Groupsourcing

Rokicki, Markus; Zerr, Sergej; Siersdorfer, Stefan

doi:10.1145/2736277.2741097

Cited by 51 publications

(14 citation statements)

References 19 publications

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“…In this method, employees try and evaluate different candidate partners. Rokicki [7] explores a cohesive strategy that includes self-organization. In this strategy, workers (initially in the form of a one-man team) can decide which team they want to join or who could join their team.…”

Section: A Team Formation Problemmentioning

confidence: 99%

“…do nothing 11. end for First, judge whether the visited node in Step 5 of algorithm 1 is its own precursor, if it is, do nothing (step 1-2); if not, record ai as the precursor of ax, traverse the precursor set of ax to update ax's optimal precursor in task t (step [3][4][5][6][7][8][9][10][11]. In this process, if the optimal precursor of ax changes to ai, the shortest distance between ax and It is recalculated by calDist(t,ax) (step 8).…”

Section: ) Determine the Optimal Precursormentioning

confidence: 99%

“…Cnew += c(ax,gj)* q(ax,gj,t2)*(1+η(It2,ax)) agree(It, It2, gj, ai, Contribution) If Nt2 has started to supply, It2 will directly reject the coordination request of It (step 3-4), otherwise, it will try to find a node that can replace ai to supply gj (step [5][6][7][8][9][10][11][12][13][14][15][16][17]. The PreDecide method is used to meet the gj requirements of q(ai,gj,t2) (step 10) (the method will be detailed below) until all requirements are met (step [15][16].…”

Section: ) Judge Stagementioning

confidence: 99%

“…The demander wants to build a supply network that covers the task demand in both type and quantity. Unlike the previous "team formation problem" [1][2][3][4][5][6][7][8][9][10][11], we had to redesign the solution because of the following characteristics of the supply-demand matching problem:①The same service or product requirement in a task can be segmented to multiple providers to provide collaboratively; ② Different from contributing skills, suppliers of services or products may face capacity caps; ③A single supplier can supply multiple products and services to multiple demanders simultaneously. Besides, due to the selfishness of members in practical application [12] [13], the scheme must be feasible under the constraints of non-cooperation.…”

Section: Introductionmentioning

confidence: 99%

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Supply-Demand Matching in Non-Cooperative Social Networks

Zhang

Wang

et al. 2020

IEEE Access

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The complex supply-demand matching problem is a kind of social service computing problem, which can be applied to the coordinated production of products or the supply of service. In this scenario, the demander needs a number of suppliers to provide services or products to complete a given task. The key to solving this problem is to build a supply network that covers the requester's requirement. Traditional collaboration issues in social network mainly focused on the "team formation problem", that is to build a team that covers all the skills required for the task. However, due to the complex characteristics of supply-demand matching problems in the application of social services, the team formation method is limited and inefficient, and there is no special solution for the complex supply-demand matching problems in social network. This paper proposes a general framework to solve the complex matching problem of supply and demand. On the premise of non-cooperative constraints, social networks are used to build supply networks with low communication loss, and the unnecessary cost is reduced through cooperation.

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Section: A Team Formation Problemmentioning

confidence: 99%

Section: ) Determine the Optimal Precursormentioning

confidence: 99%

Section: ) Judge Stagementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Supply-Demand Matching in Non-Cooperative Social Networks

Zhang

Wang

et al. 2020

IEEE Access

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“…For instance, in Rokicki et al . (2015) a human team competition mechanism improves cost efficiency and the quality of a solution in a team-based crowdsourcing scenario. In conventional crowdsourcing reward schemes, the payment of online workers is proportional to the number of accomplished tasks (pay-per-task).…”

Section: Team Composition and Formation From A Computer Science Perspmentioning

confidence: 99%

The composition and formation of effective teams: computer science meets organizational psychology

Andrejczuk¹,

Berger

Rodŕıguez-Aguilar³

et al. 2018

The Knowledge Engineering Review

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Nowadays the composition and formation of effective teams is highly important for both companies to assure their competitiveness and for a wide range of emerging applications exploiting multiagent collaboration (e.g. crowdsourcing, human-agent collaborations). The aim of this article is to provide an integrative perspective on team composition, team formation and their relationship with team performance. Thus, we review the contributions in both the computer science literature and the organisational psychology literature dealing with these topics. Our purpose is twofold. First, we aim at identifying the strengths and weaknesses of the contributions made by these two diverse bodies of research. Second, we pursue to identify cross-fertilisation opportunities that help both disciplines benefit from one another. Given the volume of existing literature, our review is not intended to be exhaustive. Instead, we have preferred to focus on the most significant contributions in both fields together with recent contributions that break new ground to spur innovative research.1. Capacity: individual and social capabilities of agents; and 2. Personality: individual behaviour models.

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CrowdMashup: Recommending Crowdsourcing Teams for Mashup Development

Binzagr

Medjahed

2018

Service-Oriented Computing

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Groupsourcing

Cited by 51 publications

References 19 publications

Supply-Demand Matching in Non-Cooperative Social Networks

Supply-Demand Matching in Non-Cooperative Social Networks

The composition and formation of effective teams: computer science meets organizational psychology

CrowdMashup: Recommending Crowdsourcing Teams for Mashup Development

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