Relevant bibliographies by topics / Knowledge acquisition

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Knowledge acquisition'

Author: Grafiati
Published: 4 June 2021
Last updated: 7 September 2023

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Journal articles on the topic "Knowledge acquisition"

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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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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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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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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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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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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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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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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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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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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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Dissertations / Theses on the topic "Knowledge acquisition"

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Al-Jabir, Shaikha. "Terminology-based knowledge acquisition." Thesis, University of Surrey, 1999. http://epubs.surrey.ac.uk/843300/.

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A methodology for knowledge acquisition from terminology databases is presented. The methodology outlines how the content of a terminology database can be mapped onto a knowledge base with a minimum of human intervention. Typically, terms are defined and elaborated by terminologists by using sentences that have a common syntactic and semantic structure. It has been argued that in defining terms, terminologists use a local grammar and that this local grammar can be used to parse the definitions. The methodology has been implemented in a program called DEARSys (Definition Analysis and Representation System), that reads definition sentences and extracts new concepts and conceptual relations about the defined terms. The linguistic component of the system is a parser for the sublanguage of terminology definitions that analyses a definition into its logical form, which in turn is mapped onto a frame-based representation. The logical form is based on first-order logic (FOL) extended with untyped lambda calculus. Our approach is data-driven and domain independent; it has been applied to definitions of various domains. Experiments were conducted with human subjects to evaluate the information acquired by the system. The results of the preliminary evaluation were encouraging.
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Youn, Bong-Soo. "Intelligent knowledge acquisition system /." Online version of thesis, 1989. http://hdl.handle.net/1850/10444.

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González-Fernández, Beatriz. "Vocabulary knowledge components : knowledge, acquisition and conceptualisation." Thesis, University of Nottingham, 2018. http://eprints.nottingham.ac.uk/52090/.

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Vocabulary knowledge is a multifaceted construct for which complete command comprises mastering various types of knowledge. Achieving this full mastery is deemed challenging and problematic for second language learners, and yet it is key for successful and appropriate language use (Webb & Nation, 2017). By understanding how these various kinds of knowledge behave and relate, practitioners can better systematise when and how they are introduced to the students, and thus facilitate the overall vocabulary learning process. Nevertheless, little is known about how these multiple types of word knowledge are acquired by learners of a second/foreign language. This thesis attempts to contribute to bridging this gap by empirically exploring the knowledge, acquisition and conceptualisation of overall vocabulary knowledge in second languages. Five studies are devoted to this aim. Study 1 examined the knowledge and order of acquisition of four different components of vocabulary knowledge (form–meaning link, collocations, derivatives and multiple meanings) in recall and recognition. It shows that those components vary considerably in their difficulty for second language (L2) learners, and implicational scaling analysis revealed that a consistent order of acquisition of these components can be established. Study 2 investigated how various factors typically identified as influencing vocabulary learning affect the mastery of those four word knowledge components. The results suggest that cognateness status of the target words has the strongest effect on knowledge of most vocabulary aspects by Spanish learners of L2 English, followed by frequency and proficiency. Importantly, this cognate influence raised the question of whether the order of acquisition of word knowledge components retrieved in Study 1 was unique to L2 English learners of cognate languages. Study 3 explored the theoretical conceptualisation of vocabulary knowledge by attempting to provide empirical support for its multidimensionality. Structural equation modelling analyses exposed that the various types of vocabulary knowledge were so interconnected that they could not be considered separate dimensions. This finding suggests that the different aspects of vocabulary knowledge are better seen as various word knowledge difficulty levels that comprise a unidimensional construct. Finally, Studies 4 and 5 tried to provide generalisability to the previous findings by replicating Studies 1 and 3, respectively, with Chinese L2 learners of English. Study 4 investigated the hypothesis that the order of acquisition outlined in Study 1 for Spanish learners depended partially on the cognate status of the participants’ language. The implicational scaling analysis with the non-cognate Chinese population, however, corroborated the order of acquisition of vocabulary aspects previously suggested, indicating that a universal vocabulary acquisition order might exist. Study 5 also confirmed the finding that vocabulary knowledge is not empirically multidimensional. In addition, it provided evidence for the fact that the vocabulary knowledge construct functions similarly across the Chinese and Spanish learners of English as a unidimensional concept. Taken together, the results presented in this thesis support the notion that mastering the various components involved in word knowledge is a slow and incremental process, and demonstrate that some of them seem to be consistently acquired before others. Nonetheless, the findings also suggest that these different types of word knowledge cannot be considered separate dimensions in the learners’ mental lexicon, and thereby the multidimensional structure of vocabulary knowledge might need to be reconsidered. Overall, while more research is needed, these findings offer useful insights for the learning and teaching of vocabulary in a more systematic and efficient manner.
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Bakke, Elise. "Knowledge acquisition and modelling for knowledge-intensive CBR." Thesis, Norwegian University of Science and Technology, Department of Computer and Information Science, 2005. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9187.

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This thesis contains a study of state of the art knowledge acquisition modelling principles and methods for modelling general domain knowledge. This includes Newell's knowledge level, knowledge level modelling, Components of Expertise, CommonKADS and the Protégé meta tool. The thesis also includes a short introduction to the knowledge-intensive case-based reasoning system TrollCreek. Based on this background knowledge, one did analysis and comparison of different possible solutions. Then, after justifying the choices made, a knowledge acquisition method for TrollCreek was created. The method was illustrated through an example, evaluated and discussed.

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Jones, Hugh William Fawcett. "Children's understanding of knowledge acquisition." Thesis, University of Oxford, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306994.

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Wu, Xindong. "Knowledge acquisition from data bases." Thesis, University of Edinburgh, 1993. http://hdl.handle.net/1842/581.

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Knowledge acquisition from databases is a research frontier for both data base technology and machine learning (ML) techniques,and has seen sustained research over recent years. It also acts as a link between the two fields,thus offering a dual benefit. Firstly, since database technology has already found wide application in many fields ML research obviously stands to gain from this greater exposure and established technological foundation. Secondly, ML techniques can augment the ability of existing database systems to represent acquire,and process a collection of expertise such as those which form part of the semantics of many advanced applications (e.gCAD/CAM).The major contribution of this thesis is the introduction of an effcient induction algorithm to facilitate the acquisition of such knowledge from databases. There are three typical families of inductive algorithms: the generalisation- specialisation based AQ11-like family, the decision tree based ID3-like family,and the extension matrix based family. A heuristic induction algorithm, HCV based on the newly-developed extension matrix approach is described in this thesis. By dividing the positive examples (PE) of a specific class in a given example set into intersect in groups and adopting a set of strategies to find a heuristic conjunctive rule in each group which covers all the group's positiv examples and none of the negativ examples(NE),HCV can find rules in the form of variable-valued logic for PE against NE in low-order polynomial time. The rules generated in HCV are shown empirically to be more compact than the rules produced by AQ1-like algorithms and the decision trees produced by the ID3-like algorithms. KEshell2, an intelligent learning database system, which makes use of the HCV algorithm and couples ML techniques with database and knowledgebase technology, is also described.
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Muggleton, Stephen H. "Inductive acquisition of expert knowledge." Thesis, University of Edinburgh, 1986. http://hdl.handle.net/1842/8124.

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Expert systems divide neatly into two categories: those in which ( 1) the expert decisions result in changes to some external environment (control systems), and (2) the expert decisions merely seek to describe the environment (classification systems). Both the explanation of computer-based reasoning and the "bottleneck" (Feigenbaum, 1979) of knowledge acquisition are major issues in expert systems research. We have contributed to these areas of research in two ways. Firstly, we have implemented an expert system shell, the Mugol environment, which facilitates knowledge acquisition by inductive inference and provides automatic explanation of run-time reasoning on demand. RuleMaster, a commercial version of this environment, has been used to advantage industrially in the construction and testing of two large classification systems. Secondly, we have investigated a new technique called sequence induction which can be used in the construction of control systems. Sequence induction is based on theoretical work in grammatical learning. We have improved existing grammatical learning algorithms as well as suggesting and theoretically characterising new ones. These algorithms have been successfully applied to the acquisition of knowledge for a diverse set of control systems, including inductive construction of robot plans and chess end-game strategies.
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Chisnall, Anne Clare. "Grounded theory for knowledge acquisition." Thesis, De Montfort University, 1998. http://hdl.handle.net/2086/4140.

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Thomas, Christopher J. "Knowledge Acquisition in a System." Wright State University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=wright1357753287.

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Bosan, Sorel. "Interactive Simulations for Knowledge Acquisition." W&M ScholarWorks, 1989. https://scholarworks.wm.edu/etd/1539626819.

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Books on the topic "Knowledge acquisition"

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Brulé, James F. Knowledge acquisition. New York: McGraw-Hill, 1989.

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Luelsdorff, Philip A. Knowledge complexity and knowledge acquisition. Regensburg: P.A. Luelsdorff, Universität Regensburg, 1992.

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1943-, Dillon Tharam S., and Knowledge Systems Research Pty Ltd., eds. Automated knowledge acquisition. New York: Prentice Hall, 1994.

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Aussenac, N., G. Boy, B. Gaines, M. Linster, J. G. Ganascia, and Y. Kodratoff, eds. Knowledge Acquisition for Knowledge-Based Systems. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/3-540-57253-8.

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R, Gaines Brian, and Boose John H, eds. Knowledge acquisition for knowledge-based systems. London: Academic Press, 1988.

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Meyrowitz, Alan L., and Susan Chipman, eds. Foundations of Knowledge Acquisition. Boston, MA: Springer US, 1993. http://dx.doi.org/10.1007/b102257.

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Shadbolt, Nigel, Kieron O'Hara, and Guus Schreiber, eds. Advances in Knowledge Acquisition. Berlin, Heidelberg: Springer Berlin Heidelberg, 1996. http://dx.doi.org/10.1007/3-540-61273-4.

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Wu, Xindong. Knowledge acquisition from databases. Norwood, N.J: Ablex Pub., 1995.

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F, Chipman Susan, and Meyrowitz Alan Lester, eds. Foundations of knowledge acquisition. Boston: Kluwer Academic Publishers, 1993.

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M, Ford Kenneth, and Bradshaw Jeffrey M, eds. Knowledge acquisition as modeling. New York: Wiley, 1993.

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Book chapters on the topic "Knowledge acquisition"

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Wright, Stephen. "Acquisition." In Knowledge Transmission, 30–44. 1 [edition]. | New York : Routledge, 2018. | Series: Routledge focus on philosophy: Routledge, 2018. http://dx.doi.org/10.4324/9781315111384-3.

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Grzymala-Busse, Jerzy W. "Knowledge Acquisition." In Managing Uncertainty in Expert Systems, 43–76. Boston, MA: Springer US, 1991. http://dx.doi.org/10.1007/978-1-4615-3982-7_3.

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Mohan, Chilukuri Krishna. "Knowledge Acquisition." In Frontiers of Expert Systems, 201–36. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4509-5_8.

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Huysman, Marleen, and Dirk de Wit. "Knowledge Acquisition." In Information Science and Knowledge Management, 47–65. Dordrecht: Springer Netherlands, 2002. http://dx.doi.org/10.1007/978-94-015-9992-4_4.

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Swain, Martin. "Knowledge Acquisition." In Encyclopedia of Systems Biology, 1073. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_1031.

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Weik, Martin H. "knowledge acquisition." In Computer Science and Communications Dictionary, 864. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_9871.

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Kidd, Alison L. "Knowledge Acquisition." In Knowledge Acquisition for Expert Systems, 1–16. Boston, MA: Springer US, 1987. http://dx.doi.org/10.1007/978-1-4613-1823-1_1.

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Schmoldt, Daniel L., and H. Michael Rauscher. "Knowledge Acquisition." In Building Knowledge-Based Systems for Natural Resource Management, 139–73. Boston, MA: Springer US, 1996. http://dx.doi.org/10.1007/978-1-4613-1155-3_5.

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Sagerer, Gerhard, and Heinrich Niemann. "Acquisition of Knowledge." In Semantic Networks for Understanding Scenes, 317–52. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4899-1913-7_7.

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Kordon, Arthur K. "Problem Knowledge Acquisition." In Applying Data Science, 203–19. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-36375-8_7.

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Conference papers on the topic "Knowledge acquisition"

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Grundgeiger, Tobias, Julian Hester, Volker Held, and Jörn Hurtienne. "Beyond Knowledge Acquisition." In CSCW '17: Computer Supported Cooperative Work and Social Computing. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3022198.3026315.

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"Letter of acquisition." In Knowledge Engineering 2009). IEEE, 2009. http://dx.doi.org/10.1109/ictke.2009.5397313.

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Pantel, Patrick, Deepak Ravichandran, and Eduard Hovy. "Towards terascale knowledge acquisition." In the 20th international conference. Morristown, NJ, USA: Association for Computational Linguistics, 2004. http://dx.doi.org/10.3115/1220355.1220466.

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Wagner, William P. "Issues in knowledge acquisition." In the 1990 ACM SIGBDP conference. New York, New York, USA: ACM Press, 1990. http://dx.doi.org/10.1145/97709.97728.

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Assadi, Houssem. "Knowledge acquisition from texts." In the eighth conference. Morristown, NJ, USA: Association for Computational Linguistics, 1997. http://dx.doi.org/10.3115/979617.979683.

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Assadi, Houssem. "Knowledge acquisition from texts." In the 35th annual meeting. Morristown, NJ, USA: Association for Computational Linguistics, 1997. http://dx.doi.org/10.3115/976909.979683.

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Shadbolt, N. R., and R. K. Stobart. "Knowledge acquisition for knowledge based process control." In the third international conference. New York, New York, USA: ACM Press, 1990. http://dx.doi.org/10.1145/98894.99139.

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Armella, Michael, Isai Michel Lombera, Stuart H. Rubin, Shu-Ching Chen, and Gordon Lee. "Knowledge acquisition from corresponding domain knowledge transformations." In Integration (IRI). IEEE, 2009. http://dx.doi.org/10.1109/iri.2009.5211547.

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Bartl, Eduard, and Radim Belohlavek. "Knowledge Spaces with Graded Knowledge States." In 2008 International Symposium on Knowledge Acquisition and Modeling (KAM). IEEE, 2008. http://dx.doi.org/10.1109/kam.2008.106.

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Hua, Jiang. "Study on Knowledge Acquisition Techniques." In 2008 Second International Symposium on Intelligent Information Technology Application (IITA). IEEE, 2008. http://dx.doi.org/10.1109/iita.2008.152.

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Reports on the topic "Knowledge acquisition"

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Klinker, Georg, Casey Boyd, and Serge Genetet. A Knack for Knowledge Acquisition. Fort Belvoir, VA: Defense Technical Information Center, August 1987. http://dx.doi.org/10.21236/ada201187.

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Abrett, Glenn, Mark H. Bursstein, John Gunshenan, and Livia Polany. The BBN Knowledge Acquisition Project. Fort Belvoir, VA: Defense Technical Information Center, September 1988. http://dx.doi.org/10.21236/ada203846.

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Gil, Yolanda, and Cecile Paris. Towards Method-Independent Knowledge Acquisition. Fort Belvoir, VA: Defense Technical Information Center, June 1994. http://dx.doi.org/10.21236/ada285823.

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Domingos, Pedro. Algorithms for Collective Knowledge Acquisition. Fort Belvoir, VA: Defense Technical Information Center, May 2012. http://dx.doi.org/10.21236/ada561728.

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Swartout, Bill, and Yolanda Gil. Flexible Knowledge Acquisition Through Explicit Representation of Knowledge Roles. Fort Belvoir, VA: Defense Technical Information Center, January 1996. http://dx.doi.org/10.21236/ada459767.

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Gil, Yolanda. Template Enhancement Through Knowledge Acquisition (TEMPLE). Fort Belvoir, VA: Defense Technical Information Center, September 2004. http://dx.doi.org/10.21236/ada427491.

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Gil, Yolanda, and Cecile L. Paris. Towards Versatile and Practical Knowledge Acquisition. Fort Belvoir, VA: Defense Technical Information Center, June 1993. http://dx.doi.org/10.21236/ada269596.

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Muraida, Daniel J., Gary R. Grimes, and Saul B. Wilen. CBT Data /Knowledge Acquisition: Using Knowledge Objects to Prototype Courseware,. Fort Belvoir, VA: Defense Technical Information Center, January 1998. http://dx.doi.org/10.21236/ada362149.

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Van Lehn, Kurt. Long Term Learning: Integration of Knowledge Acquisition and Knowledge Compilation. Fort Belvoir, VA: Defense Technical Information Center, January 1994. http://dx.doi.org/10.21236/ada274775.

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McKeown, David M., Harvey Jr., and Wilson A. Automatic Knowledge Acquisition for Aerial Image Interpretation. Fort Belvoir, VA: Defense Technical Information Center, December 1987. http://dx.doi.org/10.21236/ada188616.

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