ActiveClean: An Interactive Data Cleaning Framework For Modern Machine Learning (Demonstration Paper)

Sanjay Krishnan, Michael Franklin, Ken Goldberg, Eugene Wu, Jiannan Wang
SIGMOD, Jun. 2016.

Tags: best demo award, crowdsourcing, Data Cleaning

Clamshell: Scaling Up Crowds for Low Latency Data Labeling

Daniel Haas, Jiannan Wang, Eugene Wu, Michael Franklin
Proceedings of the VLDB (PVLDB), Oct. 2015.

Tags: crowdsourcing, human-in-the-loop, labeling, vldb

Argonaut: Macrotask Crowdsourcing for Complex Data Processing

Daniel Haas, Jason Ansel, Lydia Gu, Adam Marcus
VLDB 2015, Aug. 2015.

Tags: crowdsourcing, Data Cleaning, data quality

Wisteria: Nurturing Scalable Data Cleaning Infrastructure

Daniel Haas, Sanjay Krishnan, Jiannan Wang, Michael Franklin, Eugene Wu
VLDB 2015, Aug. 2015.

Tags: crowdsourcing, Data Cleaning, sampleclean

Stale View Cleaning: Getting Fresh Answers from Stale Materialized Views

Sanjay Krishnan, Jiannan Wang, Michael Franklin, Michael Jordan, Tim Kraska
VLDB 2015 (PVLDB Vol. 8 No. 12), Aug. 2015.

Tags: crowdsourcing, Data Cleaning, data quality, Materialized Views, Sampling

Introducing AMPCrowd: a simple service for declarative cross-crowd microtasking.

Posted on April 30, 2015 by Daniel Haas

Error: Unable to create directory uploads/2023/03. Is its parent directory writable by the server?

Crowdsourcing platforms like Amazon’s Mechanical Turk (AMT) make it possible to assign human workers small ‘microtasks’, such as labeling images or … Continue reading →

Scaling Up Crowd-Sourcing to Very Large Datasets: A Case for Active Learning

Barzan Mozafari, Purna Sarkar, Michael Franklin, Michael Jordan, Sam Madden
VLDB 2015 (PVLDB Vol. 8, No. 2), Aug. 2015.

Tags: active learning, amp, crowdsourcing, databases, Machine Learning

A Methodology for Learning, Analyzing, and Mitigating Social Influence Bias in Recommender Systems

Sanjay Krishnan, Jay Patel, Michael Franklin, Ken Goldberg
ACM Conference on Recommender Systems, Oct. 2014.

Tags: bias mitigation, crowdsourcing, Data Cleaning

A Sample-and-Clean Framework for Fast and Accurate Query Processing on Dirty Data

Jiannan Wang, Sanjay Krishnan, Michael Franklin, Ken Goldberg, Tim Kraska, Tova Milo
SIGMOD, Jun. 2014.

Tags: Big Data, crowdsourcing, Data Cleaning, query processing, Sampling

Leveraging Transitive Relations for Crowdsourced Joins

Jiannan Wang, Guoliang Li, Tim Kraska, Michael Franklin, Jianhua Feng
ACM SIGMOD Conference, Jun. 2013.

Tags: amp, crowdsourcing, query processing

CrowdQ: Crowdsourced Query Understanding

Gianluca Demartini, Beth Trushkowsky, Tim Kraska, Michael Franklin
CIDR 2013, Jan. 2013.

Tags: crowdsourcing, data quality, query processing, semantic web

Crowdsourced Enumeration Queries (Best Paper Award)

Beth Trushkowsky, Tim Kraska, Michael Franklin, Purna Sarkar
ICDE, Apr. 2013.

Tags: amp, Best Paper Award, crowdsourcing

CrowdER: Crowdsourcing Entity Resolution

Jiannan Wang, Tim Kraska, Michael Franklin, Jianhua Feng
Proceedings of the VLDB Endowment 2012, Vol. 5, No. 10, Aug. 2012.