摘要翻译:
我们分析了del.icio.us的一个大规模快照,并研究了系统中不同标记的数量是如何随着适当定义的时间概念而增长的。我们研究了全局词汇量的时间演化,即整个系统中不同标签的数量,以及局部词汇量的演化,即给定资源或用户上下文中使用的不同标签数量的增长。在这两种情况下,我们都发现指数小于1的幂律行为。令人惊讶的是,观察到的生长行为在整个系统的历史中以及在被书签的非常不同的资源中都是非常有规律的。在书面文本中也观察到了类似的亚线性增长规律,这种定性的普遍性要求对协作标记的复杂交互模式中的非琐碎认知过程进行解释和指出方向。
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英文标题:
《Vocabulary growth in collaborative tagging systems》
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作者:
Ciro Cattuto, Andrea Baldassarri, Vito D. P. Servedio, Vittorio Loreto
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最新提交年份:
2007
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分类信息:
一级分类:Computer Science 计算机科学
二级分类:Information Retrieval 信息检索
分类描述:Covers indexing, dictionaries, retrieval, content and analysis. Roughly includes material in ACM Subject Classes H.3.0, H.3.1, H.3.2, H.3.3, and H.3.4.
涵盖索引,字典,检索,内容和分析。大致包括ACM主题课程H.3.0、H.3.1、H.3.2、H.3.3和H.3.4中的材料。
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一级分类:Physics 物理学
二级分类:Statistical Mechanics 统计力学
分类描述:Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变,热力学,场论,非平衡现象,重整化群和标度,可积模型,湍流
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一级分类:Computer Science 计算机科学
二级分类:Computers and Society 计算机与社会
分类描述:Covers impact of computers on society, computer ethics, information technology and public policy, legal aspects of computing, computers and education. Roughly includes material in ACM Subject Classes K.0, K.2, K.3, K.4, K.5, and K.7.
涵盖计算机对社会的影响、计算机伦理、信息技术和公共政策、计算机的法律方面、计算机和教育。大致包括ACM学科类K.0、K.2、K.3、K.4、K.5和K.7中的材料。
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一级分类:Physics 物理学
二级分类:Data Analysis, Statistics and Probability 数据分析、统计与概率
分类描述:Methods, software and hardware for physics data analysis: data processing and storage; measurement methodology; statistical and mathematical aspects such as parametrization and uncertainties.
物理数据分析的方法、软硬件:数据处理与存储;测量方法;统计和数学方面,如参数化和不确定性。
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英文摘要:
We analyze a large-scale snapshot of del.icio.us and investigate how the number of different tags in the system grows as a function of a suitably defined notion of time. We study the temporal evolution of the global vocabulary size, i.e. the number of distinct tags in the entire system, as well as the evolution of local vocabularies, that is the growth of the number of distinct tags used in the context of a given resource or user. In both cases, we find power-law behaviors with exponents smaller than one. Surprisingly, the observed growth behaviors are remarkably regular throughout the entire history of the system and across very different resources being bookmarked. Similar sub-linear laws of growth have been observed in written text, and this qualitative universality calls for an explanation and points in the direction of non-trivial cognitive processes in the complex interaction patterns characterizing collaborative tagging.
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PDF链接:
https://arxiv.org/pdf/704.3316


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