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Journal articles on the topic 'Knowledge acquisition'

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Published: 4 June 2021
Last updated: 7 September 2023

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1

Liou, Yihwa I. "Knowledge acquisition." ACM SIGMIS Database: the DATABASE for Advances in Information Systems 23, no. 1 (March 1992): 59–64. http://dx.doi.org/10.1145/134347.134364.

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2

Gracia-Moret, G. L. "Knowledge acquisition." Artificial Intelligence in Medicine 2, no. 2 (June 1990): 120. http://dx.doi.org/10.1016/0933-3657(90)90034-o.

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3

Borko, Harold. "Knowledge acquisition." Information Processing & Management 26, no. 4 (January 1990): 566–67. http://dx.doi.org/10.1016/0306-4573(90)90088-j.

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4

Putri, Nuril Kusumawardhani Soeprapto. "Akuisisi dan Budaya Knowledge Sharing." ComTech: Computer, Mathematics and Engineering Applications 2, no. 1 (June 1, 2011): 505. http://dx.doi.org/10.21512/comtech.v2i1.2795.

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Large companies which are experiencing barriers in innovation often take a radical step to acquire knowledge, namely acquisition. Though innovation is not the only reason, acquisition will result in the company wishes to achieve competitive advantage affected by the creation of ideas, creativity and innovation. The three points can be achieved more easily when the knowledge sharing within the organization / company runs well. However, the acquisition maybe impacts as a counter-attack for the knowledge sharing culture both in the acquisitor and and company which obtains the acquisition. Therefore, a key to succeed the acquisition is a sharing culture among individuals within a company that runs well or even better. Individuals from the acquisitor and those of the company that obtains the acquisition can adapt to each other and have confidence in order not to hinder them to share knowledge. This study discusses in detail the potential impacts of an acquisition upon a knowledge sharing culture in a company.
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5

Lefkowitz, Lawrence S., and Victor R. Lesser. "Knowledge acquisition as knowledge assimilation." International Journal of Man-Machine Studies 29, no. 2 (August 1988): 215–26. http://dx.doi.org/10.1016/s0020-7373(88)80047-6.

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6

Knight, Kevin. "Integrating knowledge acquisition and language acquisition." Applied Intelligence 1, no. 4 (May 1992): 277–95. http://dx.doi.org/10.1007/bf00122018.

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7

Deuser, Kaya, and Pavel Naumov. "Strategic Knowledge Acquisition." ACM Transactions on Computational Logic 22, no. 3 (June 24, 2021): 1–18. http://dx.doi.org/10.1145/3459993.

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The article proposes a trimodal logical system that can express the strategic ability of coalitions to learn from their experience. The main technical result is the completeness of the proposed system.
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8

Anjewierden, Anjo. "Knowledge Acquisition Tools." AI Communications, no. 1 (1987): 29–38. http://dx.doi.org/10.3233/aic-1987-0106.

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9

Sabou, Marta, Arno Scharl, and Michael Föls. "Crowdsourced Knowledge Acquisition." International Journal on Semantic Web and Information Systems 9, no. 3 (July 2013): 14–41. http://dx.doi.org/10.4018/ijswis.2013070102.

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Novel social media collaboration platforms, such as games with a purpose and mechanised labour marketplaces, are increasingly used for enlisting large populations of non-experts in crowdsourced knowledge acquisition processes. Climate Quiz uses this paradigm for acquiring environmental domain knowledge from non-experts. The game’s usage statistics and the quality of the produced data show that Climate Quiz has managed to attract a large number of players but noisy input data and task complexity led to low player engagement and suboptimal task throughput and data quality. To address these limitations, the authors propose embedding the game into a hybrid-genre workflow, which supplements the game with a set of tasks outsourced to micro-workers, thus leveraging the complementary nature of games with a purpose and mechanised labour platforms. Experimental evaluations suggest that such workflows are feasible and have positive effects on the game’s enjoyment level and the quality of its output.
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10

Boose, John, and Brian Gaines. "Editorial: Knowledge acquisition." International Journal of Man-Machine Studies 26, no. 1 (January 1987): 1–2. http://dx.doi.org/10.1016/s0020-7373(87)80031-7.

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11

Lanzola, Giordano, and Mario Stefanelli. "Inferential knowledge acquisition." Artificial Intelligence in Medicine 5, no. 3 (June 1993): 253–68. http://dx.doi.org/10.1016/0933-3657(93)90028-2.

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12

LIOU, Y. "Collaborative knowledge acquisition." Expert Systems with Applications 5, no. 1-2 (1992): 1–13. http://dx.doi.org/10.1016/0957-4174(92)90089-b.

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13

Aussenac-Gilles, Nathalie, and Fabien Gandon. "From the knowledge acquisition bottleneck to the knowledge acquisition overflow: A brief French history of knowledge acquisition." International Journal of Human-Computer Studies 71, no. 2 (February 2013): 157–65. http://dx.doi.org/10.1016/j.ijhcs.2012.10.009.

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14

Öberg, Christina. "Transferring acquisition knowledge – sources, directions and outcomes." Management Research: Journal of the Iberoamerican Academy of Management 15, no. 1 (April 10, 2017): 28–46. http://dx.doi.org/10.1108/mrjiam-02-2016-0644.

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Purpose The literature has described knowledge transfer in terms of how companies advance their merger and acquisition activities through experience. This indicates a knowledge transfer from one acquisition to the next, with the acquiring party being the carrier of such knowledge. The present paper aims to add to this view through pointing out how knowledge on how to acquire and how to integrate, follows also from other parties and their experiences. The paper discusses and classifies sources, directions and outcomes of knowledge transfer on acquisitions from a stakeholder point of view. Focus is on external stakeholders and knowledge is divided between knowledge on acquiring and knowledge on integrating, thus dealing with the pre- and post-merger stages of acquisitions. Design/methodology/approach The paper adopts a multiple case study research design to illustrate its point. While the individual acquisitions are interconnected through the acquirer or acquired party being the same company, indications are that knowledge on how, when and what party to acquire and how to integrate (degree, direction, timing and function) follows from external stakeholders and their previous experiences. Findings The findings suggest that knowledge on acquiring follows from general knowledge on sector levels, while specific parties – including customers, competitors and the acquired party – are the sources of knowledge on integration. Knowledge on acquiring is imitative, while knowledge on integrating rests more on the external stakeholders’ failures. Originality/value The paper provides a research design contribution to acquisition studies, as most such studies adopt a quantitative, secondary data approach. The main contribution is though the focus on external stakeholders as sources of knowledge on acquiring and integrating. The previous literature seems to suggest that it is the experience accumulated through the acquirer’s previous acquisitions that provides the acquisition knowledge. The paper’s perspective, which includes several external stakeholders, provides a rather unique piece of research on stakeholders in mergers and acquisitions.
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15

Kogut, Clarice Secches, Renato Dourado Cotta de Mello, and Angela da Rocha. "International expansion for knowledge acquisition or knowledge acquisition for international expansion?" Multinational Business Review 28, no. 2 (October 14, 2019): 177–200. http://dx.doi.org/10.1108/mbr-11-2018-0084.

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Purpose Starting from the knowledge-based view as a theoretical perspective, this study aims to examine how an emerging market multinational enterprise (EMMNE) engages in reverse knowledge transfer (RKT) processes and how such processes are managed by headquarters. Therefore, this paper captures the perspective of top management concerning RKT and the processes used to create, transfer and integrate knowledge. Design/methodology/approach The study uses a longitudinal design based on the case method of investigation. The case selected for the study was a Brazilian company theoretically sampled for being a domestically, regionally and globally important, information-rich company that operates in an industry in which technology plays a crucial role. The company was also selected for having had asset-seeking motives in at least some of its foreign market entries and for having successfully absorbed foreign-acquired capabilities. Findings The study provides counterfactual evidence to the springboard perspective, considering timing and speed of the internationalization and catch-up processes and the size of acquisitions. The study also highlights differences to other emerging market multinational enterprises, concerning the internationalization trajectory and catch-up moves, and to traditional MNEs, regarding RKT challenges and practices. Research limitations/implications The main limitations of the study relate to the case study method, which does not allow for statistical generalization, although it does support analytical generalization. Originality/value The study contributes to the literature by shedding light on the process by which a Latin American multinational firm developed technological capabilities to compete globally, focusing on the symbiotic, self-nurturing relationship between internationalization processes and technology acquisition and integration processes. Moreover, the work provides novel theoretical insights regarding timing, location, size and execution of the RKT activities. Finally, the paper contributes to the understanding of the relational aspects of the RKT process by focusing on building human relationships as the major force behind knowledge integration and examining the resistance of the acquired companies from developed markets to adopt the parent company’s best practices, or to contribute to its integrated knowledge, when the parent company is an EMMNE.
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16

Runkel, Jay T., and William P. Birmingham. "Knowledge acquisition in the small: building knowledge-acquisition tools from pieces." Knowledge Acquisition 5, no. 2 (June 1993): 221–43. http://dx.doi.org/10.1006/knac.1993.1009.

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17

Motoda, H., R. Mizoguchi, J. Boose, and B. Gaines. "Knowledge acquisition for knowledge-based systems." IEEE Expert 6, no. 4 (August 1991): 53–64. http://dx.doi.org/10.1109/64.85921.

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18

Müller-Kolck, Ulrich. "Knowledge acquisition for knowledge-based systems." Artificial Intelligence in Medicine 2, no. 2 (June 1990): 119–20. http://dx.doi.org/10.1016/0933-3657(90)90033-n.

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19

Gruber, Thomas R. "Automated knowledge acquisition for strategic knowledge." Machine Learning 4, no. 3-4 (December 1989): 293–336. http://dx.doi.org/10.1007/bf00130716.

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20

Morales, Francisco Javier. "Do acquisitions lead to knowledge search renewal? Inventor's knowledge search after an acquisition." Academy of Management Proceedings 2019, no. 1 (August 1, 2019): 13048. http://dx.doi.org/10.5465/ambpp.2019.13048abstract.

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21

Kuhn, Deanna, Merce Garcia-Mila, Anat Zohar, Christopher Andersen, Sheldon H. White, David Klahr, and Sharon M. Carver. "Strategies of Knowledge Acquisition." Monographs of the Society for Research in Child Development 60, no. 4 (1995): i. http://dx.doi.org/10.2307/1166059.

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22

Sawaragi, Tetsuo. "Knowledge Acquisition and Instruction." Journal of the Robotics Society of Japan 13, no. 5 (1995): 588–91. http://dx.doi.org/10.7210/jrsj.13.588.

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23

Kahn, Gary, Steven Nowlan, and John McDermott. "Strategies for Knowledge Acquisition." IEEE Transactions on Pattern Analysis and Machine Intelligence PAMI-7, no. 5 (September 1985): 511–22. http://dx.doi.org/10.1109/tpami.1985.4767699.

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24

Winter, Stephan, Krzysztof Janowicz, Kai-Florian Richter, and Maria Vasardani. "Knowledge acquisition about places." SIGSPATIAL Special 4, no. 3 (November 2012): 20–21. http://dx.doi.org/10.1145/2429177.2429181.

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25

Shan, X. H., A. Y. C. Nee, and A. N. Poo. "Process Planning Knowledge Acquisition." IFAC Proceedings Volumes 25, no. 28 (October 1992): 157–61. http://dx.doi.org/10.1016/s1474-6670(17)49484-5.

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26

Gaines, Brian R., and Mildred L. G. Shaw. "Integrated knowledge acquisition architectures." Journal of Intelligent Information Systems 1, no. 1 (August 1992): 9–34. http://dx.doi.org/10.1007/bf01006412.

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27

Eriksson, H., and M. Musen. "Metatools for knowledge acquisition." IEEE Software 10, no. 3 (May 1993): 23–29. http://dx.doi.org/10.1109/52.210598.

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28

Reich, Yoram. "Exemplar-based knowledge acquisition." Machine Learning 6, no. 1 (January 1991): 99–103. http://dx.doi.org/10.1007/bf00153763.

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29

WILSON, D. "Strategies of knowledge acquisition." Journal of Social and Biological Systems 11, no. 1 (January 1988): 161–63. http://dx.doi.org/10.1016/0140-1750(88)90058-9.

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30

Tzafestas, Spyros. "Knowledge acquisition as modeling." Advances in Engineering Software 21, no. 2 (January 1994): 133–34. http://dx.doi.org/10.1016/0965-9978(94)90040-x.

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31

Snaprud, Mikael, and Hermann Kaindl. "Knowledge acquisition using hypertext." Expert Systems with Applications 5, no. 3-4 (January 1992): 369–75. http://dx.doi.org/10.1016/0957-4174(92)90020-s.

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32

MENZIES, TIM. "Towards situated knowledge acquisition." International Journal of Human-Computer Studies 49, no. 6 (December 1998): 867–93. http://dx.doi.org/10.1006/ijhc.1998.0230.

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33

Musen, Mark A. "Knowledge acquisition at the metalevel: creation of custom-tailored knowledge-acquisition tools." ACM SIGART Bulletin, no. 108 (April 1989): 45–55. http://dx.doi.org/10.1145/63266.63272.

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34

Gruber, Thomas R., and Paul R. Cohen. "Design for acquisition: principles of knowledge-system design to facilitate knowledge acquisition." International Journal of Man-Machine Studies 26, no. 2 (February 1987): 143–59. http://dx.doi.org/10.1016/s0020-7373(87)80088-3.

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35

Kim, Jae-Kyeong. "Knowledge acquisition for knowledge based decision systems." Applied Artificial Intelligence 11, no. 2 (March 1997): 131–50. http://dx.doi.org/10.1080/088395197118280.

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36

Preston, S., C. Chapman, M. Pinfold, and G. Smith. "Knowledge acquisition for knowledge-based engineering systems." International Journal of Information Technology and Management 4, no. 1 (2005): 1. http://dx.doi.org/10.1504/ijitm.2005.006401.

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37

Nwana, Hyacinth S., Trevor J. M. Bench-Capon, Ray C. Paton, and Michael J. R. Shave. "Domain-driven knowledge modelling for knowledge acquisition." Knowledge Acquisition 6, no. 3 (September 1994): 243–70. http://dx.doi.org/10.1006/knac.1994.1013.

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38

Chen, Andrew N. K., Yuhchang Hwang, and T. S. Raghu. "Knowledge Life Cycle, Knowledge Inventory, and Knowledge Acquisition Strategies." Decision Sciences 41, no. 1 (February 2010): 21–47. http://dx.doi.org/10.1111/j.1540-5915.2009.00258.x.

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39

Zhen, L., Z. Jiang, G. Q. Huang, and J. Liang. "Knowledge acquisition for product development in knowledge grid." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 222, no. 11 (November 1, 2008): 2269–80. http://dx.doi.org/10.1243/09544062jmes672.

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This paper is mainly concerned with the implementation of innovative product development-oriented knowledge acquisition in a knowledge grid. The architecture of a knowledge acquisition platform based on the theory of inventive problem solving (TRIZ) and ontology is proposed at first. Then the key techniques analysed are: ontology building for product development, semantic register, semantic parser, query dispatch, and knowledge acquisition based on contradiction matrix. Finally, working scenarios are employed to illustrate the knowledge acquisition process.
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40

Feng, Xin, and Thomas A. Weber. "Knowledge Acquisition Advisor (KA2): An interactive knowledge-acquisition tool for expert system development." Engineering Applications of Artificial Intelligence 6, no. 6 (December 1993): 507–18. http://dx.doi.org/10.1016/0952-1976(93)90048-3.

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41

Alexander, Phill. "KNOWing How to Play: Gamer Knowledges and Knowledge Acquisition." Computers and Composition 44 (June 2017): 1–12. http://dx.doi.org/10.1016/j.compcom.2017.03.004.

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42

Kaba, Abdoulaye, and Chennupati K. Ramaiah. "Predicting knowledge creation through the use of knowledge acquisition tools and reading knowledge sources." VINE Journal of Information and Knowledge Management Systems 50, no. 3 (January 2, 2020): 531–51. http://dx.doi.org/10.1108/vjikms-07-2019-0106.

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Purpose The purpose of this research paper is to report about an investigation on the relationship between knowledge acquisition and knowledge creation to find out whether knowledge acquisition can predict knowledge creation. The study measures the concept of knowledge acquisition through the faculty use of knowledge acquisition tools and reading knowledge sources while measuring the concept of knowledge creation through the faculty use of knowledge creation tools and publishing knowledge sources. Design/methodology/approach The population of the study is faculty members in the United Arab Emirates (UAE). The sample of the population consisted of 300 faculty members affiliated with 26 universities and colleges. Data was collected from the sample through questionnaire instrument. Stated hypotheses and Mathew’s theory of knowledge consumption–production correlation are tested and verified through correlation matrix and regression analysis. Findings Findings of the study revealed that the use of knowledge acquisition tools by faculty members has a positive effect on the use of knowledge creation tools and on publishing knowledge sources. Likewise, reading knowledge sources appeared to have a positive impact on the use of knowledge creation tools and publishing knowledge sources. Accordingly, the study confirmed the stated four hypotheses. Moreover, the results of the study supported the theory of knowledge consumption–production correlation and strongly confirmed the prediction of knowledge creation through the use of information and communication technology (ICT) tools for knowledge acquisition and reading knowledge sources. Practical implications Findings of the study appeal to the decision-makers and stakeholders of academic institutions to make effective investment in ICT facilities and knowledge sources to improve knowledge creation among faculty members. Originality/value Not many studies have investigated how knowledge acquisition can predict knowledge creation in the academic environment. This paper contributes to the understanding of the relationship between knowledge acquisition and knowledge creation in academic settings. Findings of the study can be an important reference for providing and improving knowledge sources, knowledge acquisition tools and knowledge creation tools in the academic environment.
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43

Kukko, Marianne. "Knowledge Sharing Barriers of Acquisitioned Growth: A Case Study from a Software Company." International Journal of Engineering Business Management 5 (January 1, 2013): 8. http://dx.doi.org/10.5772/56005.

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Acquisition as a growth strategy is often burdened by subsequent unsatisfactory performance. The literature suggests that a potential cause is mismanagement of knowledge. Such mismanagement may occur if the barriers to knowledge sharing in acquisitioned growth are not adequately understood. Hence, the aim of this study is to improve understanding of the potentially most restrictive knowledge sharing barriers in acquisitioned growth. It does so through a case study in the context of the software business. The findings of the study will help companies with a strategy of growing through acquisitions to better prepare for the challenging task of managing such growth. The paper also contributes to the literature on knowledge management by defining knowledge sharing barriers in the context of acquisitioned growth in the software business. A contribution to growth literature is made by touching on the issue of the management of acquisitions from the perspective of knowledge management, and especially knowledge sharing.
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44

Slocum, Terry A., and Stephen L. Egbert. "Knowledge Acquisition from Choropleth Maps." Cartography and Geographic Information Systems 20, no. 2 (January 1993): 83–95. http://dx.doi.org/10.1559/152304093782610351.

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45

Kilpeläinen, Tiina. "Knowledge Acquisition for Generalization Rules." Cartography and Geographic Information Science 27, no. 1 (January 2000): 41–50. http://dx.doi.org/10.1559/152304000783547993.

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46

Leake, Charles R., Karen L. McGraw, and Karan Harbison-Briggs. "Knowledge Acquisition: Principles and Guidelines." Journal of the Operational Research Society 42, no. 12 (December 1991): 1125. http://dx.doi.org/10.2307/2582962.

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47

Veale, Tony, and Guofu Li. "Creative Introspection and Knowledge Acquisition." Proceedings of the AAAI Conference on Artificial Intelligence 25, no. 1 (August 4, 2011): 1243–48. http://dx.doi.org/10.1609/aaai.v25i1.8073.

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Introspection is a question-led process in which one builds on what one already knows to explore what is possible and plausible. In creative introspection, whether in art or in science, framing the right question is as important as finding the right answer. Presupposition-laden questions are themselves a source of knowledge, and in this paper we show how widely-held beliefs about the world can be dynamically acquired by harvesting such questions from the Web. We show how metaphorical reasoning can be modeled as an introspective process, one that builds on questions harvested from the Web to pose further speculative questions and queries. Metaphor is much more than a knowledge-hungry rhetorical device: it is a conceptual lever that allows a system to extend its model of the world.
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48

Matoskova, Jana, Helena Rehackova, Eliska Sobotkova, Martina Polcakova, Martin Jurasek, Ales Gregar, and Vlastimil Svec. "Facilitating Leader Tacit Knowledge Acquisition." Journal of Competitiveness 5, no. 1 (March 31, 2013): 3–15. http://dx.doi.org/10.7441/joc.2013.01.01.

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49

Grigorenko, I. N., and T. F. Datsko. "EFFECTIVE KNOWLEDGE ACQUISITION THROUGH HYPERTEXT." Historical and social-educational ideas 9, no. 1/2 (January 1, 2017): 135–39. http://dx.doi.org/10.17748/2075-9908-2017-9-1/2-135-139.

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50

Bergadano, F., Y. Kodratoff, and K. Morik. "Machine Learning and Knowledge Acquisition." AI Communications 5, no. 1 (1992): 19–24. http://dx.doi.org/10.3233/aic-1992-5102.

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