for having short-term rewards as goals, which incentivize the users to contribute. Finally, our cost-quality analysis indicates that the cost of our approach is below that of hiring workers through paid-crowdsourcing platforms, while offering the additional advantage of giving access to billions of potential users all over the planet, and being able to reach users with specialized expertise that is not typically available through existing labor marketplaces.]]> Tue, 22 Apr 2014 21:04:23 GMT /slideshow/quizz-33826994/33826994 ipeirotis@slideshare.net(ipeirotis) Quizz: Targeted Crowdsourcing with a Billion (Potential) Users ipeirotis We describe Quizz, a gamified crowdsourcing system that simultaneously assesses the knowledge of users and acquires new knowledge from them. Quizz operates by asking users to complete short quizzes on specific topics; as a user answers the quiz questions, Quizz estimates the user’s competence. To acquire new knowledge, Quizz also incorporates questions for which we do not have a known answer; the answers given by competent users provide useful signals for selecting the correct answers for these questions. Quizz actively tries to identify knowledgeable users on the Internet by running advertising campaigns, effectively leveraging “for free” the targeting capabilities of existing, publicly available, ad placement services. Quizz quantifies the contributions of the users using information theory and sends feedback to the advertising system about each user. The feedback allows the ad targeting mechanism to further optimize ad placement. Our experiments, which involve over ten thousand users, confirm that we can crowdsource knowledge curation for niche and specialized topics, as the advertising network can automatically identify users with the desired expertise and interest in the given topic. We present controlled experiments that examine the effect of various incentive mechanisms, highlighting the need for having short-term rewards as goals, which incentivize the users to contribute. Finally, our cost-quality analysis indicates that the cost of our approach is below that of hiring workers through paid-crowdsourcing platforms, while offering the additional advantage of giving access to billions of potential users all over the planet, and being able to reach users with specialized expertise that is not typically available through existing labor marketplaces. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/quizz-www2014-140422210423-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> We describe Quizz, a gamified crowdsourcing system that simultaneously assesses the knowledge of users and acquires new knowledge from them. Quizz operates by asking users to complete short quizzes on specific topics; as a user answers the quiz questions, Quizz estimates the user’s competence. To acquire new knowledge, Quizz also incorporates questions for which we do not have a known answer; the answers given by competent users provide useful signals for selecting the correct answers for these questions. Quizz actively tries to identify knowledgeable users on the Internet by running advertising campaigns, effectively leveraging “for free” the targeting capabilities of existing, publicly available, ad placement services. Quizz quantifies the contributions of the users using information theory and sends feedback to the advertising system about each user. The feedback allows the ad targeting mechanism to further optimize ad placement. Our experiments, which involve over ten thousand users, confirm that we can crowdsource knowledge curation for niche and specialized topics, as the advertising network can automatically identify users with the desired expertise and interest in the given topic. We present controlled experiments that examine the effect of various incentive mechanisms, highlighting the need for having short-term rewards as goals, which incentivize the users to contribute. Finally, our cost-quality analysis indicates that the cost of our approach is below that of hiring workers through paid-crowdsourcing platforms, while offering the additional advantage of giving access to billions of potential users all over the planet, and being able to reach users with specialized expertise that is not typically available through existing labor marketplaces.

Quizz: Targeted Crowdsourcing with a Billion (Potential) Users from Panos Ipeirotis

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1 Humanities and Technology Unite /slideshow/humanities-and-technology-unite/14576968 humanitiesandtechnologyunite-121003131808-phpapp02
�ݺ�ߣs from the "Humanities and Technology Unite" event at the Museum of the City of New York http://m.mcny.org/programs/Humanities-and-Technology-Unite A special evening to celebrate the NEH Grant awarded to MCNY and Tagasauris, a NYC Technology start-up, to annotate the Museum's archives using crowdsouring and semantic web technologies.]]>
�ݺ�ߣs from the "Humanities and Technology Unite" event at the Museum of the City of New York http://m.mcny.org/programs/Humanities-and-Technology-Unite A special evening to celebrate the NEH Grant awarded to MCNY and Tagasauris, a NYC Technology start-up, to annotate the Museum's archives using crowdsouring and semantic web technologies.]]> Wed, 03 Oct 2012 13:18:07 GMT /slideshow/humanities-and-technology-unite/14576968 ipeirotis@slideshare.net(ipeirotis) Humanities and Technology Unite ipeirotis �ݺ�ߣs from the "Humanities and Technology Unite" event at the Museum of the City of New York http://m.mcny.org/programs/Humanities-and-Technology-Unite A special evening to celebrate the NEH Grant awarded to MCNY and Tagasauris, a NYC Technology start-up, to annotate the Museum's archives using crowdsouring and semantic web technologies. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/humanitiesandtechnologyunite-121003131808-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> �ݺ�ߣs from the "Humanities and Technology Unite" event at the Museum of the City of New York http://m.mcny.org/programs/Humanities-and-Technology-Unite A special evening to celebrate the NEH Grant awarded to MCNY and Tagasauris, a NYC Technology start-up, to annotate the Museum's archives using crowdsouring and semantic web technologies.

Humanities and Technology Unite from Panos Ipeirotis

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1 The Market for Intellect: Discovering economically-rewarding education paths /ipeirotis/the-market-for-intellect crowdsourcingpersonalizedonlineeducation-120729141901-phpapp01
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]]> Sun, 29 Jul 2012 14:18:59 GMT /ipeirotis/the-market-for-intellect ipeirotis@slideshare.net(ipeirotis) The Market for Intellect: Discovering economically-rewarding education paths ipeirotis <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/crowdsourcingpersonalizedonlineeducation-120729141901-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" />

The Market for Intellect: Discovering economically-rewarding education paths from Panos Ipeirotis

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1 On Mice and Men: The Role of Biology in Crowdsourcing /slideshow/on-mice-and-men-the-role-of-biology-in-crowdsourcing/12609800 ci2012-120419181012-phpapp02
�ݺ�ߣs from my talk at the Collective Intelligence 2012 conference.]]>
�ݺ�ߣs from my talk at the Collective Intelligence 2012 conference.]]> Thu, 19 Apr 2012 18:10:10 GMT /slideshow/on-mice-and-men-the-role-of-biology-in-crowdsourcing/12609800 ipeirotis@slideshare.net(ipeirotis) On Mice and Men: The Role of Biology in Crowdsourcing ipeirotis �ݺ�ߣs from my talk at the Collective Intelligence 2012 conference. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ci2012-120419181012-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> �ݺ�ߣs from my talk at the Collective Intelligence 2012 conference.

On Mice and Men: The Role of Biology in Crowdsourcing from Panos Ipeirotis

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1 Crowdsourcing using Mechanical Turk: Quality Management and Scalability /slideshow/crowdsourcing-using-mechanical-turk-quality-management-and-scalability/12211655 google-talk-march27-120329123322-phpapp01
�ݺ�ߣs from a talk at Google, Mountain View on March 27th, 2012]]>
�ݺ�ߣs from a talk at Google, Mountain View on March 27th, 2012]]> Thu, 29 Mar 2012 12:33:21 GMT /slideshow/crowdsourcing-using-mechanical-turk-quality-management-and-scalability/12211655 ipeirotis@slideshare.net(ipeirotis) Crowdsourcing using Mechanical Turk: Quality Management and Scalability ipeirotis �ݺ�ߣs from a talk at Google, Mountain View on March 27th, 2012 <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/google-talk-march27-120329123322-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> �ݺ�ߣs from a talk at Google, Mountain View on March 27th, 2012

Crowdsourcing using Mechanical Turk: Quality Management and Scalability from Panos Ipeirotis

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1 Big Data, Stupid Decisions / Strata Jumpstart 2011 / Panos Ipeirotis / http://www.youtube.com/watch?v=LXDFwphuwCs /slideshow/big-data-stupid-decisions-9326862/9326862 ipeirotisstratajumpstart-110919145547-phpapp02
Strata Jumpstart, New York, September 19 2011 Big Data, Stupid Decisions: The Importance Of Measuring What We Should Be Measuring Video at http://www.youtube.com/watch?v=LXDFwphuwCs]]>
Strata Jumpstart, New York, September 19 2011 Big Data, Stupid Decisions: The Importance Of Measuring What We Should Be Measuring Video at http://www.youtube.com/watch?v=LXDFwphuwCs]]> Mon, 19 Sep 2011 14:55:45 GMT /slideshow/big-data-stupid-decisions-9326862/9326862 ipeirotis@slideshare.net(ipeirotis) Big Data, Stupid Decisions / Strata Jumpstart 2011 / Panos Ipeirotis / http://www.youtube.com/watch?v=LXDFwphuwCs ipeirotis Strata Jumpstart, New York, September 19 2011 Big Data�, Stupid Decisions:� �The Importance Of Measuring �What We Should Be Measuring� Video at http://www.youtube.com/watch?v=LXDFwphuwCs <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/ipeirotisstratajumpstart-110919145547-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> Strata Jumpstart, New York, September 19 2011 Big Data�, Stupid Decisions:� �The Importance Of Measuring �What We Should Be Measuring� Video at http://www.youtube.com/watch?v=LXDFwphuwCs

Big Data, Stupid Decisions / Strata Jumpstart 2011 / Panos Ipeirotis / http://www.youtube.com/watch?v=LXDFwphuwCs from Panos Ipeirotis

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1 Crowdsourcing: Lessons from Henry Ford /slideshow/crowdsourcing-lessons-from-henry-ford/7884697 www2011-crowdsourcing-panel-110508114518-phpapp02
�ݺ�ߣs from WWW2011 panel: "The Computer is the new Sewing Machine: Benefits and Perils of Crowdsourcing"]]>
�ݺ�ߣs from WWW2011 panel: "The Computer is the new Sewing Machine: Benefits and Perils of Crowdsourcing"]]> Sun, 08 May 2011 11:45:15 GMT /slideshow/crowdsourcing-lessons-from-henry-ford/7884697 ipeirotis@slideshare.net(ipeirotis) Crowdsourcing: Lessons from Henry Ford ipeirotis �ݺ�ߣs from WWW2011 panel: "The Computer is the new Sewing Machine: Benefits and Perils of Crowdsourcing" <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/www2011-crowdsourcing-panel-110508114518-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /> �ݺ�ߣs from WWW2011 panel: "The Computer is the new Sewing Machine: Benefits and Perils of Crowdsourcing"

Crowdsourcing: Lessons from Henry Ford from Panos Ipeirotis

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1 Managing Crowdsourced Human Computation: A Tutorial /slideshow/managing-crowdsourced-human-computation/7526103 crowdsourcinghumancomputationwww2011tutorial-110405135225-phpapp01
The slides from the tutorial presented during the WWW2011 conference in Hyderabad, India (March 29th 2011, by Panos Ipeirotis)]]>
The slides from the tutorial presented during the WWW2011 conference in Hyderabad, India (March 29th 2011, by Panos Ipeirotis)]]> Tue, 05 Apr 2011 13:52:19 GMT /slideshow/managing-crowdsourced-human-computation/7526103 ipeirotis@slideshare.net(ipeirotis) Managing Crowdsourced Human Computation: A Tutorial ipeirotis The slides from the tutorial presented during the WWW2011 conference in Hyderabad, India (March 29th 2011, by Panos Ipeirotis) <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/crowdsourcinghumancomputationwww2011tutorial-110405135225-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /> The slides from the tutorial presented during the WWW2011 conference in Hyderabad, India (March 29th 2011, by Panos Ipeirotis)

Managing Crowdsourced Human Computation: A Tutorial from Panos Ipeirotis

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1 New York Mechanical Turk Meetup /slideshow/new-york-mechanical-turk-meetup/1921301 sep2009-mturk-meetup-090828154707-phpapp01
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]]> Fri, 28 Aug 2009 15:46:59 GMT /slideshow/new-york-mechanical-turk-meetup/1921301 ipeirotis@slideshare.net(ipeirotis) New York Mechanical Turk Meetup ipeirotis <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/sep2009-mturk-meetup-090828154707-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" />

New York Mechanical Turk Meetup from Panos Ipeirotis

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1 https://cdn.slidesharecdn.com/profile-photo-ipeirotis-48x48.jpg?cb=1557857458 Panos Ipeirotis is an Associate Professor and George A. Kellner Faculty Fellow at the Department of Information, Operations, and Management Sciences at Leonard N. Stern School of Business of New York University. He is also the Chief Scientist at Tagasauris, and in 2012-2013 serves as “academic-in-residence” at oDesk Research. His recent research interests focus on crowdsourcing and on mining user-generated content on the Internet. He received his Ph.D. degree in Computer Science from Columbia University in 2004, working with Prof. Luis Gravano. He has received three “Best Paper” awards (IEEE ICDE 2005, ACM SIGMOD 2006, WWW 2011), two “Best Paper Runner Up” awards (JCDL 2002, ACM www.behind-the-enemy-lines.com https://cdn.slidesharecdn.com/ss_thumbnails/quizz-www2014-140422210423-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/quizz-33826994/33826994 Quizz: Targeted Crowds... https://cdn.slidesharecdn.com/ss_thumbnails/humanitiesandtechnologyunite-121003131808-phpapp02-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/humanities-and-technology-unite/14576968 Humanities and Technol... https://cdn.slidesharecdn.com/ss_thumbnails/crowdsourcingpersonalizedonlineeducation-120729141901-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds ipeirotis/the-market-for-intellect The Market for Intelle...