基于用户行为数据分析的在线服务需求理解

Qing Zhou, Lin Liu
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引用次数: 1

摘要

用户行为数据为当前软件设计的不足提供了重要线索,并为未来的设计提供了改进点。今天基于web的软件服务提供商可以收集不同类型的服务使用数据,这是一个很好的信息来源,可以帮助开发人员更好地了解用户的行为。本文以在线词典服务的演变为例,探讨了以下问题的答案:软件产品设计和服务内容质量的关键指标是什么,以及如何通过用户行为数据分析获得的理解来提高新产品的成功。本文首先总结了目前可以收集到的网络日志数据的可能类型,然后介绍了基于用户行为数据分析为字典域生成的用户行为模型,然后讨论了数据收集功能如何与在线服务协同发展,以及具体的数据分析方法如挖掘算法和统计函数如何帮助生成对设计决策者有价值的有趣的分析结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Understanding Requirements for Online Services Based on Users' Behavioural Data Analysis
User behavioural data provides important cue for deficiencies in the current software design, and points for improvement in future design. Today's web based software services providers could collect different kinds of service usage data, which is a good source of information which can help developers better understand user's behaviours. This paper takes the example of the evolution of an online dictionary services, explores answers for questions such as: what are the key indicators with regard to the quality of software product design and service content, and how to enhance new product success by understandings obtained from user behavioural data analysis. In this paper, we first summarise the possible types of web log data that can be collected so far, Then we introduce a user behaviour model generated for the dictionary domain based on user behavioural data analysis, then we discuss how data collection function shall co-evolve with the online services, and how specific data analysis approaches such as mining algorithms and statistical functions can help generate interesting analysis results of value to design decision makers.
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