Matches in ScholarlyData for { ?s ?p ?o. }
- 394 creator brian-noble.
- 394 creator yidnekachew-haile.
- 394 type InProceedings.
- 394 label "Distributing Private Data in Challenged Network Environments".
- 394 sameAs 394.
- 394 abstract "Developing countries face significant challenges in network access, making even simple network tasks unpleasant. Many standard techniques---caching and predictive prefetching---help somewhat, but provide little or no assistance for personal data that is needed only by a single user. Sulula addresses this problem by leveraging the near-ubiquity of cellular phones able to send and receive simple SMS messages. Rather than visit a kiosk and fetch data on demand---a tiresome process at best---users request a future visit. If capacity exists, the kiosk can schedule secure retrieval of that user's data, saving time and more efficiently utilizing the kiosk's limited connectivity. When the user arrives at a provisioned kiosk, she need only obtain the session key on-demand, and thereafter has instant access. Experimental results show significant gains for the end user, saving tens of minutes of time for a typical email/news reading session. We also describe a small, ongoing deployment in-country for proof-of-concept, lessons learned from that experience, and provide a discussion on pricing and marketplace issues that remain to be addressed to make the system viable for developing-world access.".
- 394 hasAuthorList authorList.
- 394 isPartOf proceedings.
- 394 keyword "Content".
- 394 keyword "service delivery".
- 394 title "Distributing Private Data in Challenged Network Environments".
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- item-1 hasContent azarias-reda.
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- item-2 hasContent brian-noble.
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- item-3 hasContent yidnekachew-haile.
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- 398 creator arnd-christian-koenig.
- 398 creator ping-li.
- 398 type InProceedings.
- 398 label "b-bit minwise hashing".
- 398 sameAs 398.
- 398 abstract "This paper establishes the theoretical framework of b-bit minwise hashing. The original minwise hashing method has become a standard technique for estimating set similarity (e.g., resemblance) with applications in information retrieval, data management, social networks and computational advertising. By only storing the lowest b bits of each (minwise) hashed value (e.g., b=1 or 2), one can gain substantial advantages in terms of computational efficiency and storage space. We prove the basic theoretical results and provide an unbiased estimator of the resemblance for any $b$. We demonstrate that, even in the least favorable scenario, using b=1 may reduce the storage space at least by a factor of 21.3 (or 10.7) compared to using b=64 (or b=32), if one is interested in resemblance >0.5. Our theoretical results are validated using a proprietary collection of $10^6$ news articles and a public (UCI) dataset of $300,000$ NYTimes articles.".
- 398 hasAuthorList authorList.
- 398 isPartOf proceedings.
- 398 keyword "Efficient algorithms for large-scale analysis".
- 398 title "b-bit minwise hashing".
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- item-1 hasContent ping-li.
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- item-2 hasContent arnd-christian-koenig.
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- 4 creator nikolay-archak.
- 4 type InProceedings.
- 4 label "Money, glory and cheap talk: analyzing strategic behavior of contestants in simultaneous crowdsourcing contests on TopCoder.com".
- 4 sameAs 4.
- 4 abstract "Crowdsourcing is a new Web phenomenon, in which a firm takes a function once performed in-house and outsources it to a crowd, usually in the form of an open contest. Designing efficient crowdsoucring mechanisms is not possible without deep understanding of incentives and strategic choices of all participants. This paper presents an empirical analysis of determinants of individual performance in multiple simultaneous crowdsourcing contests using a unique dataset for the world's largest competitive software development portal: TopCoder.com. Special attention is given to studying the effects of the reputation system currently used by TopCoder.com on behavior of contestants. We find that individual specific traits together with the project payment and the number of project requirements are significant predictors of the final project quality. Furthermore, we find significant evidence of strategic behavior of contestants. High rated contestants face tougher competition from their opponents in the competition phase of the contest. In order to soften the competition, they move first in the registration phase of the contest, signing up early for particular projects. Although registration in TopCoder contests is non-binding, it deters entry of opponents in the same contest; our lower bound estimate shows that this strategy generates significant surplus gain to high rated contestants. We conjecture that the reputation + cheap talk mechanism employed by TopCoder has positive effect on allocative efficiency of the simultaneous all-pay contests and should be considered for adoption in other crowdsourcing platforms.".
- 4 hasAuthorList authorList.
- 4 isPartOf proceedings.
- 4 keyword "Economics aspects of online reviews".
- 4 keyword "ratings".
- 4 keyword "reputations".
- 4 title "Money, glory and cheap talk: analyzing strategic behavior of contestants in simultaneous crowdsourcing contests on TopCoder.com".
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- item-1 hasContent nikolay-archak.
- 405 creator andrew-tomkins.
- 405 creator flavio-chierichetti.
- 405 creator ravi-kumar.
- 405 type InProceedings.
- 405 label "Max-Cover in Map-Reduce".
- 405 sameAs 405.
- 405 abstract "The NP-hard \mkc problem requires selecting $k$ sets from a collection so as to maximize the size of the union. This classic problem occurs commonly in many settings in web search and advertising. For moderately-sized instances, a greedy algorithm gives an approximation of $(1-1/e)$. However, the greedy algorithm requires updating scores of arbitrary elements after each step, and hence becomes intractable for large datasets. We give the first max cover algorithm designed for today's large-scale commodity clusters. Our algorithm has provably almost the same approximation as greedy, but runs much faster. Furthermore, it can be easily expressed in the \mr programming paradigm, and requires only polylogarithmically many passes over the data. Our experiments on five large problem instances show that our algorithm is practical and can achieve good speedups compared to the sequential greedy algorithm.".
- 405 hasAuthorList authorList.
- 405 isPartOf proceedings.
- 405 keyword "Efficient algorithms for large-scale analysis".
- 405 title "Max-Cover in Map-Reduce".
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- item-1 hasContent flavio-chierichetti.
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- item-2 hasContent ravi-kumar.
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- item-3 hasContent andrew-tomkins.
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- 406 creator beth-trushkowsky.
- 406 creator john-mark-agosta.
- 406 creator rob-ennals.
- 406 creator tad-hirsch.
- 406 creator tye-rattenbury.
- 406 type InProceedings.
- 406 label "Highlighting Disputed Claims on the Web".
- 406 sameAs 406.