协同标记 - 版本历史

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用于知识获取的社会化标签

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用于知识获取的社会化标签

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Folksonomy vs. taxonomy

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	* [http://www.vanderwal.net/random/entrysel.php?blog=1750 Vanderwal's take on Wikipedia's definition of folksonomy]		* [http://www.vanderwal.net/random/entrysel.php?blog=1750 Vanderwal's take on Wikipedia's definition of folksonomy]
	*[http://er.educause.edu/articles/2011/9/classroom-collaboration-using-social-bookmarking-service-diigo Classroom Collaboration Using Social Bookmarking Service Diigo]		*[http://er.educause.edu/articles/2011/9/classroom-collaboration-using-social-bookmarking-service-diigo Classroom Collaboration Using Social Bookmarking Service Diigo]
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		+	==编者推荐==
		+	===集智课程===
		+	====[https://campus.swarma.org/course/1873 在线知识分享系统的知识协同构建]====
		+	基于知识协同建构理论，本研究利用语词共现网络分析，将知识疆域量化为标签共现网络。本研究旨在描述，以知乎为代表的在线知识分享平台，其知识疆域的内容特点和演化模式。本研究分别探究了知识疆域的内容与结构特征、知识疆域的演化规律以及节点的生成、死亡与生存机制。从理论意义而言，本研究廓清了 “知识协同建构理论”视域下在线“协作知识”内容与结构特征，印证了协同建构的在线知识整体特征。从方法论意义而言，该课题基于大数据分析技术，运用文本挖掘、社会网络分析，以及Pathfinder算法，对大规模知识文本进行分析和可视化呈现，对在线文本挖掘分析的借鉴意义。从社会意义而言，本研究成果综合评估了在线知识分享平台的知识疆域普惠性。
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 ==参考文献==
 {{refbegin}}
 *{{cite book |last1=Bateman |first1=S. |last2=Brooks |first2=C. |last3=McCalla |first3=G. |last4=Brusilovsky |first4=P.  |chapter=Applying collaborative tagging to e-learning |chapter-url=http://www.www2007.org/workshops/paper_56.pdf |title=Proceedings of the 16th International World Wide Web Conference (WWW2007) |date=2007 |citeseerx=10.1.1.64.8892}}
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 *{{cite book |first=David |last=Weinberger |title=Everything Is Miscellaneous: The Power of the New Digital Disorder |url=https://books.google.com/books?id=Hl0DGfKPn2MC |date=2007 |publisher=Henry Holt}}
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 *[http://er.educause.edu/articles/2011/9/classroom-collaboration-using-social-bookmarking-service-diigo Classroom Collaboration Using Social Bookmarking Service Diigo]
 [[Category:Folksonomy| ]]
 [[Category:Collective intelligence]]

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	与特定内容频繁的共同出现的标签通常被认为是连接性更强的标记。此外，标签可以相互连接，这可以从它们共同出现的频率中看出来。它们共同出现的次数越多，联系就越紧密。标签云通常用于可视化资源和标记之间的连接，字体大小随着关联强度的增加而增加。<ref name=":1">Kimmerle, J., Cress, U., & Held, C. (2010). The interplay between individual and collective knowledge: technologies for organisational learning and knowledge building. Knowledge Management Research & Practice, 8(1), 33-44.</ref>		与特定内容频繁的共同出现的标签通常被认为是连接性更强的标记。此外，标签可以相互连接，这可以从它们共同出现的频率中看出来。它们共同出现的次数越多，联系就越紧密。标签云通常用于可视化资源和标记之间的连接，字体大小随着关联强度的增加而增加。<ref name=":1">Kimmerle, J., Cress, U., & Held, C. (2010). The interplay between individual and collective knowledge: technologies for organisational learning and knowledge building. Knowledge Management Research & Practice, 8(1), 33-44.</ref>
−
−	Tags show interconnections of concepts that were formerly unknown to a user. Therefore, a user's current cognitive constructs may be modified or augmented by the metadata information found in aggregated social tags. This process promotes knowledge acquisition through cognitive irritation and equilibration. This theoretical framework is known as the co-evolution model of individual and collective knowledge.<ref name=":1" />
−
−	Tags show interconnections of concepts that were formerly unknown to a user. Therefore, a user's current cognitive constructs may be modified or augmented by the metadata information found in aggregated social tags. This process promotes knowledge acquisition through cognitive irritation and equilibration. This theoretical framework is known as the co-evolution model of individual and collective knowledge.

	标签显示了以前用户不知道的概念之间的相互联系。因此，用户当前的认知结构可能会被聚合的社会化标签中的元数据信息修改或增强。这个过程通过认知刺激和平衡促进知识的获得，这个理论框架被称为个体和集体知识的协同进化模型。<ref name=":1" />		标签显示了以前用户不知道的概念之间的相互联系。因此，用户当前的认知结构可能会被聚合的社会化标签中的元数据信息修改或增强。这个过程通过认知刺激和平衡促进知识的获得，这个理论框架被称为个体和集体知识的协同进化模型。<ref name=":1" />

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 用户为存储的资源选择单独的标签。这些标签反映了个人联系、类别和概念。所有这些都是基于个人意义和相关性的个性化表达。这些标签或者关键字是由用户指定的。因此，标签表示与资源对应的用户关联。通常标签的资源包括视频、照片、文章、网站和电子邮件。标签的好处体现在几个方面：第一是它们帮助构建和组织大量的数字资源，以便当用户以后试图查找资源时能够方便地访问这些资源。第二是社会化的本质，也就是说用户可以根据其他用户的标签来搜索新的资源和内容，甚至仅仅通过普通标签浏览也可能为知识获取提供更多的资源。<ref name=":0" />
-Tags that occur more frequently with specific resources are said to be more strongly connected. Furthermore, tags may be connected to each other. This may be seen in the frequency in which they co-occur. The more often they co-occur, the stronger the connection. Tag clouds are often utilized to visualize connectivity between resources and tags. Font size increases as the strength of association increases.<ref name=":1">Kimmerle, J., Cress, U., & Held, C. (2010). The interplay between individual and collective knowledge: technologies for organisational learning and knowledge building. Knowledge Management Research & Practice, 8(1), 33-44.</ref>
+与特定内容频繁的共同出现的标签通常被认为是连接性更强的标记。此外，标签可以相互连接，这可以从它们共同出现的频率中看出来。它们共同出现的次数越多，联系就越紧密。标签云通常用于可视化资源和标记之间的连接，字体大小随着关联强度的增加而增加。<ref name=":1">Kimmerle, J., Cress, U., & Held, C. (2010). The interplay between individual and collective knowledge: technologies for organisational learning and knowledge building. Knowledge Management Research & Practice, 8(1), 33-44.</ref>
 Tags show interconnections of concepts that were formerly unknown to a user. Therefore, a user's current cognitive constructs may be modified or augmented by the metadata information found in aggregated social tags. This process promotes knowledge acquisition through cognitive irritation and equilibration. This theoretical framework is known as the co-evolution model of individual and collective knowledge.<ref name=":1" />
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 Tags show interconnections of concepts that were formerly unknown to a user. Therefore, a user's current cognitive constructs may be modified or augmented by the metadata information found in aggregated social tags. This process promotes knowledge acquisition through cognitive irritation and equilibration. This theoretical framework is known as the co-evolution model of individual and collective knowledge.
-标签显示了以前用户不知道的概念之间的相互联系。因此，用户当前的认知结构可能会被聚合的社会化标签中的元数据信息修改或增强。这个过程通过认知刺激和平衡促进知识的获得，这个理论框架被称为个体和集体知识的协同进化模型。
+标签显示了以前用户不知道的概念之间的相互联系。因此，用户当前的认知结构可能会被聚合的社会化标签中的元数据信息修改或增强。这个过程通过认知刺激和平衡促进知识的获得，这个理论框架被称为个体和集体知识的协同进化模型。<ref name=":1" />
-The co-evolution model focuses on cognitive conflict in which a learner's prior knowledge and the information received from the environment are dissimilar to some degree.<ref name=":0" /><ref name=":1" /> When this incongruence occurs, the learner must work through a process cognitive equilibration in order to make personal cognitive constructs and outside information congruent. According to the coevolution model, this may require the learner to modify existing constructs or simply add to them.<ref name=":0" /> The additional cognitive effort promotes information processing which in turn allows individual learning to occur.<ref name=":1" />
+协同进化模型着眼于认知冲突，即学习者的先验知识和从环境中获得的信息在一定程度上是不一致的。当这种不一致发生时，学习者必须通过一个认知平衡的过程来使个人认知结构和外部信息一致。根据协同进化模型，这可能需要学习者对现有的构造进行修改或添加。额外的认知努力促进了信息处理，而信息处理又促进了个体学习的发生。<ref name=":1" />
 ==Examples==
-* [[BibSonomy]]: social bookmarking and publication-sharing system
+* [[BibSonomy]]: 社会化书签育出版共享系统
-* [[Delicious (website)|del.icio.us]]: public tagging service
+* [[Delicious (website)|del.icio.us]]: 公共标签服务
-* [[Diigo]]: [[social bookmarking]] website
+* [[Diigo]]: 社会化书签网站
-* [[Flickr]]: shared photos
+* [[Flickr]]: 照片共享
-* [[Instagram]]: online photo-sharing and social networking service
+* [[Instagram]]: 在线照片共享与社交服务
 * Many [[Library catalog#Online catalogs|libraries' online catalogs]]<ref>Steele, T. (2009).  The new cooperative cataloging.  Library Hi Tech, 27 (1), 68-77</ref><ref>Corey A. Harper and [[Barbara B. Tillett]], [https://archive.today/20130410094132/https://scholarsbank.uoregon.edu/dspace/bitstream/1794/3269/1/ccq_s Library of Congress controlled vocabularies and their application to the Semantic Web]</ref>
-* [[Mendeley]]: social reference management software
+* [[Mendeley]]: 社会参考管理软件
-* [[Pinterest]]: photosharing and publishing website
+* [[Pinterest]]:  照片共享与发布网站
 * [[Steam (service)|Steam]] video game store
-* [[StumbleUpon]]: content discovery engine
+* [[StumbleUpon]]:  内容发现引擎
 * [[Twitter]] [[hashtag]]s
 * The [[World Wide Web Consortium]]'s [[Annotea]] project with user-generated tags in 2002.
-* [[WordPress]]: blogging tool and Content Management System
+* [[WordPress]]: 博客撰写与内容管理
-*[http://tumblr.com Tumblr] tags
+*[http://tumblr.com Tumblr] ：标签<br />
 ==其他内容==
 {{div col|colwidth=30em}}
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 * [[Wiki]]
 {{div col end}}
 * 自动标签

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 作为广义协同标记的网站， del.icio.us允许用户使用自己的个人标签标记任何他们发现的相关的在线资源的网站。 Flickr 作为一个照片分享网站，是狭义协同标记的典型例子。
-==Folksonomy vs. taxonomy==
+==协同标记与分类方法 ==
 'Taxonomy' refers to a [[hierarchical categorization]] in which relatively well-defined classes are nested under broader categories. A ''folksonomy'' establishes categories (each tag is a category) without stipulating or necessarily deriving a hierarchical structure of parent-child relations among different tags. (Work has been done on techniques for deriving at least loose hierarchies from clusters of tags.<ref>{{cite journal|last1=Laniado|first1=David|title=Using WordNet to turn a folksonomy into a hierarchy of concepts|journal=CEUR Workshop Proceedings|volume=314|issue=51|url=http://ceur-ws.org/Vol-314/51.pdf|access-date=7 August 2015}}</ref>)
 'Taxonomy' refers to a hierarchical categorization in which relatively well-defined classes are nested under broader categories. A folksonomy establishes categories (each tag is a category) without stipulating or necessarily deriving a hierarchical structure of parent-child relations among different tags. (Work has been done on techniques for deriving at least loose hierarchies from clusters of tags.)
-“分类法”是指一种层次分类，其中定义相对良好的类被嵌套在更广泛的类别中。大众分类法建立了类别(每个标记都是一个类别) ，但是没有规定或者必须在不同的标记之间得到父子关系的层次结构。(已经研究了从标记集群中至少衍生出松散层次结构的技术。)
+“分类法”是指一种层次分类，将定义相对良好的类被嵌套在更广泛的类别中。协同标记建立的分类目录，不规定或者必须在不同的标签之间的道父子关系的层次结构类别，即每个标记就是一个类别(已经有从标签集群中至少衍生出松散层次结构的技术)。
 Supporters of folksonomies claim that they are often preferable to taxonomies because folksonomies democratize the way information is organized, they are more useful to users because they reflect current ways of thinking about domains, and they express more information about domains.<ref>{{cite web|last1=Weinberger|first1=David|title=Folksonomy as Symbol|url=http://www.hyperorg.com/blogger/?p=6254|website=Joho the Blog|access-date=7 August 2015}}</ref> Critics claim that folksonomies are messy and thus harder to use, and can reflect transient trends that may misrepresent what is known about a field.
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 Supporters of folksonomies claim that they are often preferable to taxonomies because folksonomies democratize the way information is organized, they are more useful to users because they reflect current ways of thinking about domains, and they express more information about domains. Critics claim that folksonomies are messy and thus harder to use, and can reflect transient trends that may misrepresent what is known about a field.
-支持 folksonomies 的人声称，他们通常比分类法更可取，因为 folksonomies 使信息的组织方式民主化，他们对用户更有用，因为他们反映了当前对领域的思考方式，他们表达了更多关于领域的信息。批评者声称，民俗分类法杂乱无章，因此难以使用，而且可以反映出短暂的趋势，可能会歪曲某一领域的已知信息。
+支持 协同标记的人声称，他们通常比分类法更可取，因为协同标记使信息的组织方式民主化，他们对用户更有用，因为他们反映了当前对领域的思考方式，他们表达了更多关于领域的信息。批评者声称，协同标记杂乱无章，难以使用，而且反映出的短暂趋势可能会歪曲某一领域的已知信息。
 An empirical analysis of the complex dynamics of tagging systems, published in 2007,<ref name="WWW07-ref" >Harry Halpin, Valentin Robu, Hana Shepherd [http://portal.acm.org/citation.cfm?id=1242572.1242602 The Complex Dynamics of Collaborative Tagging], Proc. International Conference on World Wide Web, ACM Press, 2007.</ref> has shown that consensus around stable distributions and shared vocabularies does emerge, even in the absence of a central [[controlled vocabulary]]. For content to be searchable, it should be categorized and grouped. While this was believed to require commonly agreed on sets of content describing tags (much like keywords of a journal article), some research has found that in large folksonomies common structures also emerge on the level of categorizations.<ref name="TWEB-ref" >V. Robu, H. Halpin, H. Shepherd [http://portal.acm.org/citation.cfm?id=1594173.1594176 Emergence of consensus and shared vocabularies in collaborative tagging systems], ACM Transactions on the Web (TWEB), Vol. 3(4), art. 14, 2009.</ref>
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 Accordingly, it is possible to devise mathematical models of collaborative tagging that allow for translating from personal tag vocabularies (personomies) to the vocabulary shared by most users.Robert Wetzker, Carsten Zimmermann, Christian Bauckhage, and Sahin Albayrak I tag, you tag: translating tags for advanced user models, Proc. International Conference on Web Search and Data Mining, ACM Press, 2010.
-年发表的一篇关于复动力学标签系统的实证分析，Harry Halpin，Valentin Robu，Hana Shepherd，复动力学的分众分类法标签系统，Proc。万维网国际会议，美国计算机学会出版社，2007年。已经表明，围绕稳定发行版和共享词汇表的共识确实出现了，即使在没有核心受控词表的情况下。对于可搜索的内容，应该对其进行分类和分组。虽然这被认为需要在描述标签的内容集上达成共识(很像期刊文章的关键词) ，但是一些研究发现，在大型民俗学中，常见结构也出现在 categorizations.V 的层面上。分众分类法系统中共识和共享词汇的出现，ACM Transactions on the Web (TWEB) ，Vol。3(4) ，艺术。14, 2009.因此，我们可以设计出分众分类法的数学模型，从而将个人标记词汇(personomies)转换为大多数用户共享的词汇。和 Sahin Albayrak i tag，you tag: translating tags for advanced user models，Proc。网络搜索和数据挖掘国际会议，ACM 出版社，2010年。
+年发表的一篇关于复动力学标签系统的实证分析表明，即使在没有核心受控词表的情况下，围绕稳定发布和共享词汇表的共识也确实出现了。对于可搜索的内容，应该对其进行分类和分组。虽然大家普遍认为需要像期刊关键词一样，在描述标签的内容集上达成共识。但是一些研究发现，在一些常见的目录水平的协同标记结构也出现了。因此，我们可以设计出协同设计的数学模型，从而将个人标记词汇转换为更加大众化的词汇。
 Folksonomy is unrelated to [[folk taxonomy]], a cultural practice that has been widely documented in anthropological and [[folkloristics|folkloristic]] work. Folk taxonomies are culturally supplied, intergenerationally transmitted, and relatively stable classification systems that people in a given culture use to make sense of the entire world around them (not just the [[Internet]]).<ref name="Berlin, B. 1992"/>
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 Folksonomy is unrelated to folk taxonomy, a cultural practice that has been widely documented in anthropological and folkloristic work. Folk taxonomies are culturally supplied, intergenerationally transmitted, and relatively stable classification systems that people in a given culture use to make sense of the entire world around them (not just the Internet).
-民间分类法与民间分类法无关，这种文化实践在人类学和民间分类学著作中得到了广泛的记载。民间分类法是文化上提供的、代际间传播的、相对稳定的分类系统，特定文化中的人们使用这些系统来理解他们周围的整个世界(而不仅仅是互联网)。
+协同标记与民间分类法无关，这种文化实践在人类学和民间分类学著作中得到了广泛的记载。民间分类法是文化上提供的、代际间传播的、相对稳定的分类系统，特定文化中的人们使用这些系统来理解他们周围的整个世界，而不仅仅是互联网。
 The study of the structuring or classification of folksonomy is termed ''folksontology''.<ref>{{cite web | url=http://www.heppnetz.de/files/vandammeheppsiorpaes-folksontology-semnet2007-crc.pdf | title=FolksOntology: An Integrated Approach for Turning Folksonomies into Ontologies | access-date=April 20, 2012 | author=Van Damme, Céline|display-authors=etal}}</ref> This branch of [[ontology (information science)|ontology]] deals with the intersection between highly structured taxonomies or hierarchies and loosely structured folksonomy, asking what best features can be taken by both for a system of classification. The strength of flat-tagging schemes is their ability to relate one item to others like it. Folksonomy allows large disparate groups of users to collaboratively label massive, dynamic information systems. The strength of taxonomies are their browsability: users can easily start from more generalized knowledge and target their queries towards more specific and detailed knowledge.<ref>Trattner, C., Körner, C., Helic, D.: [http://www.christophtrattner.info/pubs/iknow2011.pdf Enhancing the Navigability of Social Tagging Systems with Tag Taxonomies]. In Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies, ACM, New York, NY, USA, 2011</ref> Folksonomy looks to categorize tags and thus create browsable spaces of information that are easy to maintain and expand.
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 The study of the structuring or classification of folksonomy is termed folksontology. This branch of ontology deals with the intersection between highly structured taxonomies or hierarchies and loosely structured folksonomy, asking what best features can be taken by both for a system of classification. The strength of flat-tagging schemes is their ability to relate one item to others like it. Folksonomy allows large disparate groups of users to collaboratively label massive, dynamic information systems. The strength of taxonomies are their browsability: users can easily start from more generalized knowledge and target their queries towards more specific and detailed knowledge.Trattner, C., Körner, C., Helic, D.: Enhancing the Navigability of Social Tagging Systems with Tag Taxonomies. In Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies, ACM, New York, NY, USA, 2011 Folksonomy looks to categorize tags and thus create browsable spaces of information that are easy to maintain and expand.
-研究大众分类法的结构或分类称为大众分类学。本体论的这个分支处理高度结构化的分类法或层次结构与松散结构大众分类法之间的交叉，询问这两者对于一个分类系统可以采用哪些最佳特性。平面标签方案的优势在于它们能够将一个项目与类似的其他项目联系起来。大众分类允许大型不同用户群体协作标记大规模的动态信息系统。分类法的优势在于它们的可浏览性: 用户可以很容易地从更广泛的知识开始，并将他们的查询定向到更具体和详细的知识。特拉特纳，c. ，k ö rner，c. ，Helic，d. : 通过标记分类增强社会标签系统的可导航性。在第11届知识管理和知识技术国际会议论文集中，ACM，纽约，纽约，美国，2011年 Folksonomy 期望对标签进行分类，从而创建易于维护和扩展的可浏览的信息空间。
+研究协同标记的结构或分类称为协同分类学。本体论的这个分支处理高度结构化的分类或层次结构与协同标记之间的交叉，寻找对于一个分类系统来说可以采用的最佳特性有哪些。平面标签方案的优势在于它们能够将一个项目与类似的其他项目联系起来。协同标记则允许大型不同用户群体协作标记大规模的动态信息系统。分类法的优势在于它们的可浏览性: 用户可以很容易地从更广泛的知识开始，并将他们的查询定向到更具体和详细的知识。 如果系统标记能够对标签进行分类，则可以创建易于维护和扩展的可浏览的信息空间。
-== Social tagging for knowledge acquisition ==
+== 用于知识获取的社会化标签 ==
 Social tagging for [[knowledge acquisition]] is the specific use of tagging for finding and re-finding specific content for an individual or group. Social tagging systems differ from traditional taxonomies in that they are community-based systems lacking the traditional hierarchy of taxonomies. Rather than a top-down approach, social tagging relies on users to create the folksonomy from the bottom up.<ref name=":0">Held, C., & Cress, U. (2009). Learning by Foraging: The impact of social tags on knowledge acquisition. In Learning in the synergy of multiple disciplines (pp. 254-266). Springer Berlin Heidelberg.</ref>