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Data Analysis and Knowledge Discovery  2018, Vol. 2 Issue (5): 23-31    DOI: 10.11925/infotech.2096-3467.2017.1218
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Mining User Preferences in Crowdsourcing Community with Sensitivity Analysis
Zhang Tingting1(), Zhao Yuxiang2, Zhu Qinghua3
1School of Engineering and Management, Nanjing University, Nanjing 210093, China
2School of Economics and Management, Nanjing University of Science and Technology, Nanjing 210094, China
3School of Information Management, Nanjing University, Nanjing 210093, China
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[Objective] This paper analyzes the attributes and task characteristics of crowdsourcing community users, aiming to identify their potential interests or preferences. [Methods] First, we studied the user’s sensitivity to task attributes based on sensitivity analysis method, and constructed a model for mining user’s potential preferences with bipartite graph. Then, we used this model to discover the implicit preferences from user’s behaviors. Finally, we confirmed the validity of the proposed model through experimental analysis. [Results] Our model could effectively identify the degrees of users’ sensitivity to Books, Software, and Music etc. It could also discover users’ potential interests or preferences to Pyrex Oblong Roaster, Oxford, and Cashback etc. to predict their choices. Compared with traditional collaborative filtering algorithms, the proposed model has a smaller MAE value. [Limitations] Our preferences mining model is based on users in the competitive environment, and it does not consider the complementarity among the interests of collaborative users. [Conclusions] The proposed model could accurately understand the users’ interests in crowdsourcing community, and then reveal their potential preferences. It helps us effectively distribute crowdsourcing tasks.

Key wordsCrowdsourcing      Task-User Fit      Attribute Feature      Sensitivity Analysis      Potential Preferences Mining     
Received: 05 December 2017      Published: 20 June 2018
ZTFLH:  N99  

Cite this article:

Zhang Tingting,Zhao Yuxiang,Zhu Qinghua. Mining User Preferences in Crowdsourcing Community with Sensitivity Analysis. Data Analysis and Knowledge Discovery, 2018, 2(5): 23-31.

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User ID Products Categories of the Products Rating
5247778 ‘Wader Basics Tow Truck’ ‘Family’ 5
5247778 ‘Arthur in a pickle - Marc Brown' 'Books' 4
5647565 'Straightheads (DVD)' 'DVDs' 4
3338 'Oxford (England)' 'Travel' 4
6496990 'Top Gun (Blu-ray)' 'DVDs' 5
用户 用户编号
众包用户1 5247778
众包用户2 5647565
众包用户3 3338
众包用户4 5769137
众包用户5 6496990
众包用户6 5241292
众包任务 描述
任务1 Pyrex Oblong Roaster
任务2 Wader Basics Tow Truck
任务3 Straw Craft: More GoldenDollies-M.Lambeth
任务4 Arthur in a pickle-Marc Brown
任务5 Straight heads (DVD)
任务6 The Daughter of Time-Josephine Tey
任务7 Rebecca Wheatley-The New Me Workout(DVD)
任务8 Oxford (England)
任务9 Cashback (DVD)
任务10 Movie Collector: DVD Database Software
任务11 Free All Angels [ECD]-Ash
任务12 Take A Break''s Fate & Fortune
属性 描述 属性 描述
属性1 House & Garden 属性6 Software
属性2 Family 属性7 Food & Drink
属性3 Books 属性8 Beauty
属性4 DVDs 属性9 Music
属性5 Travel 属性10 Entertainment
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