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利用文本挖掘和主题分析对辅助犬相关文献的综述。

An overview of the literature on assistance dogs using text mining and topic analysis.

作者信息

Bassan Emma, Mair Alberto, De Santis Marta, Bugianelli Massimo, Loretti Enrico, Capecci Alessio, Mutinelli Franco, Contalbrigo Laura

机构信息

National Reference Centre for Animal Assisted Interventions, Istituto Zooprofilattico Sperimentale delle Venezie, Legnaro, Italy.

National Guide Dog School for the Blind, Scandicci, Italy.

出版信息

Front Vet Sci. 2024 Dec 11;11:1463332. doi: 10.3389/fvets.2024.1463332. eCollection 2024.

DOI:10.3389/fvets.2024.1463332
PMID:39723180
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11669006/
Abstract

It is said that dogs are human's best friend. On occasion, dogs can be raised and trained to provide additional specific benefits to humans suffering from a range of physical or mental conditions, working as assistance dogs. In this article, we employed innovative techniques to review the vast and constantly expanding literature on the subject, which covers a multitude of aspects. The 450 articles obtained through keyword search on Scopus were initially described in terms of year of publication, geographical context and publication destination, and were subsequently analysed through automated text mining to detect the most important words contained within them. Lastly, a generative model of topic analysis (Latent Dirichlet Allocation-LDA) described the content of the collection of documents, dividing it into the appropriate number of topics. The results yielded interesting insights across all domains, demonstrating the potential of automated text mining and topic analysis as a useful tool to support the researchers in dealing with complex and time-consuming subjects' reviews, integrating the work done with traditional reviewing methods.

摘要

据说狗是人类最好的朋友。有时,狗可以被饲养和训练,为患有一系列身体或精神疾病的人提供额外的特殊益处,充当辅助犬。在本文中,我们采用创新技术回顾了关于该主题的大量且不断扩展的文献,这些文献涵盖了多个方面。通过在Scopus上进行关键词搜索获得的450篇文章,首先按照出版年份、地理背景和出版目的地进行了描述,随后通过自动文本挖掘进行分析,以检测其中包含的最重要的词汇。最后,一个主题分析生成模型(潜在狄利克雷分配-LDA)描述了文档集合的内容,将其划分为适当数量的主题。结果在所有领域都产生了有趣的见解,证明了自动文本挖掘和主题分析作为一种有用工具的潜力,可支持研究人员处理复杂且耗时的主题综述,将其与传统综述方法所做的工作相结合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a83/11669006/e547b390c4c2/fvets-11-1463332-g0010.jpg
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