Zobrazeno 1 - 10
of 155
pro vyhledávání: '"Jennifer Widom"'
Autor:
Jennifer Widom, Michael J. Franklin, Michael Stonebraker, Volker Markl, Joseph M. Hellerstein, Samuel Madden, Anastasia Ailamaki, Johannes Gehrke, Daniel J. Abadi, Dan Suciu, Christopher Olston, Tova Milo, Philip A. Bernstein, Laura M. Haas, Rakesh Agrawal, Todd Walter, Christopher Ré, Donald Kossmann, Jeffrey Dean, Yannis Ioannidis, AnHai Doan, Jeffrey F. Naughton, Raghu Ramakrishnan, Magdalena Balazinska, Sharad Mehrotra, Michael J. Carey, H. V. Jagadish, Alon Halevy, Surajit Chaudhuri, Beng Chin Ooi
Publikováno v:
Communications of the ACM. 59:92-99
Every few years a group of database researchers meets to discuss the state of database research, its impact on practice, and important new directions. This report summarizes the discussion and conclusions of the eighth such meeting, held October 14-
We conduct an experimental analysis of a dataset comprising over 27 million microtasks performed by over 70,000 workers issued to a large crowdsourcing marketplace between 2012--2016. Using this data---never before analyzed in an academic context---w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::82deea4972391263127a2695d6e073cd
Autor:
Aditya Parameswaran, Neoklis Polyzotis, Hector Garcia-Molina, Ashish Gupta, Stephen Boyd, Jennifer Widom
Publikováno v:
Proceedings of the VLDB Endowment. 7:685-696
We focus on crowd-powered filtering, i.e., filtering a large set of items using humans. Filtering is one of the most commonly used building blocks in crowdsourcing applications and systems. While solutions for crowd-powered filtering exist, they make
Autor:
Semih Salihoglu, Jennifer Widom
Publikováno v:
Proceedings of the VLDB Endowment. 7:577-588
We study the problem of implementing graph algorithms efficiently on Pregel-like systems, which can be surprisingly challenging. Standard graph algorithms in this setting can incur unnecessary inefficiencies such as slow convergence or high communica
Publikováno v:
Proceedings of the AAAI Conference on Human Computation and Crowdsourcing. 1:112-120
Traditional information retrieval systems have limited functionality. For instance, they are not able to adequately support queries containing non-textual fragments such as images or videos, queries that are very long or ambiguous, or semantically-ri
Autor:
Hyunjung Park, Jennifer Widom
Publikováno v:
Proceedings of the VLDB Endowment. 6:781-792
Deco is a comprehensive system for answering declarative queries posed over stored relational data together with data obtained on-demand from the crowd. In this paper we describe Deco's cost-based query optimizer, building on Deco's data model, query
Autor:
Richard Pang, Hyunjung Park, Aditya Parameswaran, Neoklis Polyzotis, Jennifer Widom, Hector Garcia-Molina
Publikováno v:
ACM SIGMOD Record. 41:22-27
Deco is a comprehensive system for answering declarative queries posed over stored relational data together with data obtained on-demand from the crowd. In this overview paper, we describe Deco's data model, query language, and system prototype, summ
Autor:
Jennifer Widom
Publikováno v:
2016 Sixteenth International Conference on Advances in ICT for Emerging Regions (ICTer).
A great deal of database research is largely systems-driven, with less of a focus on well thought out, clean foundations. My approach has been to lay solid theoretical foundations first, then develop a prototype system realizing those foundations. Th
Publikováno v:
SIGMOD Conference
We study crowdsourcing quality management, that is, given worker responses to a set of tasks, our goal is to jointly estimate the true answers for the tasks, as well as the quality of the workers. Prior work on this problem relies primarily on applyi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bd182b293d9117307b7b70b1fbed30c5
https://escholarship.org/uc/item/9gf262w6
https://escholarship.org/uc/item/9gf262w6
Autor:
Keith Ito, Arvind Arasu, Shivnath Babu, Mayur Datar, Brian Babcock, Jennifer Widom, John Cieslewicz, Utkarsh Srivastava, Rajeev Motwani
Publikováno v:
Data-Centric Systems and Applications ISBN: 9783540286073
Data Stream Management
Data Stream Management
Traditional database management systems are best equipped to run one-time queries over finite stored data sets. However, many modern applications such as network monitoring, financial analysis, manufacturing, and sensor networks require long-running,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::082d84c25b92b24c84368bb761f8bee1
https://doi.org/10.1007/978-3-540-28608-0_16
https://doi.org/10.1007/978-3-540-28608-0_16