skip to main content
10.1145/2939672.2945389acmconferencesArticle/Chapter ViewAbstractPublication PageskddConference Proceedingsconference-collections
tutorial
Public Access

Mining Reliable Information from Passively and Actively Crowdsourced Data

Authors Info & Claims
Published:13 August 2016Publication History

ABSTRACT

Recent years have witnessed an astonishing growth of crowd-contributed data, which has become a powerful information source that covers almost every aspect of our lives. This big treasure trove of information has fundamentally changed the ways in which we learn about our world. Crowdsourcing has attracted considerable attentions with various approaches developed to utilize these enormous crowdsourced data from different perspectives. From the data collection perspective, crowdsourced data can be divided into two types: "passively" crowdsourced data and "actively" crowdsourced data; from task perspective, crowdsourcing research includes information aggregation, budget allocation, worker incentive mechanism, etc. To answer the need of a systematic introduction of the field and comparison of the techniques, we will present an organized picture on crowdsourcing methods in this tutorial. The covered topics will be interested for both advanced researchers and beginners in this field.

Skip Supplemental Material Section

Supplemental Material

kdd2016_tutorial_actively_crowdsourced_data_01-acm.mp4

mp4

1 GB

kdd2016_tutorial_actively_crowdsourced_data_02-acm.mp4

mp4

688.1 MB

kdd2016_tutorial_actively_crowdsourced_data_03-acm.mp4

mp4

1.3 GB

Index Terms

  1. Mining Reliable Information from Passively and Actively Crowdsourced Data

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in
    • Published in

      cover image ACM Conferences
      KDD '16: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
      August 2016
      2176 pages
      ISBN:9781450342322
      DOI:10.1145/2939672

      Copyright © 2016 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 13 August 2016

      Check for updates

      Author Tags

      Qualifiers

      • tutorial

      Acceptance Rates

      KDD '16 Paper Acceptance Rate66of1,115submissions,6%Overall Acceptance Rate1,133of8,635submissions,13%

      Upcoming Conference

      KDD '24

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader