Relevant bibliographies by topics / Knowledge acquisition bottleneck

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  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Knowledge acquisition bottleneck'

Author: Grafiati
Published: 31 August 2024
Last updated: 31 July 2025

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Journal articles on the topic "Knowledge acquisition bottleneck"

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Cullen, J., and A. Bryman. "The Knowledge Acquisition Bottleneck: Time for Reassessment?" Expert Systems 5, no. 3 (1988): 216–25. http://dx.doi.org/10.1111/j.1468-0394.1988.tb00065.x.

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Wagner, Christian. "Breaking the Knowledge Acquisition Bottleneck Through Conversational Knowledge Management." Information Resources Management Journal 19, no. 1 (2006): 70–83. http://dx.doi.org/10.4018/irmj.2006010104.

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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 (2013): 157–65. http://dx.doi.org/10.1016/j.ijhcs.2012.10.009.

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Hoppenbrouwers, Stijn, Bart Schotten, and Peter Lucas. "Towards Games for Knowledge Acquisition and Modeling." International Journal of Gaming and Computer-Mediated Simulations 2, no. 4 (2010): 48–66. http://dx.doi.org/10.4018/jgcms.2010100104.

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Many model-based methods in AI require formal representation of knowledge as input. For the acquisition of highly structured, domain-specific knowledge, machine learning techniques still fall short, and knowledge elicitation and modelling is then the standard. However, obtaining formal models from informants who have few or no formal skills is a non-trivial aspect of knowledge acquisition, which can be viewed as an instance of the well-known “knowledge acquisition bottleneck”. Based on the authors’ work in conceptual modelling and method engineering, this paper casts methods for knowledge mode
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Sauer, Christopher, Thilo Breitsprecher, Christof Küstner, Benjamin Schleich, and Sandro Wartzack. "SLASSY—An Assistance System for Performing Design for Manufacturing in Sheet-Bulk Metal Forming: Architecture and Self-Learning Aspects." AI 2, no. 3 (2021): 307–29. http://dx.doi.org/10.3390/ai2030019.

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Substantial efforts have been made to integrate manufacturing- and design-relevant knowledge into product development processes. A common approach is to provide the relevant knowledge to the design engineers using a knowledge-based system (KBS) that, in turn, becomes the engineering assistance system. Keeping the knowledge up to date is a critical issue, making knowledge acquisition a bottleneck of developing and maintaining KBS. This article presents a robust metamodel optimization and performance estimation architecture for developing and maintaining a KBS useful for design-for-manufacturing
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Zhao, Guo Zhen, and Wan Li Zuo. "Semi-Supervised Word Sense Disambiguation via Context Weighting." Advanced Materials Research 1049-1050 (October 2014): 1327–38. http://dx.doi.org/10.4028/www.scientific.net/amr.1049-1050.1327.

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Word sense disambiguation as a central research topic in natural language processing can promote the development of many applications such as information retrieval, speech synthesis, machine translation, summarization and question answering. Previous approaches can be grouped into three categories: supervised, unsupervised and knowledge-based. The accuracy of supervised methods is the highest, but they suffer from knowledge acquisition bottleneck. Unsupervised method can avoid knowledge acquisition bottleneck, but its effect is not satisfactory. With the built-up of large-scale knowledge, know
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Lin, Shun-Chieh, Chia-Wen Teng, and Shian-Shyong Tseng. "Capturing Evolutional Knowledge Using Time Interval Tracing." Journal of Advanced Computational Intelligence and Intelligent Informatics 11, no. 4 (2007): 373–80. http://dx.doi.org/10.20965/jaciii.2007.p0373.

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Knowledge acquisition is a critical bottleneck in building a knowledge-based system. Much research and many tools have been developed to acquire domain knowledge with embedded rules that may be ignored in constructing the initial prototype. Due to different backgrounds and dynamic knowledge changing over time, domain knowledge constructed at one time may be degraded at any time thereafter. Here, we propose knowledge acquisition, called enhanced embedded meaning capturing under uncertainty deciding (enhanced EMCUD), which constructs a domain ontology and traces information over time to efficien
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Ren, Yong Chang, Tao Xing, and Ping Zhu. "An Attribute Reduction Algorithms of Expert System Knowledge Acquisition." Applied Mechanics and Materials 48-49 (February 2011): 187–91. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.187.

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Knowledge acquisition is the bottleneck of construction expert system, to provide an accurate inference of knowledge is the key decision-making plan. This article use the rough sets theory, through the rough sets reduction eliminate redundant condition attribute, to achieve the streamlining of the knowledge library. First study the knowledge acquisition, in exposition knowledge hierarchical structure foundation, has given the conceptualization, formal, the knowledge library refinement and so on three knowledge acquisition; and then study attributes reduction algorithms, in the research sets di
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Lv, Zhan Min, Wei Yan, Jun Liang He, and Dao Fang Chang. "Knowledge-Based System for Major-Pieces Lifting Project Using MRM." Applied Mechanics and Materials 170-173 (May 2012): 3260–65. http://dx.doi.org/10.4028/www.scientific.net/amm.170-173.3260.

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Knowledge-based system (KBS) for major-pieces lifting projects can be useful for improving the level of decision-making. And it is important to use the knowledge acquired from domain experts to finish all kinds of projects for lifting major-pieces. Knowledge acquisition plays a critical role in constructing a KBS for major-pieces lifting project, also it is commonly regarded as a major obstacle and bottleneck in the process of designing and implementing a KBS. This paper presents a KBS model based on matrix representation and mapping (MRM) approach to facilitate the effectiveness of knowledge
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Jensen, Isabel Nadine, Roumyana Slabakova, Marit Westergaard, and Björn Lundquist. "The Bottleneck Hypothesis in L2 acquisition: L1 Norwegian learners’ knowledge of syntax and morphology in L2 English." Second Language Research 36, no. 1 (2019): 3–29. http://dx.doi.org/10.1177/0267658318825067.

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The Bottleneck Hypothesis (Slabakova, 2008, 2013) proposes that acquiring properties of the functional morphology is the most challenging part of learning a second language. In the experiment presented here, the predictions of this hypothesis are tested in the second language (L2) English of Norwegian native speakers. Two constructions are investigated that do not match in English and Norwegian: One involving functional morphology, subject–verb (SV) agreement, which is obligatory in the L2 but non-existent in the first language (L1), and one involving syntax, verb-second (V2) word order, which
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Dissertations / Theses on the topic "Knowledge acquisition bottleneck"

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Suraweera, Pramuditha. "Widening the Knowledge Acquisition Bottleneck for Intelligent Tutoring Systems." Thesis, University of Canterbury. Computer Science and Software Engineering, 2007. http://hdl.handle.net/10092/1150.

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Empirical studies have shown that Intelligent Tutoring Systems (ITS) are effective tools for education. However, developing an ITS is a labour-intensive and time-consuming process. A major share of the development effort is devoted to acquiring the domain knowledge that accounts for the intelligence of the system. The goal of this research is to reduce the knowledge acquisition bottleneck and enable domain experts to build the domain model required for an ITS. In pursuit of this goal an authoring system capable of producing a domain model with the assistance of a domain expert was developed. U
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Ballout, Ali. "Apprentissage actif pour la découverte d'axiomes." Electronic Thesis or Diss., Université Côte d'Azur, 2024. http://www.theses.fr/2024COAZ4026.

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Cette thèse aborde le défi de l'évaluation des formules logiques candidates, avec un accent particulier sur les axiomes, en combinant de manière synergique l'apprentissage automatique et le raisonnement symbolique. Cette approche innovante facilite la découverte automatique d'axiomes, principalement dans la phase d'évaluation des axiomes candidats générés. La recherche vise à résoudre le problème de la validation efficace et précise de ces candidats dans le contexte plus large de l'acquisition de connaissances sur le Web sémantique.Reconnaissant l'importance des heuristiques de génération exis
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Suraweera, Pramuditha. "Widening the knowledge acquisition bottleneck for intelligent tutoring systems : a thesis submitted in partial fulfilment of the requirements for the degree of Doctor of Philosophy in the University of Canterbury /." 2006. http://library.canterbury.ac.nz/etd/adt-NZCU20070417.162903.

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Book chapters on the topic "Knowledge acquisition bottleneck"

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Weibel, Robert, Stefan Keller, and Tumasch Reichenbacher. "Overcoming the knowledge acquisition bottleneck in map generalization: The role of interactive systems and computational intelligence." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 1995. http://dx.doi.org/10.1007/3-540-60392-1_10.

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Možina Martin, Guid Matej, Krivec Jana, Sadikov Aleksander, and Bratko Ivan. "Fighting Knowledge Acquisition Bottleneck with Argument Based Machine Learning." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2008. https://doi.org/10.3233/978-1-58603-891-5-234.

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Knowledge elicitation is known to be a difficult task and thus a major bottleneck in building a knowledge base. Machine learning has long ago been proposed as a way to alleviate this problem. Machine learning usually helps the domain expert to uncover some of the more tacit concepts. However, the learned concepts are often hard to understand and hard to extend. A common view is that a combination of a domain expert and machine learning would yield the best results. Recently, argument based machine learning (ABML) has been introduced as a combination of argumentation and machine learning. Throu
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Zolhavarieh Seyedjamal and Parry Dave. "KQA: A Knowledge Quality Assessment Model for Clinical Decision Support Systems." In Studies in Health Technology and Informatics. IOS Press, 2017. https://doi.org/10.3233/978-1-61499-830-3-983.

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Informatics researchers have developed many methods for using computers to utilize knowledge in decision making in the form of clinical decision support systems (CDSSs). These systems can enhance human decision making in the healthcare domain. The knowledge acquisition bottleneck is one of the well-known issues in developing knowledge-based systems such as CDSS. It can be considered as a flow of knowledge from different knowledge sources to the main system. Most existing methods for extracting knowledge from knowledge resources suffer from the lack of a proper mechanism for extracting high-qua
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Mendes, David, Irene Pimenta Rodrigues, and Carlos Fernandes Baeta. "Clinical Practice Ontology Automatic Learning from SOAP Reports." In Healthcare Ethics and Training. IGI Global, 2017. http://dx.doi.org/10.4018/978-1-5225-2237-9.ch028.

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We show how we implemented an end-to-end process to automatically develop a clinical practice knowledge base acquiring from SOAP notes. With our contribution we intend to overcome the “Knowledge Acquisition Bottleneck” problem by jump-starting the knowledge gathering from the most widely available source of clinical information that are natural language reports. We present the different phases of our process to populate automatically a proposed ontology with clinical assertions extracted from daily routine SOAP notes. The enriched ontology becomes a reasoning able knowledge base that depicts a
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Mendes, David, Irene Pimenta Rodrigues, and Carlos Fernandes Baeta. "Clinical Practice Ontology Automatic Learning from SOAP Reports." In Handbook of Research on Trends in the Diagnosis and Treatment of Chronic Conditions. IGI Global, 2016. http://dx.doi.org/10.4018/978-1-4666-8828-5.ch016.

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We show how we implemented an end-to-end process to automatically develop a clinical practice knowledge base acquiring from SOAP notes. With our contribution we intend to overcome the “Knowledge Acquisition Bottleneck” problem by jump-starting the knowledge gathering from the most widely available source of clinical information that are natural language reports. We present the different phases of our process to populate automatically a proposed ontology with clinical assertions extracted from daily routine SOAP notes. The enriched ontology becomes a reasoning able knowledge base that depicts a
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Asai, Masataro, Hiroshi Kajino, Alex Fukunaga, and Christian Muise. "Chapter 2. Symbolic Reasoning in Latent Space: Classical Planning as an Example." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2021. http://dx.doi.org/10.3233/faia210349.

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Symbolic systems require hand-coded symbolic representation as input, resulting in a knowledge acquisition bottleneck. Meanwhile, although deep learning has achieved significant success in many fields, the knowledge is encoded in a subsymbolic representation which is incompatible with symbolic systems. To address the gap between the two fields, one has to solve Symbol Grounding problem: The question of how a machine can generate symbols automatically. We discuss our recent work called Latplan, an unsupervised architecture combining deep learning and classical planning. Given only an unlabeled
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Nirenburg, Sergei. "Lexicon Acquisition for NLP: A Consumer Report." In Computational Approaches to the Lexicon. Oxford University PressOxford, 1994. http://dx.doi.org/10.1093/oso/9780198239796.003.0012.

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Abstract Current natural language processing systems typically operate in a ‘demo’ mode—they sometimes feature sizeable grammars but seldom sizeable lexicons containing information about meaning. This difficulty of going beyond toy systems is one of the main bottlenecks of artificial intelligence in general. Scaling up the dictionaries (and other knowledge bases) of a knowledge-based system is, however, essential for the overall success of the field. There are several ways in which the indispensable massive knowledge acquisition program can in principle be conducted. One can envisage developin
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Garfield, Seth. "Drug Prospects." In Guaraná. University of North Carolina PressChapel Hill, NC, 2022. http://dx.doi.org/10.5149/northcarolina/9781469671277.003.0005.

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Abstract This chapter looks at guaraná’s fleeting popularity in late nineteenth-century Anglo-American pharmacy and therapeutics. It explores Western scientists’ acquisition and dissemination of knowledge of guaraná and the drug’s interface with commercial health care, cultural practices, and epistemologies. Nineteenth-century scientists’ reclassification of guaraná according to the “universal” standards of botany and chemistry transpired within the context of colonial botanizing and Indigenous knowledge erasures. Bavarian Karl von Martius renamed the plant according to the precepts and politi
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Conference papers on the topic "Knowledge acquisition bottleneck"

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Pasini, Tommaso. "The Knowledge Acquisition Bottleneck Problem in Multilingual Word Sense Disambiguation." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/687.

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Word Sense Disambiguation (WSD) is the task of identifying the meaning of a word in a given context. It lies at the base of Natural Language Processing as it provides semantic information for words. In the last decade, great strides have been made in this field and much effort has been devoted to mitigate the knowledge acquisition bottleneck problem, i.e., the problem of semantically annotating texts at a large scale and in different languages. This issue is ubiquitous in WSD as it hinders the creation of both multilingual knowledge bases and manually-curated training sets. In this work, we fi
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Barba, Edoardo, Luigi Procopio, Niccolò Campolungo, Tommaso Pasini, and Roberto Navigli. "MuLaN: Multilingual Label propagatioN for Word Sense Disambiguation." In Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/531.

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The knowledge acquisition bottleneck strongly affects the creation of multilingual sense-annotated data, hence limiting the power of supervised systems when applied to multilingual Word Sense Disambiguation. In this paper, we propose a semi-supervised approach based upon a novel label propagation scheme, which, by jointly leveraging contextualized word embeddings and the multilingual information enclosed in a knowledge base, projects sense labels from a high-resource language, i.e., English, to lower-resourced ones. Backed by several experiments, we provide empirical evidence that our automati
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Chen, Xiyang, Kewei Zhang, and Yucheng Peng. "Research on Multi Diagnosis Methods for Hydro-Generator Sets." In ASME 7th Biennial Conference on Engineering Systems Design and Analysis. ASMEDC, 2004. http://dx.doi.org/10.1115/esda2004-58163.

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Hydro-Generator Sets Condition Monitoring and Predictive Maintenance activity has increased dramatically over the past few years. The Fault Diagnostic System is the key technique for the Predictive Maintenance. This paper discusses the Fault Diagnostic System function structure, system design and inferential strategy of Multi-Fault Diagnostic System of the Hydro-Generator Sets. The developing of the power system to big unit requires the higher automation and reliability of the power station. Electrical power systems are constantly exposed to faults and disturbances. This may lead to damage or
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Stensrud, Rune, Sigmund Valaker, and Olav Rune Nummedal. "Exploring Human autonomy teaming methods in challenging environments: the case of uncrewed system (UxS) solutions – challenges and opportunities (with AI)." In AHFE 2023 Hawaii Edition. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1004307.

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Current uncrewed system (UxS) solutions tend to operate with tightly coupled Command and Control systems, making it difficult to contribute to operating as an integrated force. The case presented in this article is used to reason at the conceptual level about the different requirements and approaches for a future Norwegian UxS Integrated C2 system in order to inform the national development of an UxS Integrated C2 Reference Architecture. This is one in a series of papers that will develop a mission engineering approach and represents functional analysis needed for future acquisition of Norwegi
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