In:
Concurrency and Computation: Practice and Experience, Wiley, Vol. 30, No. 24 ( 2018-12-25)
Abstract:
With the development of Internet plus technologies such as IoT, cloud computing, mobile Internet, and big data analysis, several new forms of sports community, which provided significant conveniences to the exercisers, were proposed. However, online communications are still deficient, and relationships among exercisers and between exercisers and sports activities are absent. To solve these problems, an Internet plus O2O sports community was proposed, and the idea and methods of sports activities management are discussed in this paper. Firstly, the activity management framework contributed by activity organizers, participants, and followers is constructed using cloud storage technology. Responsibilities of different kinds of users and constitution of activity data are also described. Secondly, six personalized recommendation algorithms, including tag‐based, relationship‐based, ranking list–based, content‐based, content‐based collaborative filtering, and user‐based collaborative filtering algorithms and their application in sports community are presented. Thirdly, a novel activity management model is designed, which supports online‐offline deep fusion and provides management of the whole procedures of a sports activity. Primary tasks of different activity stages are described. Finally, analysis methods and exhibition forms of statistics, text, and multimedia data are discussed.
Type of Medium:
Online Resource
ISSN:
1532-0626
,
1532-0634
Language:
English
Publisher:
Wiley
Publication Date:
2018
detail.hit.zdb_id:
2052606-4
SSG:
11
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