技术创新风险管理的分类与识别   总被引：25，自引：1，他引：25  

周寄中  薛刚 《科学学研究》2002,20(2):221-224

技术创新的不确定性决定了技术创新高风险的特征 ,企业对技术创新的风险进行科学系统的管理对创新成功具有重要意义。而技术创新风险管理的首要任务便是风险识别 ,本文将可能的技术创新风险归为决策风险、技术风险、市场风险、组织风险、资金风险、信息管理风险、企业文化风险、外部环境风险共八类 ,可以帮助企业有效地进行风险的识别 ,从而采取对策 ,尽可能降低可能的损失、增加可能的收益  相似文献   

文本知识的自动分类方法初探     

范宇中  张玉峰 《情报科学》2003,21(1):103-105

本文结合运用信息管理和人工智能的原理与技术，探讨了文本知识的自动分类方法，包括：自动归类与聚类方法、基于实例的学习分类方法和基于特征值的元学习方法。  相似文献   

关系网络与创业机会识别:创业学习的多重中介效应          下载免费PDF全文

陈文沛 《科学学研究》2016,34(9):1391-1396

基于178家企业的样本数据,研究关系网络影响创业机会识别的内在机制。结构方程建模分析结果表明:关系网络不仅可以直接预测创业机会识别,还可以通过认知和经验学习以及实践学习间接预测创业机会识别。此外认知和经验学习对创业机会识别的预测作用相同,认知学习相比于经验学习对实践学习的预测作用则更强。  相似文献   

Predicting smartphone brand loyalty: Consumer value and consumer-brand identification perspectives     

《International Journal of Information Management》2016,36(3):245-257

With the growth and competition of the smartphone industry, developing a better understanding of what drives consumers' loyalty to smartphone brands has become an important issue for academics and practitioners. This study hypothesizes four determinants of smartphone brand loyalty based on the perspectives of consumer value and consumer-brand identification. Furthermore, this study also explores the moderating effects of age and gender differences on the determination process of smartphone brand loyalty. Data collected from 157 respondents was tested against the research model using a partial least squares (PLS) approach. The results indicate that functional value, emotional value, social value, and brand identification have a positive influence on smartphone brand loyalty. Of the two moderators, results show that age enhances the emotional value-brand loyalty and social value-brand loyalty linkages but weakens the brand identification-brand loyalty relationship. However, gender does not play a moderating role in the determination of smartphone brand loyalty. The results of this study provide several important theoretical and practical implications for smartphone brand management.  相似文献   

颠覆性技术识别方法述评   总被引：1，自引：0，他引：1  

张欣 《图书情报工作》2020,64(17):145-152

[目的/意义] 通过对国内外颠覆性技术概念和颠覆性技术识别方法进行文献梳理,分析存在的问题,提出未来颠覆性技术识别可能的研究视角。[方法/过程] 利用文献调研法归纳总结了6种颠覆性技术识别方法,分析各种识别方法目前存在的优势和不足。[结果/结论] 颠覆性技术识别方法还存在一些弊端,如颠覆性技术分类不明确、特征定量化研究缺乏、现有识别方法中缺乏考虑技术知识之间的关联性,未来研究应该进一步加强颠覆性技术特征研究,并考虑知识之间的关联特征,并且加强从功效性特征数值突破和技术融合视角来识别颠覆性技术,同时,深入挖掘更细粒度的技术主题。  相似文献   

气象档案分级鉴定关键技术与策略分析     

兰平 《兰台世界》2020,(2):81-84

档案分级鉴定是依据科学的原则和标准甄别具有永久保存价值档案之间的价值差异,从而对不同价值的档案施以更为科学的管理、保护和利用[1]。文章是在对档案分级鉴定理论进行充分研究和实践的基础上,提出了气象档案分级鉴定工作的技术关键,总结了气象档案分级鉴定方法,针对馆藏永久档案的分级鉴定策略与难点,提出了解决方法,以便充实和完善气象档案管理工作内容,最大化实现永久气象档案的社会效益,为在全国气象档案领域开展分级鉴定工作提供一种可行的技术思路和有效的技术参考。  相似文献   

高校图书馆读者需求识别方法探析     

叶冬梅  牛卫东 《兰台世界》2020,(2):112-114

从读者角度对国内部分高校图书馆开展的调查进行分析,针对收集高校读者需求信息的三种主要方法,即基于图书馆和数字平台的读者数据挖掘需求信息,使用问卷调查收集读者需求信息,以及采用校内访谈形式捕获读者需求信息,分析三种方法的应用以及优势和局限性,旨在为高校图书馆识别读者需求提供参考。  相似文献   

Application of machine learning techniques to assess the trends and alignment of the funded research output     

《Journal of Informetrics》2020,14(2):101018

Research and development activities are regarded as one of the most influencing factors of the future of a country. Large investments in research can yield a tremendous outcome in terms of a country’s overall wealth and strength. However, public financial resources of countries are often limited which calls for a wise and targeted investment. Scientific publications are considered as one of the main outputs of research investment. Although the general trend of scientific publications is increasing, a detailed analysis is required to monitor the research trends and assess whether they are in line with the top research priorities of the country. Such focused monitoring can shed light on scientific activities evolution as well as the formation of new research areas, thus helping governments to adjust priorities, if required. But monitoring the output of the funded research manually is not only very expensive and difficult, it is also subjective. Using structural topic models, in this paper we evaluated the trends in academic research performed by federally funded Canadian researchers during the time-frame of 2000–2018, covering more than 140,000 research publications. The proposed approach makes it possible to objectively and systematically monitor research projects, or any other set of documents related to research activities such as funding proposals, at large-scale. Our results confirm the accordance between the performed federally funded research projects and the top research priorities of Canada.  相似文献   

A new unsupervised method for document clustering by using WordNet lexical and conceptual relations     

Diego Reforgiato Recupero 《Information Retrieval》2007,10(6):563-579

Text document clustering provides an effective and intuitive navigation mechanism to organize a large amount of retrieval results by grouping documents in a small number of meaningful classes. Many well-known methods of text clustering make use of a long list of words as vector space which is often unsatisfactory for a couple of reasons: first, it keeps the dimensionality of the data very high, and second, it ignores important relationships between terms like synonyms or antonyms. Our unsupervised method solves both problems by using ANNIE and WordNet lexical categories and WordNet ontology in order to create a well structured document vector space whose low dimensionality allows common clustering algorithms to perform well. For the clustering step we have chosen the bisecting k-means and the Multipole tree, a modified version of the Antipole tree data structure for, respectively, their accuracy and speed.

Diego Reforgiato RecuperoEmail:

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Extending WHIRL with background knowledge for improved text classification     

Sarah Zelikovitz  William W. Cohen  Haym Hirsh 《Information Retrieval》2007,10(1):35-67

Intelligent use of the many diverse forms of data available on the Internet requires new tools for managing and manipulating heterogeneous forms of information. This paper uses WHIRL, an extension of relational databases that can manipulate textual data using statistical similarity measures developed by the information retrieval community. We show that although WHIRL is designed for more general similarity-based reasoning tasks, it is competitive with mature systems designed explicitly for inductive classification. In particular, WHIRL is well suited for combining different sources of knowledge in the classification process. We show on a diverse set of tasks that the use of appropriate sets of unlabeled background knowledge often decreases error rates, particularly if the number of examples or the size of the strings in the training set is small. This is especially useful when labeling text is a labor-intensive job and when there is a large amount of information available about a particular problem on the World Wide Web.

Haym HirshEmail:

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