Relevant bibliographies by topics / Knowledge generation

Academic literature on the topic 'Knowledge generation'

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Published: 4 June 2021
Last updated: 19 February 2023

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Journal articles on the topic "Knowledge generation"

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Popov, Evgeny, Maxim Vlasov, and Hanusch Horst. "Resource Potential of Knowledge Generation." MONTENEGRIN JOURNAL OF ECONOMICS 12, no. 3 (October 20, 2016): 101–14. http://dx.doi.org/10.14254/1800-5845.2016/12-3/7.

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van der Walt, Mariana. "Knowledge management and scientific knowledge generation." Knowledge Management Research & Practice 4, no. 4 (November 2006): 319–30. http://dx.doi.org/10.1057/palgrave.kmrp.8500115.

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Wang, Jian, Junhao Liu, Wei Bi, Xiaojiang Liu, Kejing He, Ruifeng Xu, and Min Yang. "Improving Knowledge-Aware Dialogue Generation via Knowledge Base Question Answering." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 05 (April 3, 2020): 9169–76. http://dx.doi.org/10.1609/aaai.v34i05.6453.

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Neural network models usually suffer from the challenge of incorporating commonsense knowledge into the open-domain dialogue systems. In this paper, we propose a novel knowledge-aware dialogue generation model (called TransDG), which transfers question representation and knowledge matching abilities from knowledge base question answering (KBQA) task to facilitate the utterance understanding and factual knowledge selection for dialogue generation. In addition, we propose a response guiding attention and a multi-step decoding strategy to steer our model to focus on relevant features for response generation. Experiments on two benchmark datasets demonstrate that our model has robust superiority over compared methods in generating informative and fluent dialogues. Our code is available at https://github.com/siat-nlp/TransDG.
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Panikarova, S. V., and M. V. Vlasov. "Knowledge Generation Risk Management." Economic Analysis: Theory and Practice 16, no. 9 (September 28, 2017): 1696–707. http://dx.doi.org/10.24891/ea.16.9.1696.

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Davies, John, Alistair Duke, Nick Kings, Dunja Mladenić, Kalina Bontcheva, Miha Grčar, Richard Benjamins, Jesus Contreras, Mercedes Blazquez Civico, and Tim Glover. "Next generation knowledge access." Journal of Knowledge Management 9, no. 5 (October 2005): 64–84. http://dx.doi.org/10.1108/13673270510622465.

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Dettmar, Harvey, Xiaohui Liu, Roger Johnson, and Alan Payne. "Knowledge-based data generation." Knowledge-Based Systems 11, no. 3-4 (November 1998): 167–77. http://dx.doi.org/10.1016/s0950-7051(98)00031-8.

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Schofield, M. J. "Knowledge-based test generation." IEE Proceedings G (Electronic Circuits and Systems) 132, no. 3 (1985): 108. http://dx.doi.org/10.1049/ip-g-1.1985.0023.

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Davies, J., R. Studer, Y. Sure, and P. W. Warren. "Next generation knowledge management." BT Technology Journal 23, no. 3 (July 2005): 175–90. http://dx.doi.org/10.1007/s10550-005-0040-3.

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van Deventer, Marko. "African Generation Y students’ personal finance behavior and knowledge." Investment Management and Financial Innovations 17, no. 4 (November 26, 2020): 136–44. http://dx.doi.org/10.21511/imfi.17(4).2020.13.

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Personal financial management is important, given uncertainties in both financial and economic environment. However, published research on African Generation Y students’ personal finance behavior and knowledge is limited. This study aimed to evaluate African Generation Y students’ personal finance behavior in terms of their attitudes towards financial planning and whether this cohort believes that they have the skills to manage their finances successfully. In addition, this study sought to evaluate African Generation Y students’ knowledge regarding personal finance. A convenience sample of 500 African students across the campuses of two South African public higher education institutions situated in the Gauteng province was surveyed using structured, self-administered questionnaires. The t-test results indicate that the sample deems the process of planning personal finances and managing credit, insurance, investment, and estate, as important. Moreover, the students scored low in the broad personal finance knowledge areas of basic finance, saving, spending, and debt, suggesting that this cohort is financially illiterate. The results also indicated that the students think they have the financial skillset to manage their personal finances. A high Pearson’s correlation coefficient was noted between sampled participants’ personal finance behavior and their observed personal finance management skillset regarding the relationship between the constructs. However, an insignificant relationship was found between attitudes towards personal finance and financial knowledge and between financial knowledge and African Generation Y students’ apparent finance skills. Understanding African Generation Y students’ personal finance behavior and knowledge, universities and financial institutions can more effectively identify gaps and deficiencies in students’ personal finance endeavors.
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B, Yeslando J. Gonzalez. "Investigate from the knowledge of the peoples." Sociology International Journal 2, no. 6 (December 27, 2018): 726–28. http://dx.doi.org/10.15406/sij.2018.02.00128.

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The following paper addresses from a critical point of view the way on how Venezuelan universities approach popular knowledge and how it would be transmitted to future generations. For the author institutions cannot become mere instruments generating ideologies or become Universities for the Generation of Communes and less in particularities ... "believe that you can replace a research university by a university in the commune ... "1 As our current policy in Venezuela intends, it is to try to apply policies that pretend to relegate us to the past.
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Dissertations / Theses on the topic "Knowledge generation"

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Mohamud, Mohamed Omar. "The generation of knowledge in knowledge-based firms." Thesis, University of Leeds, 2007. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.439583.

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Taneja, Abhinav 1975. "Knowledge organization and content generation in knowledgemediaries." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/8875.

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Thesis (S.M.)--Massachusetts Institute of Technology, Technology and Policy Program; and, (S.B.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.
Includes bibliographical references (leaves 115-116).
by Abhinav Taneja.
S.B.
S.M.
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Cline, Ben E. "Knowledge intensive natural language generation with revision." Diss., This resource online, 1994. http://scholar.lib.vt.edu/theses/available/etd-09092008-063657/.

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Sandrasegaran, Kumbesan. "A methodology for generation of fault diagnostic knowledge." Thesis, McGill University, 1994. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=28908.

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This dissertation presents a methodology for generation of fault diagnostic knowledge from a description of a device. The generated knowledge is to be used in a computer based learning environment for fault diagnostic tasks. In the past, developers of such environments obtained diagnostic knowledge through a knowledge engineering exercise with human experts. There are a number of drawbacks associated with such an approach. A major bottleneck in the development of such learning environments was capturing human expertise for diagnosis of an application, encoding this knowledge in a suitable form in a computer, and then verifying this knowledge. This exercise also depends on the availability and cooperation of a knowledgeable human expert(s). If more than one expert participates in the knowledge acquisition process, one may obtain contradictory information. Furthermore, most of the diagnostic knowledge is highly application specific thus making it useless for other applications. The starting point of the methodology of this thesis is a description of a device in terms of the components, component behaviors, and interconnections between components (structural knowledge). The end point of the methodology is a set of rules that can be used to diagnose faults in the device. The intermediate points are a behavioral and causal descriptions of the device, and a set of domain independent diagnostic strategies. This methodology has been applied to a counter circuit in the domain of digital electronics to test both the ability of the fault diagnostic system to diagnose faults in a device as well as to test its efficiency. The rules generated were able to successfully detect all the faults that were inserted in the counter application. Furthermore, as more diagnostic strategies were included in the diagnostic rule generation, the efficiency of the diagnostic system improved considerably.
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Cain, Mark. "Second generation knowledge based systems in habitat evaluation." Thesis, De Montfort University, 1993. http://hdl.handle.net/2086/10711.

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Many expert, or knowledge-based, systems have been constructed in the domain of ecology, several of which are concerned with habitat evaluation. However, these systems have been geared to solving particular problems, with little regard paid to the underlying relationships that exist within a biological system. The implementation of problem-solving methods with little regard to understanding the more primary knowledge of a problem area is referred to in the literature as 'shallow', whilst the representation and utilisation of knowledge of a more fundamental kind is termed 'deep'. This thesis contains the details of a body of research exploring issues that arise from the refinement of traditional expert systems methodologies and theory via the incorporation of depth, along with enhancements in the sophistication of the methods of reasoning (and subsequent effects on the mechanisms of communication between human and computer), and the handling of uncertainty. The approach used to address this research incorporates two distinct aspects. Firstly, the literature of 'depth', expert systems in ecology, uncertainty, and control of reasoning and related user interface issues are critically reviewed, and where inadequacies exist, proposals for improvements are made. Secondly, practical work has taken place involving the construction of two knowledge based systems, one 'traditional', and the other a second generation system. Both systems are primarily geared to the problem of evaluating a pond site with respect to its suitability for the great crested newt (Triturus cristatus). This research indicates that it is possible to build a second-generation knowledge-based system in the domain of ecology, and that construction of the second generation system required a magnitude of effort similar to the firstgeneration system. In addition, it shows that, despite using different architectures and reasoning strategies, such systems may be judged as equally acceptable by endusers, and of similar accuracy in their conclusions. The research also offers guidance concerning the organisation and utilisation of deep knowledge within an expert systems framework, in both ecology and in other domains that have a similar concept-rich nature.
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Cintra, Marcos Evandro. "Genetic generation of fuzzy knowledge bases: new perspectives." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/55/55134/tde-16072012-144620/.

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This work focus on the genetic generation of fuzzy systems. One of the main contribution of this work is the proposal of the FCA-BASED method, which generates the genetic search space using the formal concept analysis theory by extracting rules from data. The experimental evaluation results of the FCA-BASED method show its robustness, producing a good trade-off between the accuracy and the interpretability of the generated models. Moreover, the FCA-BASED method presents improvements to the DOC-BASED method, a previously proposed approach, related to the reduction of the computational cost for the generation of the genetic search space. In order to tackle high dimensional datasets, we also propose the FUZZYDT method, a fuzzy version of the classic C4.5 decision tree, a highly scalable method that presents low computational cost and competitive accuracy. Due to these characteristics, FUZZYDT is used in this work as a baseline method for the experimental evaluation and comparisons of other classic and fuzzy classification methods. We also include in this work the use of the FUZZYDT method to a real world problem, the warning of the coffee rust disease in Brazilian crops. Furthermore, this work investigates the task of feature subset selection to address the dimensionality issue of fuzzy systems. To this end, we propose the FUZZYWRAPPER method, a wrapper-based approach that selects features taking the relevant information regarding the fuzzyfication of the attributes into account, in the feature selection process. This work also investigates the automatic design of fuzzy data bases, proposing the FUZZYDBD method, which estimates the number of fuzzy sets defining all the attributes of a dataset and evenly distributing the fuzzy sets in the domains of the attributes. A modified version of the FUZZYDBD method, FUZZYDBD-II, which defines independent numbers of fuzzy sets for each attribute of a dataset, by means of estimation functions, is also proposed in this work
Este trabalho foca na geração genética de sistemas fuzzy. Uma das principais contribuições deste trabalho é a proposta do método FCA-BASED, que gera o espaço de busca genético usando a teoria de análise de conceitos formais por meio da extração de regras dos dados. Os resultados da avaliação experimental do método FCA-BASED demonstram sua robustez. O método FCABASED também produz um bom trade-off entre acurácia e interpretabilidade dos modelos gerados. Além disso, o método FCA-BASED apresenta melhorias em relação ao método DOC-BASED, uma abordagem proposta anteriormente. Essas melhorias estão relacionadas à redução do custo computacional para a geração do espaço de busca genético. Para ser capaz de trabalhar com conjuntos de dados de alta dimensão, foi também proposto o método FUZZYDT, uma versão fuzzy da clássica árvore de decisão C4.5. FUZZYDT é um método altamente escalável que apresenta baixo custo computacional e acurácia competitiva. Devido a essas características, o FUZZYDT é usado nesse trabalho como um método baseline para a avaliação experimental e comparações de outros métodos de classificação, fuzzy e clássicos. Também está incluido nesse trabalho a aplicação do método FUZZYDT em um problema do mundo real, o alerta da doença da ferrugem cafeeira em plantações brasileiras. Além disso, esse trabalho investiga a tarefa de seleção de atributos como forma de atacar o problema da dimensionalidade de sistemas fuzzy. Para esse fim, foi proposto o método FUZZYWRAPPER, uma abordagem baseada em wrapper que seleciona atributos levando em consideração as informações relevantes sobre a fuzificação dos atributos durante o processo de seleção. Esse trabalho também investiga a construção automática de bases de dados fuzzy, incluindo a proposta do método FUZZYDBD, que estima o número de conjuntos fuzzy que define todos os atributos de um conjunto de dados e distribui os conjuntos fuzzy proporcionalmente nos domínios dos atributos. Uma versão modificada do método FUZZYDBD, o método FUZZYDBD-II, também é proposta nesse trabalho. O método FUZZYDBD-II define números independentes de conjuntos fuzzy para cada atributo de um conjunto de dados por meio de funções de estimação
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Wang, Victoria Rui. "A new generation system for scientific knowledge discovery." Phd thesis, Canberra, ACT : The Australian National University, 2015. http://hdl.handle.net/1885/151246.

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Badakhova, Arina, and Reinis Virza. "Knowledge sharing between different generations in engineering field." Thesis, Högskolan Dalarna, Företagsekonomi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:du-34381.

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Purpose: The purpose of particular study is to explore individuals’ perceptions of knowledge sharing and its obstacles in a multigenerational engineering company. This study focuses on two groups of individuals: employees and managers. The perception of knowledge sharing and how differently generations perceive it is covered in this study. The obstacles which could occur during knowledge sharing between different generations in the engineering field are explored. The role of management in knowledge sharing processes is also covered. Methodology: To explore individuals’ perceptions of knowledge sharing and its obstacles in a multigenerational engineering company. A qualitative research approach was applied, using single company case study strategy. The case company is one of the leading construction engineering companies in Latvia. The primary data was gathered by conducting 12 semi-structured interviews, 3 interviews per every generation (Millennial, Generation X and Baby boomer) and 3 interviews with managers. The secondary data was obtained from the company, which included internal documents covering the general information about the company, guidelines and policies. By the usage of primary and secondary data triangulation of the study was reached. Findings: The thesis provides analysis of knowledge sharing and its obstacles within the multigenerational workforce of a construction engineering company. The perceptions of three generational cohorts such as Baby Boomers, Generation X and Millennials are presented. The conceptual framework for the study was built on the basis of three dimensions such as organizational. individual and technological obstacles. Based on the conceptual framework, authors brought up several propositions which supported the analysis process. The analysis showed that there are differences in perception of knowledge sharing and obstacles connected with it between engineers of different generations. Originality: There has not been any research about knowledge sharing between different generations in Latvia nor in Northern Europe, in general. The engineering field is a knowledge intensive sector, therefore knowledge sharing is crucial. Labor force still contains three different generations, thus it is important to explore whether engineering companies in Latvia have faced knowledge sharing obstacles, as it is a rapidly developing sector in this particular country.
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Casas, Manzanares Noé. "Injection of linguistic knowledge into neural text generation models." Doctoral thesis, Universitat Politècnica de Catalunya, 2020. http://hdl.handle.net/10803/671045.

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Language is an organic construct. It emanates from the need for communication and changes through time, influenced by multiple factors. The resulting language structures are a mix of regular syntactic and morphological constructions together with divergent irregular elements. Linguistics aims at formalizing these structures, providing a rationalization of the underlying phenomena. However, linguistic information alone is not enough to fully characterize the structures in language, as they are intrinsically tied to meaning, which constrains and modulates the applicability of the linguistic phenomena and also to context and domain. Classical machine translation approaches, like rule-based systems, relied completely on the linguistic formalisms. Hundreds of morphological and grammatical rules were wired together to analyze input text and translate it into the target language, trying to take into account the semantic load carried by it. While this kind of processing can satisfactorily address most of the low-level language structures, many of the meaning-dependent structures failed to be analyzed correctly. On the other hand, the dominant neural language processing systems are trained from raw textual data, handling it as a sequence of discrete tokens. These discrete tokens are normally defined looking for reusable word pieces identified statistically from data. In the whole training process, there is no explicit notion of linguistic knowledge: no morphemes, no morphological information, no relationships among words, or hierarchical groupings.This thesis aims at bridging the gap between the neural systems and linguistics-based systems, devising systems that have the flexibility and good results of the former with a base on the linguistic formalisms, with the purposes of improving quality where data alone cannot and forcing human-understandable working dynamics into the otherwise black-box neural systems. For this, we propose techniques to fuse statistical subwords with word-level linguistic information, to remove subwords altogether and rely solely on lemmas and morphological traits of the words, and to drive the text generation process on the ordering defined by syntactic dependencie. The main results of the proposed methods are the improvements in translation quality that can be obtained by injecting morphological information into NMT systems when testing on out-of-domain data for morphologically-rich languages, and the control over the generated text that can be gained by means of linking the generation order to the syntactic structure.
El lenguaje es una construcción orgánica que surge de la necesidad de comunicación, y que cambia a lo largo del tiempo, influenciado por múltiples factores, resultando en estructuras del lenguaje donde se mezclan construcciones morfológicas y sintácticas regulares con otros elementos irregulares. La lingüística tiene como objetivo el formalizar estas estructuras, proponiendo interpretaciones de los fenómenos subyacentes. Sin embargo, la lingüística no es suficiente para caracterizar de manera completa las estructuras del lenguaje, ya que éstas se encuentran intrínsicamente ligadas tanto al significado -al restringir y modular éste la aplicabilidad de los fenómenos lingüísticos- como al contexto y al dominio. Las técnicas de traducción automática clásicas empleadas por los sistemas basados en reglas, se basan en formalismos lingüísticos, haciendo uso de miles de reglas morfológicas y gramaticales para analizar texto del idioma de origen y traducirlo al idioma de destino, intentando mantener la carga semántica original. Aunque este tipo de traducción procesa adecuadamente la estructuras de bajo nivel del lenguaje, muchas estructuras dependientes del significado no son analizadas correctamente. Los sistemas de procesado del lenguaje natural dominantes, en cambio, se entrenan usando texto como datos de entrada. Dicho texto se procesa como una secuencia de elementos discretos, normalmente definidos como trozos de palabras o sub-palabras, que se agrupan en una estructura de diccionario que es confecccionado estadísticamente de modo que se maximice el reuso de sus sub-palabras al codificar el texto de entrenamiento. En todo este proceso, no hay ninguna noción explícita de conocimiento lingüístico, ni morfemas, ni información morfológica, ni relaciones sintácticas entre palabras o grupos jerárquicos. El objetivo de esta tesis es hibridizar los sistemas neuronales y los sistemas basados en reglas lingüísticas, de manera que el resultado pueda mostrar la flexibilidad y buenos resultados de los primeros, pero teniendo una base lingüística que le permita tanto mejorar la calidad del texto generado en los casos en los que simplemente más datos no lo consiguen, como establer unas dinámicas de funcionamiento internas que sean entendibles por humanos, a diferencia de la naturaleza de "caja negra" de los sistemas neuronales normales. Para ello, se proponen técnicas para enriqueces las sub-palabras con información lingüística de nivel de palabra, ténicas para prescindir de las sub-palabras y basarse únicamente en el lema y los rasgos lingüísticos de las palabras, y técnicas para dirigir el orden de generación de texto mediante dependencias sintácticas. Los principales resultados de los métodos propuestos son la mejora en la calidad de traducción en sistemas neuronales a los que les inyectamos información lingüística, especialmente en escenarios de lenguas morfológicamente ricas con texto de distinto dominio, y el control directo del proceso de generación al ligarlo a las estructuras sintácticas del texto.
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Jung, Hyun Ju. "The generation and flow of knowledge in technology development." Diss., Georgia Institute of Technology, 2013. http://hdl.handle.net/1853/50296.

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Scholars in strategy, economics, and sociology of science and technology have studied technology development as a source of firms’ economic gains as well as institutional changes. Drawing on the extant research of technology and innovation strategy, I investigate the problem of knowledge generation and flows in technology development. Specifically, I explore how firms generate novel technology and develop technological breakthroughs; how knowledge flows between firms affect interfirm cooperation in a knowledge network; and how science and technology programs impact the institutions of knowledge production. In Essay 1 (Chapter 2), I examine the antecedents of knowledge recombination and technological breakthroughs. Conceptualizing a firm’s exploration as a combinatory search of prior new-recombination (an original technology component), I investigate the impacts of prior new-recombination and search boundary (local vs. boundary-spanning) on the characteristics of focal invention. In particular, I theorize and juxtapose the contrasting effects of the boundary of technological search of prior new-recombination on the propensities that the focal invention generates new recombination and becomes a technological breakthrough. Specifically, I hypothesize that, when the technological search involves new recombination in prior inventions, 1) the likelihood of generating new recombination in the focal invention is greatest for a boundary spanning search, smallest for a local search, and intermediate for a hybrid search (which involves both types of search); but 2) the likelihood for the focal invention to become a technological breakthrough is greatest for a local search, smallest for a boundary spanning search, and intermediate for a hybrid search. I find supporting evidence from the analysis of U.S. nanotechnology patents granted between 1980 and 2006. The purpose of Essay 2 (Chapter 3) is to determine the effect of knowledge flows on the formation of interfirm cooperation. By distinguishing codified knowledge flows from tacit knowledge flows, this paper demonstrates that antecedents of interfirm cooperation lie in codified knowledge flows that precede interfirm cooperation. Two properties of asymmetry in directional codified knowledge flows, intensity and uncertainty, underpin this paper’s arguments and empirical tests. The main finding in this study is that intense codified knowledge flows weaken the formation of interfirm cooperation. By mapping dyadic firms to a center and a periphery firm within a knowledge network, I theorize that the uncertainty of directional codified knowledge flows induces the center and the periphery firms to pursue interfirm cooperation differently. The results show that while uncertainty caused by distant technology components in knowledge flows hinders a center firm from pursuing interfirm cooperation, uncertainty stimulates a periphery firm to pursue interfirm cooperation. A statistical analysis performed on a sample of enterprise software firms between 1992 and 2009 supports the hypotheses of this paper. In Essay 3 (Chapter 4), I examine how the National Nanotechnology Initiative (NNI), a most recent U.S. government’s science and technology (S&T) program launched in 2000, impacts the nature of university research in nanotechnology. I characterize the NNI as a policy intervention that targets the commercialization of technology and a focused research direction to promote national economic growth. As such, I expect that the NNI has brought about unintended consequences in terms of the direction of university-industry knowledge flows and the characteristics of university research output in nanotechnology. Using the difference-in-differences analysis of the U.S. nanotechnology patents filed between 1996 and 2007, I find that, for the U.S. universities, the NNI has increased knowledge inflows from the industry, diminished the branching-out to novel technologies, reduced the research scope, and decreased the likelihood of technological breakthroughs, as compared to other U.S. and non-U.S. research institutions. The findings suggest that, at least in the case of the NNI, targeted S&T programs of the government may increase the efficiency of university research, but potentially do so at a considerable price.
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Books on the topic "Knowledge generation"

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Martínez-Piva, Jorge Mario, ed. Knowledge Generation and Protection. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-1264-0.

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M, Beal George, Dissanayake Wimal, and Konoshima Sumiye, eds. Knowledge generation, exchange, and utilization. Boulder: Westview Press, 1986.

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Wolf, Steven A., and David Zilberman, eds. Knowledge Generation and Technical Change. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1499-2.

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Managing organizational knowledge: 3rd generation knowledge management and beyond. Boca Raton, FL: CRC Press, 2012.

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James, Gary Julian. Pedagogical knowledge: Representation, generation and application. Birmingham: University of Birmingham, 1992.

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Myler, Harley R. Automated knowledge generation: First year final report. [Washington, DC: National Aeronautics and Space Administration, 1988.

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Cain, Mark. Second generation knowledge based systems in habitat evaluation. Leicester: De Montfort University, 1993.

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Florance, Valerie. Next-generation IAIMS: Binding knowledge to effective action. Washington, D.C: Association of American Medical Colleges, 2002.

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Martin-Rodilla, Patricia. Digging into Software Knowledge Generation in Cultural Heritage. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-69188-6.

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Gina, Gotsill, ed. Surviving the baby boomer exodus: Capturing knowledge for Gen X and Gen Y employees. Boston, MA: Course Technology, 2011.

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Book chapters on the topic "Knowledge generation"

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Muñoz-Seca, Beatriz, and Josep Riverola. "Knowledge Generation." In Problem-Driven Management, 226–49. London: Palgrave Macmillan UK, 2004. http://dx.doi.org/10.1057/9780230504509_10.

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Ottosson, Stig. "Knowledge Generation." In Developing and Managing Innovation in a Fast Changing and Complex World, 97–109. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-94045-8_5.

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Hewitt, Carl. "Knowledge Processing." In Fifth Generation Computer Systems 1988, 161–62. London: Springer London, 1988. http://dx.doi.org/10.1007/978-1-4471-3156-4_16.

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Leeflang, Peter S. H., and Alessandro M. Peluso. "Knowledge Generation in Marketing." In Quantitative Marketing and Marketing Management, 149–70. Wiesbaden: Gabler Verlag, 2012. http://dx.doi.org/10.1007/978-3-8349-3722-3_7.

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Seu, Irene Bruna. "Between Knowledge and Action: Multidisciplinary Frames and the Psychosocial." In Passivity Generation, 9–35. London: Palgrave Macmillan UK, 2013. http://dx.doi.org/10.1057/9781137305039_2.

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Cimoli, Mario, and Annalisa Primi. "Intellectual Property and Development: An Interpretation of the (NEW) Markets for Knowledge." In Knowledge Generation and Protection, 3–26. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-1264-0_1.

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Villavicencio, Daniel. "Recent Changes in Science and Technology Policy in Mexico: Innovation Incentives." In Knowledge Generation and Protection, 263–90. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-1264-0_10.

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Castañeda, Jorge Amigo. "Scientific and Technological Policy in Mexico and Intellectual Property." In Knowledge Generation and Protection, 291–304. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-1264-0_11.

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Martínez-Piva, Jorge Mario. "Protection of Intellectual Property Rights, Innovation, and Development." In Knowledge Generation and Protection, 27–55. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-1264-0_2.

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Moncayo von Hase, Andrés. "The Flexibility of TRIPS and Its Possible Erosion in Bilateral, Multilateral, and Regional Negotiations." In Knowledge Generation and Protection, 59–83. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-1264-0_3.

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Conference papers on the topic "Knowledge generation"

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FUCHS-KITTOWSKI, FRANK, and KLAUS FUCHS-KITTOWSKI. "KNOWLEDGE MANAGEMENT BETWEEN PROVISION AND GENERATION OF KNOWLEDGE." In Proceedings of the 2007 International Conference. WORLD SCIENTIFIC, 2007. http://dx.doi.org/10.1142/9789812770592_0015.

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Hodge, Gail, Linda Hill, Marcia Lei Zeng, Jian Qin, and Douglas Tudhope. "Next generation knowledge organization systems." In the 5th ACM/IEEE-CS joint conference. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1065385.1065536.

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Yu, Wenhao, Meng Jiang, Zhiting Hu, Qingyun Wang, Heng Ji, and Nazneen Rajani. "Knowledge-Enriched Natural Language Generation." In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts. Stroudsburg, PA, USA: Association for Computational Linguistics, 2021. http://dx.doi.org/10.18653/v1/2021.emnlp-tutorials.3.

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Junfeng, Gao, Qu Jingye, and Xin Zhong. "Organization and Discovery of MOOCs Knowledge." In Future Generation Communication and Networking 2014. Science & Engineering Research Support soCiety, 2014. http://dx.doi.org/10.14257/astl.2014.73.19.

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Kim, Daesik, YoungJoon Yoo, Jeesoo Kim, Sangkuk Lee, and Nojun Kwak. "Dynamic Graph Generation Network: Generating Relational Knowledge from Diagrams." In 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). IEEE, 2018. http://dx.doi.org/10.1109/cvpr.2018.00438.

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Li, Yu, Baolin Peng, Yelong Shen, Yi Mao, Lars Liden, Zhou Yu, and Jianfeng Gao. "Knowledge-Grounded Dialogue Generation with a Unified Knowledge Representation." In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Stroudsburg, PA, USA: Association for Computational Linguistics, 2022. http://dx.doi.org/10.18653/v1/2022.naacl-main.15.

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Zheng, Chujie, Yunbo Cao, Daxin Jiang, and Minlie Huang. "Difference-aware Knowledge Selection for Knowledge-grounded Conversation Generation." In Findings of the Association for Computational Linguistics: EMNLP 2020. Stroudsburg, PA, USA: Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.findings-emnlp.11.

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Wang, Qingyun, Xiaoman Pan, Lifu Huang, Boliang Zhang, Zhiying Jiang, Heng Ji, and Kevin Knight. "Describing a Knowledge Base." In Proceedings of the 11th International Conference on Natural Language Generation. Stroudsburg, PA, USA: Association for Computational Linguistics, 2018. http://dx.doi.org/10.18653/v1/w18-6502.

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Wang, Shiquan, Yuke Si, Xiao Wei, Longbiao Wang, Zhiqiang Zhuang, Xiaowang Zhang, and Jianwu Dang. "TopicKS: Topic-driven Knowledge Selection for Knowledge-grounded Dialogue Generation." In Interspeech 2022. ISCA: ISCA, 2022. http://dx.doi.org/10.21437/interspeech.2022-11188.

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Zheng, Wen, Natasa Milic-Frayling, and Ke Zhou. "Approximation of Response Knowledge Retrieval in Knowledge-grounded Dialogue Generation." In Findings of the Association for Computational Linguistics: EMNLP 2020. Stroudsburg, PA, USA: Association for Computational Linguistics, 2020. http://dx.doi.org/10.18653/v1/2020.findings-emnlp.321.

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Reports on the topic "Knowledge generation"

1

Robinson, J. A., and Kevin J. Greene. New Generation Knowledge Processing. Volume 1. Fort Belvoir, VA: Defense Technical Information Center, October 1987. http://dx.doi.org/10.21236/ada190165.

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Robinson, J. A., and Kevin J. Greene. New Generation Knowledge Processing. Volume 2. Fort Belvoir, VA: Defense Technical Information Center, October 1987. http://dx.doi.org/10.21236/ada190166.

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Robinson, J. A., and Kevin J. Greene. New Generation Knowledge Processing. Volume 3. Fort Belvoir, VA: Defense Technical Information Center, October 1987. http://dx.doi.org/10.21236/ada190167.

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Filman, Robert E., Conrad Bock, Roy Feldman, Joshua Singer, and Richard Treitel. New Generation Knowledge System Development Tools. Fort Belvoir, VA: Defense Technical Information Center, April 1990. http://dx.doi.org/10.21236/ada223008.

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Thomas, Maikel A., Heidi Anne Smartt, and Robert F. Matthews. Processing large sensor data sets for safeguards : the knowledge generation system. Office of Scientific and Technical Information (OSTI), April 2012. http://dx.doi.org/10.2172/1039393.

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Bouillon, Cesar, Anna Crespo, Odette Maciel, Juan Manuel Puerta, Agustina Schijman, Coral Fernández, Miguel Soldano, et al. Review of Knowledge Generation and Dissemination in the Inter-American Development Bank. Inter-American Development Bank, February 2019. http://dx.doi.org/10.18235/0001652.

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Bouillon, César P., Anna Crespo, Coral Fernández Illescas, Juan Manuel Puerta, Agustina Schijman, Florencia Alejandre, Claudia Figueroa, Maria Jose Hernandez, and Patricia Sadeghi. Approach Paper: Knowledge Generation and Dissemination in the Inter-American Development Bank Group. Inter-American Development Bank, September 2017. http://dx.doi.org/10.18235/0000808.

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Volkova, Svitlana, Nathan Hodas, and Timothy Scheibe. AI-Driven Cross-Domain Knowledge Discoveryand Hypotheses Generation for Enhanced Earth System Predictability. Office of Scientific and Technical Information (OSTI), April 2021. http://dx.doi.org/10.2172/1769670.

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Katzenberger, John, James Arnott, and Alyson Wright. Next Generation Climate Change Experiments Needed to Advance Knowledge and for Assessment of CMIP6. Office of Scientific and Technical Information (OSTI), October 2014. http://dx.doi.org/10.2172/1163131.

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Israel, David. A Weak Logic of Knowledge and Belief: Epistemic and Doxastic Logic for the Yuppie Generation. Fort Belvoir, VA: Defense Technical Information Center, September 1985. http://dx.doi.org/10.21236/ada461771.

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