Task Recommendation with Developer Social Network in Software Crowdsourcing

Li, Ning; Mo, Wenkai; Shen, Beijun

doi:10.1109/apsec.2016.013

Cited by 8 publications

(2 citation statements)

References 27 publications

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“…e famous theory of "six degrees of separation" [22] maintains that people are six or fewer steps from each other and that a chain of "a friend of a friend" statements can be made to connect any two people using no more than six steps. e trust relationship in society is broadly applied to personalized recommendation systems [23,24], software crowdsourcing [25], image annotation [26], and so on. Rahman et al [12] proposed a framework that can create a large ad hoc social network and construct an incentive based on context-aware.…”

Section: Related Workmentioning

confidence: 99%

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TDSRC: A Task-Distributing System of Crowdsourcing Based on Social Relation Cognition

Peng

Gui

An³

et al. 2019

Mobile Information Systems

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Crowdsourcing significantly augments the creativity of the public and has become an indispensable component of many problem-solving pipelines. The main challenge, however, is the effective identification of malicious participators while distributing crowdsourcing tasks. In this paper, we propose a novel task-distributing system named Task-Distributing system of crowdsourcing based on Social Relation Cognition (TDSRC) to select qualified participators. First, we divided the tasks into categories according to task themes. Then, we constructed and calculated the Abilities Set (AS), Abilities Values (AVs), and the Friends’ Abilities Matrix (FAM) by using the historical interactive texts between a given task publisher (requester) and its friends. When a requester distributes a task, TDSRC can generate the candidate participators’ sequence based on the task needs and FAM. Finally, the best-matched friends in the sequence are selected as the task receivers (solvers), thus producing a personal FAM to disseminate the tasks. The experimental results indicate that (1) the proposed system can accurately and effectively discover the requester’s friends’ abilities and select appropriate solvers and (2) the natural trust relationship in the social network reduces fraudsters and enhances the quality of crowdsourcing services.

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Section: Related Workmentioning

confidence: 99%

“…According to the concept of "six degrees of separation", a task can be sent to anybody in the world by transferring six times [23][24][25][26]. Every time, we let a participant push the task to α friends in his social network (the value of α can be changed according to the demand).…”

Section: Quick Task-distribution Mode Based On Abilitiesmentioning

confidence: 99%