Truth discovery and crowdsourcing aggregation: A unified perspective

Jing Gao; Qi Li; Bo Zhao; Wei Fan; Jiawei Han

doi:10.14778/2824032.2824136

Truth discovery and crowdsourcing aggregation: A unified perspective

Jing Gao
, Qi Li
, Bo Zhao
, Wei Fan
, Jiawei Han

Department of Computer Science and Engineering

SUNY Buffalo
Microsoft USA
Baidu Inc
University of Illinois at Urbana-Champaign

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

38 Scopus citations

Abstract

In the era of Big Data, data entries, even describing the same objects or events, can come from a variety of sources, where a data source can be a web page, a database or a person. Consequently, conflicts among sources become inevitable. To resolve the conflicts and achieve high quality data, truth discovery and crowdsourcing aggregation have been studied intensively. However, although these two topics have a lot in common, they are studied separately and are applied to different domains. To answer the need of a systematic introduction and comparison of the two topics, we present an organized picture on truth discovery and crowdsourcing aggregation in this tutorial. They are compared on both theory and application levels, and their related areas as well as open questions are discussed.

Original language	English
Title of host publication	Proceedings of the VLDB Endowment
Editors	Christophe Claramunt, Simonas Saltenis, Ki-Joune Li
Publisher	Association for Computing Machinery
Pages	2048-2049
Number of pages	2
Volume	8
Edition	12 12
DOIs	https://doi.org/10.14778/2824032.2824136
State	Published - 2015
Event	3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006 - Seoul, Korea, Republic of Duration: Sep 11 2006 → Sep 11 2006

Conference

Conference	3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006
Country/Territory	Korea, Republic of
City	Seoul
Period	09/11/06 → 09/11/06

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10.14778/2824032.2824136

Cite this

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title = "Truth discovery and crowdsourcing aggregation: A unified perspective",

abstract = "In the era of Big Data, data entries, even describing the same objects or events, can come from a variety of sources, where a data source can be a web page, a database or a person. Consequently, conflicts among sources become inevitable. To resolve the conflicts and achieve high quality data, truth discovery and crowdsourcing aggregation have been studied intensively. However, although these two topics have a lot in common, they are studied separately and are applied to different domains. To answer the need of a systematic introduction and comparison of the two topics, we present an organized picture on truth discovery and crowdsourcing aggregation in this tutorial. They are compared on both theory and application levels, and their related areas as well as open questions are discussed.",

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language = "English",

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booktitle = "Proceedings of the VLDB Endowment",

publisher = "Association for Computing Machinery ",

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Gao, J, Li, Q, Zhao, B, Fan, W & Han, J 2015, Truth discovery and crowdsourcing aggregation: A unified perspective. in C Claramunt, S Saltenis & K-J Li (eds), Proceedings of the VLDB Endowment. 12 12 edn, vol. 8, Association for Computing Machinery , pp. 2048-2049, 3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006, Seoul, Korea, Republic of, 09/11/06. https://doi.org/10.14778/2824032.2824136

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T2 - 3rd Workshop on Spatio-Temporal Database Management, STDBM 2006, Co-located with the 32nd International Conference on Very Large Data Bases, VLDB 2006

AU - Gao, Jing

AU - Li, Qi

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AU - Fan, Wei

AU - Han, Jiawei

PY - 2015

Y1 - 2015

N2 - In the era of Big Data, data entries, even describing the same objects or events, can come from a variety of sources, where a data source can be a web page, a database or a person. Consequently, conflicts among sources become inevitable. To resolve the conflicts and achieve high quality data, truth discovery and crowdsourcing aggregation have been studied intensively. However, although these two topics have a lot in common, they are studied separately and are applied to different domains. To answer the need of a systematic introduction and comparison of the two topics, we present an organized picture on truth discovery and crowdsourcing aggregation in this tutorial. They are compared on both theory and application levels, and their related areas as well as open questions are discussed.

AB - In the era of Big Data, data entries, even describing the same objects or events, can come from a variety of sources, where a data source can be a web page, a database or a person. Consequently, conflicts among sources become inevitable. To resolve the conflicts and achieve high quality data, truth discovery and crowdsourcing aggregation have been studied intensively. However, although these two topics have a lot in common, they are studied separately and are applied to different domains. To answer the need of a systematic introduction and comparison of the two topics, we present an organized picture on truth discovery and crowdsourcing aggregation in this tutorial. They are compared on both theory and application levels, and their related areas as well as open questions are discussed.

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DO - 10.14778/2824032.2824136

M3 - Chapter

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SP - 2048

EP - 2049

BT - Proceedings of the VLDB Endowment

A2 - Claramunt, Christophe

A2 - Saltenis, Simonas

A2 - Li, Ki-Joune

PB - Association for Computing Machinery

Y2 - 11 September 2006 through 11 September 2006

ER -

Truth discovery and crowdsourcing aggregation: A unified perspective

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