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The Human Position in an Artificial World: Creativity, Ethics and AI in Knowledge Organization最新文献

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Human-In-The-Loop Topic Modelling: Assessing topic labelling and genre-topic relations with a movie plot summary corpus 人在环主题建模:评估主题标签和类型-主题关系与电影情节摘要语料库
P. Matthews
A much-used but not yet mainstream text analysis approach, topic modelling allows the identification of lexical themes for a document collection. Against principles for interpretable AI and sociotechnical design, there are definite strengths from its speed and ability to discover structure, but remain challenges in how results can be interpreted whether this be by analysts, domain experts, or potential end users. Automated coherence and labelling measures go some of the way toward bridging the understanding and trust gap, and user empowerment through visualisation and design intervention is starting to show how the remaining ground might be made up. This study uses topic modelling on a corpus of Wikipedia movie summaries to illustrate challenges and potential. Topic labelling for naive users was found to only be easy in a quarter of cases, and difficulty increased markedly with 100 topics compared to 50. While automated measures suggested 88 topics, the number manageable by users was closer to 50. The unsupervised topic model was compared to the movie genre labels and indicated that the two might work together well to complement genres, match content across genre and highlight within-genre variability. It is suggested that unsupervised models might work better for creativity and discovery than semi-supervised versions.
主题建模是一种广泛使用但尚未成为主流的文本分析方法,它允许识别文档集合的词汇主题。相对于可解释人工智能和社会技术设计的原则,它在速度和发现结构的能力上有明显的优势,但在如何解释结果方面仍然存在挑战,无论是由分析师、领域专家还是潜在的最终用户。自动化一致性和标签措施在一定程度上有助于弥合理解和信任差距,而通过可视化和设计干预的用户授权开始显示如何弥补剩余的基础。本研究在维基百科电影摘要语料库上使用主题建模来说明挑战和潜力。对于新手用户来说,主题标签只在四分之一的情况下是容易的,与50个主题相比,100个主题的难度明显增加。虽然自动测量显示有88个主题,但用户可管理的主题数量接近50个。将无监督主题模型与电影类型标签进行比较,表明两者可以很好地协同工作,以补充类型,匹配跨类型的内容,并突出类型内的可变性。有人认为,无监督模型可能比半监督模型更有利于创造力和发现。
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引用次数: 4
Fandom, Folksonomies and Creativity: the case of the Archive of Our Own Fandom, Folksonomies和Creativity:以我们自己的档案为例
Ludi Price
Over recent years Web 2.0 has brought information into the hands of the public, and we are increasingly seeing non-professionals doing sophisticated information tasks not merely for work, research or personal interest, but also for leisure – and even pleasure. This paper looks at an online fanfiction repository, Archive of Our Own (AO3), and investigates the ways that media fans have co-opted new technologies to build a ‘curated folksonomy’ (Bullard 2014), in order to organise the fanworks (fan-created creative works) uploaded by fans to the website. Run by volunteers, the site is a fascinating example of how passion, and even obsession, can bring amateur knowledge workers together collaboratively with users to build an intricate ‘democratic indexing’ system (Hidderley and Rafferty 1997; Rafferty and Hidderley 2007). Through methods of tag analysis and interviews, the paper explores how Archive of Our Own’s curated folksonomy allows fans to make full and creative use of their own original, freeform tags, while also building a highly granular and sophisticated taxonomy which, though highly labour-intensive to maintain, serves the community by maintaining a high degree of accuracy while also preserving the folksonomic properties of freeform tagging. As well as building a functioning taxonomy, through standardising its nomenclature, and facilitating the discoverability of AO3’s collections to its users, these amateur knowledge workers see their domain expertise and knowledge organisation labour as a type of fanwork that ‘gives back to the community’, in lieu of other creative works such as fanfiction and fanart.
近年来,Web 2.0将信息带到公众的手中,我们越来越多地看到非专业人士从事复杂的信息任务,不仅是为了工作、研究或个人兴趣,而且也是为了休闲——甚至是娱乐。本文着眼于在线同人小说存储库Archive of Our Own (AO3),并调查了媒体粉丝采用新技术建立“策划的大众分类法”(Bullard 2014)的方式,以便组织粉丝上传至网站的同人作品(粉丝创作的创意作品)。这个由志愿者运营的网站是一个很好的例子,它展示了激情,甚至是痴迷,如何将业余知识工作者与用户聚集在一起,共同建立一个复杂的“民主索引”系统(Hidderley and Rafferty 1997;Rafferty and Hidderley 2007)。通过标签分析和访谈的方法,本文探讨了Archive of Our Own的精心策划的民俗分类法是如何让粉丝们充分和创造性地使用他们自己的原创自由形式标签的,同时也建立了一个高度精细和复杂的分类法,尽管维护起来需要大量的劳动,但它通过保持高度的准确性来服务于社区,同时也保留了自由形式标签的民俗属性。这些业余知识工作者不仅通过标准化命名法建立了一个功能性的分类法,还促进了AO3的收藏对用户的可发现性,他们将自己的领域专业知识和知识组织劳动视为一种“回馈社区”的同人作品,而不是其他创造性的作品,如同人小说和同人艺术。
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引用次数: 4
The Role of Knowledge Organisation Systems in Business Intelligence: a literature review 知识组织系统在商业智能中的作用:文献综述
Tanja Svarre Jonasen, Marianne Lykke, A. Bygholm
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引用次数: 0
Developments in Ethics of Knowledge Organization: from critical approaches to classifications to controlled digital communication practices 知识组织伦理的发展:从关键方法到分类到受控的数字通信实践
Joana Casenave, Widad Mustafa El Hadi
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引用次数: 1
Paradigmatic Similarities in Knowledge Representation between AI and Ontological Systems 人工智能与本体系统知识表示的范式相似性
Jian Qin
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引用次数: 0
Digital Creativity Support: designing AI to augment human creativity 数字创意支持:设计人工智能来增强人类的创造力
N. Maiden
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引用次数: 2
Semantic Enrichment of Linked Personal Authority Data: a casestudy of elites in late Imperial China 关联个人权威数据的语义丰富:以晚清中国精英阶层为例
Shu-jiun Chen
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引用次数: 0
AI: Artificial Intelligence or Autistic Intelligence? Keeping knowledge organisation human AI:人工智能还是自闭症智能?保持知识组织人性化
Patrick Lambe
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引用次数: 0
Modeling Performing Arts Archives in South Korea Based on FRBRoo 基于FRBRoo的韩国表演艺术档案建模
Ziyoung Park
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引用次数: 1
Algorithmic Relevance: a case of knowledge representation, organization and discovery systems 算法关联:知识表示、组织和发现系统的一个案例
L. Hajibayova
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引用次数: 0
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The Human Position in an Artificial World: Creativity, Ethics and AI in Knowledge Organization
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