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Toward topic diversity in recommender systems: integrating topic modeling with a hashing algorithm 面向推荐系统中的主题多样性:将主题建模与哈希算法相结合
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-30 DOI: 10.1108/ajim-01-2023-0019
Donghui Yang, Yan Wang, Zhaoyang Shi, Huimin Wang
PurposeImproving the diversity of recommendation information has become one of the latest research hotspots to solve information cocoons. Aiming to achieve both high accuracy and diversity of recommender system, a hybrid method has been proposed in this paper. This study aims to discuss the aforementioned method.Design/methodology/approachThis paper integrates latent Dirichlet allocation (LDA) model and locality-sensitive hashing (LSH) algorithm to design topic recommendation system. To measure the effectiveness of the method, this paper builds three-level categories of journal paper abstracts on the Web of Science platform as experimental data.Findings(1) The results illustrate that the diversity of recommended items has been significantly enhanced by leveraging hashing function to overcome information cocoons. (2) Integrating topic model and hashing algorithm, the diversity of recommender systems could be achieved without losing the accuracy of recommender systems in a certain degree of refined topic levels.Originality/valueThe hybrid recommendation algorithm developed in this paper can overcome the dilemma of high accuracy and low diversity. The method could ameliorate the recommendation in business and service industries to address the problems of information overload and information cocoons.
目的提高推荐信息的多样性已成为解决信息茧的最新研究热点之一。为了实现推荐系统的高精度和多样性,本文提出了一种混合方法。本研究旨在探讨上述方法。设计/方法论/方法本文将潜在狄利克雷分配(LDA)模型和局部敏感哈希(LSH)算法相结合来设计主题推荐系统。为了衡量该方法的有效性,本文在Web of Science平台上构建了三类期刊论文摘要作为实验数据。研究结果(1)结果表明,通过利用哈希函数克服信息茧,推荐项目的多样性得到了显著增强。(2) 将主题模型和哈希算法相结合,在一定程度的细化主题级别上,可以在不损失推荐系统准确性的情况下实现推荐系统的多样性。独创性/价值本文开发的混合推荐算法可以克服高精度和低多样性的困境。该方法可以改善商业和服务业的推荐,以解决信息过载和信息茧的问题。
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引用次数: 0
Sustaining the environment through e-waste recycling: an extended valence theory perspective 通过电子废物回收维持环境:一个扩展价理论的观点
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-25 DOI: 10.1108/ajim-10-2022-0475
Pradaini Nadarajan, Ali Vafaei-Zadeh, Haniruzila Hanifah, Ramayah Thurasamay
PurposeThe escalating volume of electronic waste (e-waste) presents a significant environmental and health hazard, emphasizing the importance of promoting e-waste recycling. Therefore, this study aims to utilize a valence theory approach to comprehensively understand the factors influencing individuals' intention to recycle e-waste.Design/methodology/approachA survey-based research approach was employed to examine the factors influencing consumers' e-waste recycling intention. Data were collected through an online survey questionnaire from Malaysian individuals aged 18 and above. The hypotheses were tested using a sample of 300 respondents, employing partial least squares structural equation modeling as a symmetric analysis technique. Additionally, fuzzy-set Qualitative Comparative Analysis (fsQCA), an asymmetric analysis approach, was used to gain deeper insights. Non-probability purposive sampling was utilized in the sampling process.FindingsThe PLS-SEM analysis revealed that subjective norms and willingness to change significantly impact e-waste recycling intention. Furthermore, perceived convenience, environmental concerns and social media usage were found to support the intention to recycle e-waste. The fsQCA results enhanced the interpretation by uncovering intricate relationships among the antecedents and identifying specific configurations that accurately predict consumers' recycling intentions.Practical implicationsThe practical implications of this study emphasize the need for policymakers and practitioners to raise awareness regarding the benefits of e-waste recycling, enhance convenience in the recycling process and strengthen personal and subjective norms to encourage individuals to recycle their e-waste.Originality/valueThis study's originality lies in its adoption of a valence theory framework to comprehend the intentions behind e-waste recycling, as well as its inclusion of control variables during the analysis. This unique approach enhances the understanding of factors influencing e-waste recycling intention and provides valuable insights for policymakers and practitioners in developing effective strategies to promote e-waste recycling behavior.
目的不断增加的电子垃圾对环境和健康造成了重大危害,强调了促进电子垃圾回收利用的重要性。因此,本研究旨在利用价态理论方法来全面了解影响个人电子垃圾回收意愿的因素。设计/方法/方法采用基于调查的研究方法来检验影响消费者电子垃圾回收意向的因素。数据是通过在线调查问卷从18岁及以上的马来西亚个人中收集的。这些假设是使用300名受访者的样本进行测试的,采用偏最小二乘结构方程建模作为对称分析技术。此外,模糊集定性比较分析(fsQCA)是一种不对称分析方法,用于获得更深入的见解。在抽样过程中采用了非概率目的抽样。PLS-SEM分析显示,主观规范和改变意愿显著影响电子垃圾回收意愿。此外,人们认为方便、环境问题和社交媒体使用支持回收电子垃圾的意图。fsQCA的结果通过揭示前因之间的复杂关系和确定准确预测消费者回收意图的特定配置来增强解释。实际意义本研究的实际意义强调政策制定者和从业者需要提高对电子废物回收效益的认识,提高回收过程的便利性,加强个人和主观规范,鼓励个人回收电子垃圾。独创性/价值这项研究的独创性在于它采用了价理论框架来理解电子垃圾回收背后的意图,并在分析过程中纳入了控制变量。这种独特的方法增强了对影响电子废物回收意图的因素的理解,并为政策制定者和从业者制定促进电子废物回收行为的有效战略提供了宝贵的见解。
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引用次数: 0
Knowledge-sharing attitude and behavior of civil servants: motivations behind rewards 公务员知识分享态度与行为:奖励背后的动机
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-23 DOI: 10.1108/ajim-01-2023-0016
Kristy Lam, E. Kong, Dickson K. W. Chiu, Kevin K. W. Ho
PurposeTo a large extent, knowledge in government workplaces resides within the hierarchy as it provides unique services to the public. Governments should preserve and pass on valuable and irreplaceable knowledge in providing their services through learning by sharing. Yet, sharing requires time and effort. This study examines the motivations of civil servants to share knowledge and their knowledge-sharing behaviors.Design/methodology/approachThe authors conducted an online survey to collect quantitative data from civil servants in the Hong Kong Government and obtained 104 useable responses to test the eight hypotheses comprising six constructs by structural equation modeling to explore the participants' knowledge-sharing behaviors.FindingsResults indicated that (1) expected contribution was the primary source of motivation behind knowledge sharing; (2) participants engaged more frequently in informal than formal knowledge-sharing activities; and (3) there was a dire need for knowledge sharing focusing on explicit knowledge of work procedures.Originality/valueThe research focuses on motivational factors for knowledge sharing. Despite abundant literature about knowledge sharing in public or governmental organizations, scant studies focus on the motivations behind why expected rewards and expected associations have less significant impacts on the attitude toward knowledge sharing than expected contribution.
在很大程度上,政府工作场所的知识存在于等级制度中,因为它为公众提供独特的服务。各国政府在提供服务时应通过分享学习的方式保存和传递宝贵和不可替代的知识。然而,分享需要时间和精力。本研究探讨公务员知识分享的动机及其知识分享行为。设计/方法/方法通过网上问卷调查,收集香港政府公务员的定量数据,获得104份可用回复,运用结构方程模型检验6个构式的8个假设,探讨参与者的知识共享行为。研究结果表明:(1)期望贡献是知识共享的主要动力来源;(2)参与者参与非正式知识共享活动的频率高于正式知识共享活动;(3)迫切需要以工作流程显性知识为核心的知识共享。原创性/价值本研究关注知识共享的激励因素。尽管有大量关于公共或政府组织知识共享的文献,但很少有研究关注预期奖励和预期关联对知识共享态度的影响低于预期贡献的影响背后的动机。
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引用次数: 0
Knowledge mapping of entrepreneurship research during COVID-19 and forecasting research directions for the post-pandemic era 新冠肺炎创业研究知识图谱与后大流行时代研究方向预测
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-22 DOI: 10.1108/ajim-11-2022-0504
Carson Duan
PurposeThe COVID-19 crisis has adversely affected entrepreneurs, innovators and their ventures and, arguably, entrepreneurship research. This study aims to map the knowledge of entrepreneurship research during the COVID-19 pandemic to provide evidence of literature evolution in the field with the purpose of supporting future decision-making for policymakers, academics and practitioners in the post-COVID-19 era.Design/methodology/approachThe study examines various bibliometric and scientometric indicators of entrepreneurship research in the Web of Science database using bibliometric techniques and visualization tools. Using the information gained, the scientometrics of entrepreneurship research during the COVID-19 time slice (2020–02-12 to 2022–10-15) are synthesized and comprehensively presented, and future research avenues for the post-COVID-19 era are suggested.FindingsThe results of rigorous quantitative analyses show that entrepreneurship research activities were not disrupted by COVID-19, although entrepreneurial activities themselves were impacted worldwide. In addition to providing key insights into the research field, including the most relevant keywords, keyword co-occurrences, publication sources, countries' contribution and collaboration, and source co-citations, the conceptual structural analysis separates the current trends (hotspots) into ten themes. Based on the evolution of author keywords and research themes, the study identified numerous future research directions, including 1) entrepreneurship in emerging countries, 2) firm performance in different categories of enterprises, 3) immigrants and transnational entrepreneurs, 4) technology in entrepreneurship education and 5) the impact of COVID-19 on the entrepreneurial ecosystem and entrepreneurship.Research limitations/implicationsBy building firm foundations for advancing the field in innovative and systematic ways, this timely study contributes to entrepreneurship literature and facilitates the understanding of the features and structures of entrepreneurship research towards the end of the pandemic. The research also has important implications for research management and entrepreneurship policymaking. The study's main limitation is that the results can only represent the time slice between 2020-02-12 and 2022-10-15.Practical implicationsPolicymakers and managers of research and development can utilize this research to prepare a crisis-related minimization handbook in advance.Originality/valueThis first data mapping and thematic analysis research for entrepreneurship during the period of COVID-19 provides the latest knowledge in the field at the beginning of the end of the pandemic. It empowers scholars by 1) providing a one-stop literature overview for this global crisis time slice, 2) identifying research focuses and gaps, 3) developing new research avenues for investigation and 4) contributing conceptual structure for specific entrepreneurship research projects.
目的新冠肺炎危机对企业家、创新者及其企业以及创业研究产生了不利影响。本研究旨在绘制新冠肺炎大流行期间创业研究的知识图谱,为该领域的文献演变提供证据,以支持后新冠肺炎时代的政策制定者、学者和从业者的未来决策。设计/方法论/方法本研究使用文献计量技术和可视化工具,在Web of Science数据库中检查了创业研究的各种文献计量和科学计量指标。利用获得的信息,综合和全面介绍了新冠肺炎时间段(2020年2月12日至2022年10月15日)创业研究的科学计量学,并提出了后新冠肺炎时代的未来研究途径。发现严格的定量分析结果表明,尽管创业活动本身在全球范围内受到了影响,但创业研究活动并未受到新冠肺炎的干扰。除了提供对研究领域的关键见解,包括最相关的关键词、关键词共同出现、出版物来源、各国的贡献和合作以及来源共同引用外,概念结构分析还将当前趋势(热点)分为十个主题。基于作者关键词和研究主题的演变,该研究确定了许多未来的研究方向,包括1)新兴国家的创业,2)不同类别企业的企业绩效,3)移民和跨国企业家,4)创业教育中的技术和5)新冠肺炎对创业生态系统和创业的影响。研究局限性/含义通过为以创新和系统的方式推进该领域奠定坚实的基础,这项及时的研究有助于创业文献,并有助于理解疫情结束时创业研究的特征和结构。该研究还对研究管理和创业决策具有重要意义。该研究的主要局限性在于,结果只能代表2020-02-12年至2022-10-15年之间的时间段。实际含义政策制定者和研发管理者可以利用这项研究提前编制危机相关最小化手册。原创/价值这是新冠肺炎期间创业的首次数据映射和主题分析研究,在疫情结束之初提供了该领域的最新知识。它通过1)为这一全球危机时间段提供一站式的文献综述,2)确定研究重点和差距,3)开发新的研究途径进行调查,4)为特定的创业研究项目提供概念结构,使学者们能够发挥作用。
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引用次数: 0
From internal to external information search: the role of information accessibility, information diagnosticity, and involvement 从内部到外部信息搜索:信息可访问性、信息诊断性和参与的作用
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-08-10 DOI: 10.1108/ajim-07-2022-0330
S. Tajdini, Edward Ramírez, Z. Xu
PurposeConsumers are assumed to engage in external information search only after exhausting their internal information sources. Guided by the accessibility/diagnosticity and ease-of-retrieval frameworks, and the elaboration likelihood model, the current study investigates this phenomenon.Design/methodology/approachTo test the relationships between internal information accessibility/diagnosticity and the importance of external search, and the moderating role of involvement in these relationships, 308 responses were collected on Amazon MTurk. Then, structural equation modeling was employed to analyze the data.FindingsThe analyses showed that while accessibility and diagnosticity of internal information have an impact on external information search, involvement with the product class has a consequential moderating effect on these relationships. In particular, in the low-involvement group, only the diagnosticity of internal information had a negative effect on external information search. On the contrary, in the high-involvement group, only accessibility of internal information had a negative effect.Research limitations/implicationsThese findings highlight the possibility of drawing erroneous conclusions resulting from not incorporating involvement, in conjunction with information accessibility and diagnosticity, in the study of the consumer external information search behavior.Practical implicationsThe findings also imply that if practitioners aim to prime consumers to engage in external information search, they need to take into account that the effects of internal information's accessibility and diagnosticity on consumers' external search behavior may be different depending on their levels of involvement.Originality/valueThis study's results showed that without considering the moderating effect of involvement, spurious conclusions may be made about the relationships between accessibility and diagnosticity of internal and external information importance. This finding may explain the discrepancy between the accessibility/diagnosticity and ease-of-retrieval frameworks, thus enriching the literature.
目的假设消费者只有在耗尽其内部信息来源后才参与外部信息搜索。在可访问性/诊断性和易检索性框架以及精化可能性模型的指导下,本研究对这一现象进行了调查。设计/方法/方法为了测试内部信息可访问性/诊断性与外部搜索的重要性之间的关系,以及参与在这些关系中的调节作用,在Amazon MTurk上收集了308份回复。然后,采用结构方程模型对数据进行分析。结果分析表明,虽然内部信息的可访问性和诊断性对外部信息搜索有影响,但对产品类别的参与对这些关系有相应的调节作用。特别是,在低参与度组中,只有内部信息的诊断性对外部信息搜索有负面影响。相反,在高参与度群体中,只有获得内部信息才会产生负面影响。研究局限性/含义这些发现强调了在消费者外部信息搜索行为的研究中,如果不将参与与信息可访问性和诊断性结合起来,可能会得出错误结论。实际含义研究结果还表明,如果从业者的目标是引导消费者参与外部信息搜索,他们需要考虑到内部信息的可访问性和诊断性对消费者外部搜索行为的影响可能因其参与程度而异。原创性/价值这项研究的结果表明,在不考虑参与的调节作用的情况下,可能会对内部和外部信息重要性的可及性和诊断性之间的关系得出虚假的结论。这一发现可能解释了可访问性/诊断性和易检索性框架之间的差异,从而丰富了文献。
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引用次数: 1
Exploring the experiences of researchers in the interdisciplinary humanities research teams on knowledge creation: a qualitative study 人文学科跨学科研究团队研究人员知识创造经验的质性研究
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-07-28 DOI: 10.1108/ajim-06-2022-0287
Zahra Karparvar, M. Mirzabeigi, G. Salimi
PurposeThe process of knowledge creation is recognized as an essential process for organizational learning and innovation. Creating knowledge to solve the problems and complexities of today's world is like opening a black box. Hence, the higher education system and universities are exploring ways to overcome the complexities and cope with global changes. In this regard, interdisciplinary collaborations and activities are crucial in creating knowledge and innovation to counter these changes. This study aimed to know the experiences of Shiraz university interdisciplinary researchers in the field of humanities and also design and explain the conceptual model of knowledge creation in interdisciplinary research teams in the field of humanities.Design/methodology/approachIn this qualitative research, grounded theory was implemented based on Strauss and Corbin's systematic approach. The sampling method was purposeful, and the participants included sixteen faculty members of shiraz university who had at least one experience of performing an interdisciplinary activity in one of the humanities fields. The first participant was selected as a pilot, and the rest were selected by snowball sampling. Semi-structured interviews were also used to collect data and continued until theoretical saturation was attained. After collecting the available information and interviewing the people, the data were organized and analyzed in three stages, open coding, axial coding, and selective coding, using the proposed framework of Strauss and Corbin. Finally, the researcher reached a final and meaningful categorization.FindingsIn this research, the results were presented as a paradigm model of knowledge creation in the interdisciplinary research teams in the field of humanities. The paradigm model of the study consists of causal factors (internal and external factors), main categories (specialized competencies, scientific discourse, understanding of knowledge domains), strategies (structuring and synchronizing), context (individual and organizational), interfering factors (leadership, industry, and society), and consequences (individual and group achievement).Originality/valueThe present study aimed to explore the experiences of researchers in the interdisciplinary humanities research teams on knowledge creation in qualitative research. The study used Strauss and Corbin's systematic approach to recognize the causal factors of knowledge creation and the contexts. Discovering the main category of knowledge creation in interdisciplinary research teams, the authors analyze the strategies and consequences of knowledge creation.
目的知识创造过程被认为是组织学习和创新的重要过程。创造知识来解决当今世界的问题和复杂性就像打开一个黑盒子。因此,高等教育系统和大学正在探索克服复杂性和应对全球变化的方法。在这方面,跨学科合作和活动对于创造知识和创新以应对这些变化至关重要。本研究旨在了解设拉子大学人文学科跨学科研究人员的经验,并设计和解释人文学科跨学科研究团队知识创造的概念模型。在本定性研究中,基于Strauss和Corbin的系统化方法实施扎根理论。抽样方法是有目的的,参与者包括设拉子大学的16名教师,他们至少有一次在人文学科领域进行跨学科活动的经历。第一个参与者被选为试点,其余的通过滚雪球抽样选择。半结构化访谈也用于收集数据,并继续进行,直到达到理论饱和。在收集现有资料和访谈的基础上,采用Strauss和Corbin提出的框架,将数据分为开放编码、轴向编码和选择性编码三个阶段进行整理和分析。最后,研究者得出了一个最终且有意义的分类。研究结果为人文学科跨学科研究团队的知识创造提供了一种范式模型。本研究的范式模型由因果因素(内部因素和外部因素)、主要类别(专业能力、科学话语、对知识领域的理解)、策略(结构化和同步化)、背景(个人和组织)、干扰因素(领导力、行业和社会)和后果(个人和群体成就)组成。本研究旨在探讨跨学科人文学科研究团队的研究人员在质性研究中的知识创造经验。本研究采用Strauss和Corbin的系统方法来识别知识创造的因果因素和背景。发现了跨学科研究团队知识创造的主要范畴,分析了跨学科研究团队知识创造的策略和后果。
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引用次数: 0
Investigating physician churn in online health communities from a social influence perspective 从社会影响的角度调查在线健康社区的医生流失
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-07-14 DOI: 10.1108/ajim-01-2023-0003
Qin Chen, Jiahua Jin, Tingting Zhang, Xiangbin Yan
PurposeThe success of online health communities (OHCs) depends on maintaining long-term relationships with physicians and preventing churn. Even so, the reasons for physician churn are poorly understood. In this study, an empirical model was proposed from a social influence perspective to explore the effects of online social influence and offline social influence on physician churn, as well as the moderating effect of their online returns.Design/methodology/approachThe empirical data of 4,145 physicians from a Chinese OHC, and probit regression models were employed to verify the proposed theoretical model.FindingsThe results suggest that physicians' churn intention is influenced by online and offline social influences, and the offline social influence is more powerful. Physicians' reputational and economic returns could weaken the effect of online social influence on churn intention. However, physicians' economic returns could strengthen the effect of offline social influence on churn intention.Originality/valueThis research study is the first attempt to explore physician churn and divides the social influence into online and offline social influences according to the source of social relationship. The findings contribute to the literature on e-Health, user churn and social influence and provide management implications for OHC managers.
目的在线健康社区(OHCs)的成功取决于与医生保持长期关系和防止流失。即便如此,医生流失的原因还是鲜为人知。在本研究中,从社会影响的角度提出了一个实证模型,以探讨在线社会影响和离线社会影响对医生流失的影响,以及他们在线回报的调节作用。设计/方法/方法采用来自中国OHC的4145名医生的经验数据和probit回归模型来验证所提出的理论模型。研究结果表明,医生的流失意愿受线上和线下社会影响,线下社会影响力更大。医生的声誉和经济回报可能会削弱网络社会影响对流失意愿的影响。然而,医生的经济回报可能会加强线下社会影响对流失意愿的影响。原创性/价值本研究首次尝试探索医生流失,并根据社会关系的来源将社会影响分为线上和线下社会影响。这些发现为有关电子健康、用户流失和社会影响的文献做出了贡献,并为OHC管理人员提供了管理启示。
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引用次数: 0
Machine learning and deep learning-based advanced classification techniques for the detection of major depressive disorder 基于机器学习和深度学习的重度抑郁症检测高级分类技术
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-07-11 DOI: 10.1108/ajim-10-2022-0468
Abhinandan Chatterjee, P. Bala, Shruti Gedam, Sanchita Paul, N. Goyal
PurposeDepression is a mental health problem characterized by a persistent sense of sadness and loss of interest. EEG signals are regarded as the most appropriate instruments for diagnosing depression because they reflect the operating status of the human brain. The purpose of this study is the early detection of depression among people using EEG signals.Design/methodology/approach(i) Artifacts are removed by filtering and linear and non-linear features are extracted; (ii) feature scaling is done using a standard scalar while principal component analysis (PCA) is used for feature reduction; (iii) the linear, non-linear and combination of both (only for those whose accuracy is highest) are taken for further analysis where some ML and DL classifiers are applied for the classification of depression; and (iv) in this study, total 15 distinct ML and DL methods, including KNN, SVM, bagging SVM, RF, GB, Extreme Gradient Boosting, MNB, Adaboost, Bagging RF, BootAgg, Gaussian NB, RNN, 1DCNN, RBFNN and LSTM, that have been effectively utilized as classifiers to handle a variety of real-world issues.Findings1. Among all, alpha, alpha asymmetry, gamma and gamma asymmetry give the best results in linear features, while RWE, DFA, CD and AE give the best results in non-linear feature. 2. In the linear features, gamma and alpha asymmetry have given 99.98% accuracy for Bagging RF, while gamma asymmetry has given 99.98% accuracy for BootAgg. 3. For non-linear features, it has been shown 99.84% of accuracy for RWE and DFA in RF, 99.97% accuracy for DFA in XGBoost and 99.94% accuracy for RWE in BootAgg. 4. By using DL, in linear features, gamma asymmetry has given more than 96% accuracy in RNN and 91% accuracy in LSTM and for non-linear features, 89% accuracy has been achieved for CD and AE in LSTM. 5. By combining linear and non-linear features, the highest accuracy was achieved in Bagging RF (98.50%) gamma asymmetry + RWE. In DL, Alpha + RWE, Gamma asymmetry + CD and gamma asymmetry + RWE have achieved 98% accuracy in LSTM.Originality/valueA novel dataset was collected from the Central Institute of Psychiatry (CIP), Ranchi which was recorded using a 128-channels whereas major previous studies used fewer channels; the details of the study participants are summarized and a model is developed for statistical analysis using N-way ANOVA; artifacts are removed by high and low pass filtering of epoch data followed by re-referencing and independent component analysis for noise removal; linear features, namely, band power and interhemispheric asymmetry and non-linear features, namely, relative wavelet energy, wavelet entropy, Approximate entropy, sample entropy, detrended fluctuation analysis and correlation dimension are extracted; this model utilizes Epoch (213,072) for 5 s EEG data, which allows the model to train for longer, thereby increasing the efficiency of classifiers. Features scaling is done using a standard scalar rather than normalization because it helps incr
抑郁症是一种心理健康问题,其特征是持续感到悲伤和失去兴趣。脑电图信号反映了人脑的工作状态,被认为是诊断抑郁症最合适的工具。本研究的目的是利用脑电图信号早期检测抑郁症。设计/方法/方法(1)通过滤波去除伪影,提取线性和非线性特征;(ii)使用标准标量进行特征缩放,而主成分分析(PCA)用于特征约简;(iii)采用线性、非线性和两者的组合(仅适用于准确率最高的分类器)进行进一步分析,其中一些ML和DL分类器应用于抑郁症分类;(iv)在本研究中,共有15种不同的ML和DL方法,包括KNN、SVM、bagging SVM、RF、GB、Extreme Gradient Boosting、MNB、Adaboost、bagging RF、BootAgg、Gaussian NB、RNN、1DCNN、RBFNN和LSTM,这些方法已被有效地用作分类器来处理各种现实问题。其中,alpha、alpha不对称、gamma和gamma不对称在线性特征上效果最好,而RWE、DFA、CD和AE在非线性特征上效果最好。2. 在线性特征中,gamma和alpha不对称为Bagging RF提供了99.98%的准确率,而gamma不对称为BootAgg提供了99.98%的准确率。3.对于非线性特征,RF中的RWE和DFA准确率为99.84%,XGBoost中的DFA准确率为99.97%,BootAgg中的RWE准确率为99.94%。4. 通过使用深度学习,在线性特征中,伽马不对称在RNN中准确率超过96%,在LSTM中准确率超过91%,对于非线性特征,在LSTM中CD和AE的准确率达到89%。5. 通过结合线性和非线性特征,Bagging RF (98.50%) γ不对称+ RWE达到了最高的精度。在DL中,Alpha + RWE、Gamma不对称+ CD和Gamma不对称+ RWE在LSTM中的准确率达到98%。原创性/价值从兰契中央精神病学研究所(CIP)收集了一个新的数据集,该数据集使用128个通道进行记录,而以前的主要研究使用较少的通道;总结了研究参与者的详细信息,并使用N-way方差分析开发了一个模型进行统计分析;通过对历元数据进行高通和低通滤波,然后进行重新引用和独立分量分析以去除噪声,从而去除伪影;提取线性特征,即频带功率和半球间不对称性;提取非线性特征,即相对小波能量、小波熵、近似熵、样本熵、去趋势波动分析和相关维数;该模型利用Epoch(213072)对5秒的EEG数据进行训练,使得模型训练时间更长,从而提高了分类器的效率。特征缩放使用标准标量而不是归一化,因为它有助于提高模型的准确性(特别是对于深度学习算法),而PCA用于特征约简;将这两种特征的线性、非线性和组合与ML和DL分类器一起进行广泛的分析,用于抑郁症的分类。线性和非线性特征的结合(仅适用于精度最高的特征)用于获得最佳检测结果。
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引用次数: 0
Investigating determinants of middle-aged and elderly users' video-creating intention on short-video platforms from a lifespan development perspective 从寿命发展角度研究中老年用户短视频平台视频创作意愿的决定因素
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-06-29 DOI: 10.1108/ajim-10-2022-0460
Chang Wang, Jin Yan, Yimeng Zhang, Lijing Huang
PurposeMiddle-aged and elderly users become an important group on short-video platforms, however, the research on determinants of their video-creating intention is limited. Based on lifespan development theories, this study examines the impact of aging experiences on their video-creating intention, considering internal generative motivations as mediators and age as a moderator.Design/methodology/approachTo test this study’s hypotheses, survey data from 321 Chinese middle-aged and elderly short-video users were collected and partial least square-structural equation modelling (PLS-SEM) approach was used to analyze these data.FindingsMiddle-aged and elderly users' aging experiences of social loss and personal growth are positively related to their video-creating intention. Aging experiences (i.e. physical loss, social loss, and personal growth) are positively related to internal generative motivations (i.e. need to be needed and symbolic immortality), and need to be needed is positively related to video-creating intention. Via the mediation of need to be needed, physical loss and personal growth are indirectly positively related to video-creating intention. Personal growth strengthens the relationship between physical loss and symbolic immortality, but weakens the associations of social loss with need to be needed and symbolic immortality. Age weakens the relationship between symbolic immortality and video-creating intention.Originality/valueThis study is the first wave to introduce and integrate lifespan theories such as selective optimization with compensation model, socioemotional selectivity theory, and generativity theory to explore the impacts of aging experiences on middle-aged and elderly users' video-creating intention by considering generativity motivations as mediators and age as a moderator.
目的中老年用户成为短视频平台上的一个重要群体,但对其视频创作意愿的决定因素研究有限。基于寿命发展理论,本研究考察了衰老经历对他们视频创作意图的影响,将内部生成动机视为中介,将年龄视为调节因素。设计/方法/方法为了检验本研究的假设,收集了321名中国中老年短视频用户的调查数据,并使用偏最小二乘结构方程建模(PLS-SEM)方法对这些数据进行了分析。发现中老年用户的社会失落和个人成长的老龄化体验与其视频创作意愿呈正相关。衰老经历(即身体损失、社会损失和个人成长)与内部生成动机(即需要和象征永生)呈正相关,需要与视频创作意图呈正相关。通过被需要的中介,身体损失和个人成长与视频创作意图间接呈正相关。个人成长强化了身体损失与象征性永生之间的关系,但削弱了社会损失与需要和象征性永生的联系。年龄弱化了象征不朽与视频创作意图之间的关系。原创性/价值本研究首次引入并整合了选择性优化与补偿模型、社会情感选择性理论和生成性理论等寿命理论,通过将生成性动机作为中介,年龄作为调节因素,探讨老龄化体验对中老年用户视频创作意愿的影响。
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引用次数: 0
Guest editorial: Extraction and evaluation of knowledge entities in the age of artificial intelligence 嘉宾评论:人工智能时代知识实体的提取与评价
IF 2.6 3区 管理学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2023-06-19 DOI: 10.1108/ajim-05-2023-507
Chengzhi Zhang, Philipp Mayr, Wei Lu, Yi Zhang
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引用次数: 2
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Aslib Journal of Information Management
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