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Using Mobile Services Based on SNS to Recommend Who, How, and When to Collaborate

机译:使用基于SNS的移动服务推荐谁,如何以及何时进行协作

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摘要

The rising popularity of smart phones and social networking services (SNS) is changing many aspects of people's collaboration. With the wide use of smart phones, collaborative work based on mobile web becomes loose and flexible. Collaborators have more chances to collaborate with other people anywhere at anytime. But most supporting tools for traditional computer supported cooperative work just support defined collaborative process for certain collaborators. They can't satisfy the new requirements for loose collaboration where collaborators, collaborative process and time are unknown. In this paper, we presentation approach to using three mobile services based on SNS and mobile sensor data to recommend who, how and when to collaborate. This collaborative approach based on mobile services solves three basic key problems of modern collaboration. Firstly, we collect abundant data from SNS, do the semantic analysis, and dig out the suitable collaborators. Secondly, by analyzing the data from calendars and smart phones, we figure out the situations which collaborators are in, then reason the suitable contacts by our novel rules and finally recommend whether we can call or not, as well as the ranked text contacts. Thirdly, we use the calendar information to recommend the common free time for collaborators to work together. To verify the effectiveness of the approach and accuracy of collaborative recommendations, we have implemented an app including the services on android platform and designed two independent experiments. The case studies show the approach provides an effective and accurate means for collaborative recommendations.
机译:智能手机和社交网络服务(SNS)的日益普及正在改变人们协作的许多方面。随着智能电话的广泛使用,基于移动Web的协作工作变得宽松而灵活。协作者有更多机会随时随地与其他人协作。但是,大多数用于传统计算机支持的协作工作的支持工具仅支持为某些协作者定义的协作过程。在协作者,协作过程和时间未知的情况下,他们无法满足松散协作的新要求。在本文中,我们介绍了使用基于SNS和移动传感器数据的三种移动服务来建议谁,如何以及何时进行协作的方法。这种基于移动服务的协作方法解决了现代协作的三个基本关键问题。首先,我们从SNS收集大量数据,进行语义分析,并找出合适的协作者。其次,通过分析日历和智能手机中的数据,我们可以确定协作者所在的情况,然后根据我们的新规则推理出合适的联系人,最后建议我们是否可以打电话以及排名靠前的文本联系人。第三,我们使用日历信息为合作者推荐共同的空闲时间。为了验证该方法的有效性和协作推荐的准确性,我们在Android平台上实现了一个包含服务的应用程序,并设计了两个独立的实验。案例研究表明,该方法为协作推荐提供了有效而准确的方法。

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