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Artykuły w czasopismach na temat „Knowledge acquisition bottleneck”

Autor: Grafiati
Data publikacji: 31 sierpnia 2024
Data aktualizacji: 31 lipca 2025

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1

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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KODRATOFF, Y., and S. MOSCATELLI. "MACHINE LEARNING FOR OBJECT RECOGNITION AND SCENE ANALYSIS." International Journal of Pattern Recognition and Artificial Intelligence 08, no. 01 (1994): 259–304. http://dx.doi.org/10.1142/s0218001494000139.

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Learning is a critical research field for autonomous computer vision systems. It can bring solutions to the knowledge acquisition bottleneck of image understanding systems. Recent developments of machine learning for computer vision are reported in this paper. We describe several different approaches for learning at different levels of the image understanding process, including learning 2-D shape models, learning strategic knowledge for optimizing model matching, learning for adaptive target recognition systems, knowledge acquisition of constraint rules for labelling and automatic parameter op
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Yang, Jie, Chenzhou Ye, and Xiaoli Zhang. "An Expert System Shell for Fault Diagnosis." Robotica 19, no. 6 (2001): 669–74. http://dx.doi.org/10.1017/s0263574701003460.

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Traditional expert systems for fault diagnosis have a bottleneck in knowledge acquisition, and have limitations in knowledge representation and reasoning. A new expert system shell for fault diagnosis is presented in this paper to develop multiple knowledge models (object model, rules, neural network, case-base and diagnose models) hierarchically based on multiple knowledge. The structure of the expert system shell and the knowledge representation of multiple models are described. Diagnostic algorithms are presented for automatic modeling and hierarchical reasoning. It will be shown that the e
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Tao, Gui Ming. "Research on Fault Knowledge Acquisition Base of Circuit Simulation." Advanced Materials Research 490-495 (March 2012): 1763–66. http://dx.doi.org/10.4028/www.scientific.net/amr.490-495.1763.

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To resolve bottle-net problem of knowledge acquisition of fault diagnoses expert system. This paper make use of circuit simulation software Multisim2001module modeling and simulating, acquiring fault data of electric control circuit of missile launching vehicle, acquiring correspondence relation of function-fault, establishing knowledge base of intelligent diagnostic expert system, affording a new thought to resolve knowledge acquisition of expert system. The fault diagnosis expert system is based on the knowledge base, but many fault diagnosis expert systems face the same problem: the knowled
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GALEA, MICHELLE, QIANG SHEN, and JOHN LEVINE. "Evolutionary approaches to fuzzy modelling for classification." Knowledge Engineering Review 19, no. 1 (2004): 27–59. http://dx.doi.org/10.1017/s0269888904000189.

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An overview of the application of evolutionary computation to fuzzy knowledge discovery is presented. This is set in one of two contexts: overcoming the knowledge acquisition bottleneck in the development of intelligent reasoning systems, and in the data mining of databases where the aim is the discovery of new knowledge. The different strategies utilizing evolutionary algorithms for knowledge acquisition are abstracted from the work reviewed. The simplest strategy runs an evolutionary algorithm once, while the iterative rule learning approach runs several evolutionary algorithms in succession
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15

Усамов, И. Р., Б. Ж. Юхигов, and З. А. Магазиева. "EXPERT SYSTEMS SHELL: AN EFFECTIVE KNOWLEDGE ACQUISITION MODEL." Вестник ГГНТУ. Гуманитарные и социально-экономические науки, no. 2(28) (August 26, 2022): 80–90. http://dx.doi.org/10.34708/gstou.2022.61.19.010.

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Экспертная система - это интеллектуальная компьютерная программа, которая использует знания и процедуры вывода для решения проблем, которые считаются достаточно сложными, чтобы для их решения хватило человеческого опыта. С момента внедрения первых экспертных систем в начале 1970-х годов и последовавших за этим успехов в сочетании с преимуществами, которые человечество получило от этих ранних экспертных систем и их преемников, можно было бы ожидать, что пять десятилетий спустя произойдет бум использования экспертных систем для выполнения более специализированных задач в конкретных областях прим
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Dang, Yinglong, Xiaoguang Gao, and Zidong Wang. "Stochastic Fractal Search for Bayesian Network Structure Learning Under Soft/Hard Constraints." Fractal and Fractional 9, no. 6 (2025): 394. https://doi.org/10.3390/fractalfract9060394.

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A Bayesian network (BN) is an uncertainty processing model that simulates human cognitive thinking on the basis of probability theory and graph theory. Its network topology is a directed acyclic graph (DAG) that can be manually constructed through expert knowledge or automatically generated through data learning. However, the acquisition of expert knowledge faces problems such as excessively high labor costs, limited expert experience, and the inability to solve large-scale and highly complex DAGs. Moreover, the current data learning methods also face the problems of low computational efficien
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Lin, Yun Feng, and Xiao Ping Hu. "The Application of Data Mining Technology in Mechanical Fault Diagnosis." Key Engineering Materials 460-461 (January 2011): 821–26. http://dx.doi.org/10.4028/www.scientific.net/kem.460-461.821.

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This article first introduced the survey of mechanical fault diagnosis technology development and the data mining technology theory. Then its application situation at present and the main questions that exist are elaborated. Its development trend is analyzed. The application feasibility of using data mining technology in mechanical fault diagnosis is discussed. Next, the naissance, the development and the future development tendency of data mining technology are introduced. The four algorithms are analyzed and the framework is built too. Intelligent Diagnosis is a major development direction o
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Musen, Mark A., and Johan van der Lei. "Knowledge Engineering for Clinical Consultation Programs: Modeling the Application Area." Methods of Information in Medicine 28, no. 01 (1989): 28–35. http://dx.doi.org/10.1055/s-0038-1635543.

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Abstract:Developers of computer-based decision-support tools frequently adopt either pattern recognition or artificial intelligence techniques as the basis for their programs. Because these developers often choose to accentuate the differences between these alternative approaches, the more fundamental similarities are frequently overlooked. The principal challenge in the creation of any clinical consultation program - regardless of the methodology that is used - lies in creating a computational model of the application domain. The difficulty in generating such a model manifests itself in sympt
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Ming-qian, Wang. "RESEARCH ON SHIP ENGINE ROOM MONITORING AND FAULT DIAGNOSIS SYSTEM BASED ON LABVIEW." EPH - International Journal of Science And Engineering 7, no. 3 (2021): 1–11. http://dx.doi.org/10.53555/ephijse.v7i3.186.

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The structure of marine engine room system is complex, with many fault sources and abundant symptom parameters. There is no simple correspondence between faults and symptoms, but they are interrelated and intricate. The existing fault diagnosis of ship engine room is mostly based on expert system, but the bottleneck of knowledge acquisition, lack of learning ability and the complexity and efficiency of the expert system are restricting its further development. In order to overcome the above shortcomings of expert system, the support vector machine (SVM) is introduced into the expert system, an
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Welty, Chris, Lora Aroyo, Flip Korn, Sara M. McCarthy, and Shubin Zhao. "Rapid Instance-Level Knowledge Acquisition for Google Maps from Class-Level Common Sense." Proceedings of the AAAI Conference on Human Computation and Crowdsourcing 9 (October 4, 2021): 143–54. http://dx.doi.org/10.1609/hcomp.v9i1.18947.

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Successful knowledge graphs (KGs) solved the historical knowledge acquisition bottleneck by supplanting an expert focus with a simple, crowd-friendly one: KG nodes represent popular people, places, organizations, etc., and the graph arcs represent common sense relations like affiliations, locations, etc. Techniques for more general, categorical, KG curation do not seem to have made the same transition: the KG research community is still largely focused on methods that belie the common-sense characteristics of successful KGs. In this paper, we propose a simple approach to acquiring and reasonin
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Kota, Sridhar, Arthur G. Erdman, and Donald R. Riley. "Development of Knowledge Base for Designing Linkage-Type Dwell Mechanisms: Part 2—Application." Journal of Mechanisms, Transmissions, and Automation in Design 109, no. 3 (1987): 316–21. http://dx.doi.org/10.1115/1.3258796.

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Knowledge acquisition is a big bottleneck in any expert system development. Several “rules-of-thumb” are developed for designing linkage-type dwell mechanisms. These rules of thumb are based on path curvature theory (Part 1 of this paper) and systematic synthesis, analysis and classification of straight-line, circular-arc and symmetrical coupler-curve generating linkages. The methods of representing the domain-specific knowledge in an expert system are discussed here. “Frames” for structural representation of knowledge and “production rules” to control the reasoning during the design process a
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Xiao, Lin, Jiyan Wu, Xiangwang Hu, Jian Sun, and Ye Tian. "Collaborate or Compete? Time-Varying Incentives versus Tolling in Parallel Bottleneck." Journal of Advanced Transportation 2023 (May 12, 2023): 1–22. http://dx.doi.org/10.1155/2023/6402531.

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Incentive-based traffic demand management (IBTDM) schemes redistribute traffic demand across space and time. The relationship between IBTDM and traditional tolling programs impacts financial sustainability and decision making of both programs. This study aims to examine if an IBTDM and a tolling program can coexist and should collaborate or compete to establish a financially sustainable mobility ecosystem. We investigate a duopoly case with an IBTDM and a tolling program in a parallel bottleneck model with fixed demand. It is assumed that the IBTDM program has a user acquisition cost and is co
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Martinez, D., O. Lopez de Lacalle, and E. Agirre. "On the Use of Automatically Acquired Examples for All-Nouns Word Sense Disambiguation." Journal of Artificial Intelligence Research 33 (September 25, 2008): 79–107. http://dx.doi.org/10.1613/jair.2395.

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This article focuses on Word Sense Disambiguation (WSD), which is a Natural Language Processing task that is thought to be important for many Language Technology applications, such as Information Retrieval, Information Extraction, or Machine Translation. One of the main issues preventing the deployment of WSD technology is the lack of training examples for Machine Learning systems, also known as the Knowledge Acquisition Bottleneck. A method which has been shown to work for small samples of words is the automatic acquisition of examples. We have previously shown that one of the most promising
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Asai, Masataro, Hiroshi Kajino, Alex Fukunaga, and Christian Muise. "Classical Planning in Deep Latent Space." Journal of Artificial Intelligence Research 74 (August 9, 2022): 1599–686. http://dx.doi.org/10.1613/jair.1.13768.

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Current domain-independent, classical planners require symbolic models of the problem domain and instance 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 such as planners. We propose Latplan, an unsupervised architecture combining deep learning and classical planning. Given only an unlabeled set of image pairs showing a subset of transitions allowed in the environment (training inputs), Latplan learns
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LENTING, JACQUES H. J., and PETER J. BRASPENNING. "THE FRAME PROBLEM FROM AN ENGINEERING PERSPECTIVE." International Journal of Software Engineering and Knowledge Engineering 03, no. 02 (1993): 257–65. http://dx.doi.org/10.1142/s0218194093000124.

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Since its introduction in 1969, the phrase “frame problem” has been attributed various interpretations. Most researchers in the field of Artificial Intelligence define the frame problem as the problem of finding an effective representation for reasoning about change. Logicians use the phrase to refer to a much less general technical problem within logic whereas philosophers tend to interpret the phrase as the more general problem of determining (ir)relevance. All in all, this discrepancy has led to considerable confusion about the meaning of the phrase. We contend that most of this confusion c
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Taylor, Daniel J., Jessica R. Dietch, Kristi Pruiksma, et al. "Developing and Testing a Web-Based Provider Training for Cognitive Behavioral Therapy of Insomnia." Military Medicine 186, Supplement_1 (2021): 230–38. http://dx.doi.org/10.1093/milmed/usaa359.

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ABSTRACT Introduction Chronic insomnia is a common and debilitating disease that increases risk for significant morbidity and workplace difficulties. Cognitive behavioral therapy for insomnia (CBT-I) is the first-line treatment, but there is a critical lack of behavioral health providers trained in CBT-I because, in part, of a bottleneck in training availability and costs. The current project developed and evaluated a web-based provider training course for CBT-I: CBTIweb.org. Materials and Methods Subject matter experts developed the content for CBTIweb.org. Then, trainees completed alpha test
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Bolshina, Angelina Sergeevna, and Natalia Valentinovna Loukachevitch. "Weakly Supervised Word Sense Disambiguation Using Automatically Labelled Collections." Proceedings of the Institute for System Programming of the RAS 33, no. 6 (2021): 193–204. http://dx.doi.org/10.15514/ispras-2021-33(6)-13.

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State-of-the-art supervised word sense disambiguation models require large sense-tagged training sets. However, many low-resource languages, including Russian, lack such a large amount of data. To cope with the knowledge acquisition bottleneck in Russian, we first utilized the method based on the concept of monosemous relatives to automatically generate a labelled training collection. We then introduce three weakly supervised models trained on this synthetic data. Our work builds upon the bootstrapping approach: relying on this seed of tagged instances, the ensemble of the classifiers is used
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Asai, Masataro, and Hiroshi Kajino. "Towards Stable Symbol Grounding with Zero-Suppressed State AutoEncoder." Proceedings of the International Conference on Automated Planning and Scheduling 29 (May 25, 2021): 592–600. http://dx.doi.org/10.1609/icaps.v29i1.3526.

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While classical planning has been an active branch of AI, its applicability is limited to the tasks precisely modeled by humans. Fully automated high-level agents should be instead able to find a symbolic representation of an unknown environment without supervision, otherwise it exhibits the knowledge acquisition bottleneck. Meanwhile, Latplan (Asai and Fukunaga 2018) partially resolves the bottleneck with a neural network called State AutoEncoder (SAE). SAE obtains the propositional representation of the image-based puzzle domains with unsupervised learning, generates a state space and perfor
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Weng, Cheng-Hsiung. "Knowledge discovery of digital library subscription by RFC itemsets." Electronic Library 34, no. 5 (2016): 772–88. http://dx.doi.org/10.1108/el-06-2015-0086.

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Purpose The paper aims to understand the book subscription characteristics of the students at each college and help the library administrators to conduct efficient library management plans for books in the library. Unlike the traditional association rule mining (ARM) techniques which mine patterns from a single data set, this paper proposes a model, recency-frequency-college (RFC) model, to analyse book subscription characteristics of library users and then discovers interesting association rules from equivalence-class RFC segments. Design/methodology/approach A framework which integrates the
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Lefever, Els, and Véronique Hoste. "Parallel corpora make sense." International Journal of Corpus Linguistics 19, no. 3 (2014): 333–67. http://dx.doi.org/10.1075/ijcl.19.3.02lef.

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We present a multilingual approach to Word Sense Disambiguation (WSD), which automatically assigns the contextually appropriate sense to a given word. Instead of using a predefined monolingual sense-inventory, we use a language-independent framework by deriving the senses of a given word from word alignments on a multilingual parallel corpus, which we made available for corpus linguistics research. We built five WSD systems with English as the input language and translations in five supported languages (viz. French, Dutch, Italian, Spanish and German) as senses. The systems incorporate both bi
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Taylor, D., B. Bunnell, C. Calhoun, et al. "1186 Developing And Testing A Web-based Provider Training For Cognitive Behavioral Therapy Of Insomnia." Sleep 43, Supplement_1 (2020): A453. http://dx.doi.org/10.1093/sleep/zsaa056.1180.

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Abstract Introduction Chronic insomnia is a common, debilitating disorder and a risk factor for significant medical morbidity, mental health problems, and workplace difficulties. Cognitive behavioral therapy for insomnia (CBT-I) is the gold standard treatment for insomnia. However, few providers are trained in CBT-I, in part due to a bottleneck in training availability and the time and cost associated with current training platforms. To address this training deficit, our team developed and evaluated CBTIweb.org, a web-based provider training course for CBT-I. Methods Feedback from alpha- and b
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Aboras, Afnan. "The Acquisition of Definiteness and Specificity in English: A Case Study with Saudi-Arabic Learners of English Using an Online Task." English Language and Literature Studies 10, no. 1 (2020): 13. http://dx.doi.org/10.5539/ells.v10n1p13.

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Definiteness with Arabic learners has been explored by many researchers such as Jaensch and Sarko (2009) and Sarko (2009). The majority of previous studies have used an offline task and focused on identifying the types of errors which learners were committing. Conversely, the present study will use an online reaction time task to investigate the learners’ accuracy in judging [±definite and ±specific] in a series of sentences. The aim of the study is to ascertain the accuracy of participants in judging grammatical and ungrammatical sentences in terms of definiten
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Khan, Usman Ali. "Synthesizing a three Layer Architectural Framework for Adaptive Intelligent User Interfaces for the Disabled Community." International Journal of Automation and Smart Technology 14, no. 1 (2024): 11. http://dx.doi.org/10.5875/s2rfmt87.

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Knowledge acquisition has been a bottleneck in the design for efficient User Interfaces for Disabled Community. The best suited interfaces have been oriented towards adaptability that is the User Interface needs to adapt and configure itself according to the needs and likes of the user. Such user interfaces can arouse interest in the mind of the disabled and motivate them to become an asset to the nation, and use their intellect to contribute to the society. This study pioneers an innovative approach, aiming to develop User Interfaces (UIs) for the Disabled Community. The research introduces a
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Zhang, Yongxiang, and Raymond Y. K. Lau. "Uncertainty Detection: A Multi-View Decision Boundary Approach Against Healthcare Unknown Intents." Applied Sciences 15, no. 13 (2025): 7114. https://doi.org/10.3390/app15137114.

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Chatbots, an automatic dialogue system empowered by deep learning-oriented AI technology, have gained increasing attention in healthcare e-services for their ability to provide medical information around the clock. A formidable challenge is that chatbot dialogue systems have difficulty handling queries with unknown intents due to the technical bottleneck and restricted user-intent answering scope. Furthermore, the wide variation in a user’s consultation needs and levels of medical knowledge further complicates the chatbot’s ability to understand natural human language. Failure to deal with unk
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Feinerer, Ingo. "Efficient large-scale configuration via integer linear programming." Artificial Intelligence for Engineering Design, Analysis and Manufacturing 27, no. 1 (2013): 37–49. http://dx.doi.org/10.1017/s0890060412000376.

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AbstractConfiguration of large-scale applications in an engineering context requires a modeling environment that allows the design engineer to draft the configuration problem in a natural way and efficient methods that can process the modeled setting and scale with the number of components. Existing configuration methods in artificial intelligence typically perform quite well in certain subareas but are hard to use for general-purpose modeling without mathematical or logics background (the so-called knowledge acquisition bottleneck) and/or have scalability issues. As a remedy to this important
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CRAWFORD, STUART L., and STEVEN K. SOUDERS. "A COMPARISON OF TWO NEW TECHNIQUES FOR CONCEPTUAL CLUSTERING." International Journal of Pattern Recognition and Artificial Intelligence 04, no. 03 (1990): 409–28. http://dx.doi.org/10.1142/s0218001490000253.

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Clustering, pattern recognition, and classification are important components of many artificial intelligence systems, especially those designed to classify new observations. Often, one has access to a history of old observations that have been previously classified and, under these circumstances, the old data may be used as a training set from which one may obtain rules for the subsequent classification of new data. The techniques used to obtain these rules may be traditional statistical methods or modern computer-intensive techniques. Sometimes, however, the history of old observations has no
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Reif, Kathryn E., Guy H. Palmer, Massaro W. Ueti, et al. "Dermacentor andersoni Transmission of Francisella tularensis subsp. novicida Reflects Bacterial Colonization, Dissemination, and Replication Coordinated with Tick Feeding." Infection and Immunity 79, no. 12 (2011): 4941–46. http://dx.doi.org/10.1128/iai.05676-11.

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ABSTRACTTicks serve as biological vectors for a wide variety of bacterial pathogens which must be able to efficiently colonize specific tick tissues prior to transmission. The bacterial determinants of tick colonization are largely unknown, a knowledge gap attributed in large part to the paucity of tools to genetically manipulate these pathogens. In this study, we demonstrated thatFrancisella tularensissubsp.novicida, for which a complete two-allele transposon mutant library has been constructed, initially infects the midguts of 100% of acquisition-fedDermacentor andersoninymphs, with stable c
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Shan, Xin. "Multisensor Cross-Media Data Mining Method Assisted by Expert System." Journal of Sensors 2023 (January 31, 2023): 1–12. http://dx.doi.org/10.1155/2023/3303790.

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The information generated by the multifaceted and multilevel processing of the data of multiple sensors is more meaningful than the information obtained by a single sensor and provides accurate information and decision-making basis for various application systems. How to apply data mining theory to the multisensor cross-media field has become a research hotspot. Through the analysis of multisensor cross-media data, it is of great significance to dig out the important rules, information, or knowledge hidden in it and use it for cross-media retrieval engine. The rule acquisition is the “bottlene
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McNeese, Michael D., and Brian S. Zaff. "Knowledge as Design: A Methodology for Overcoming Knowledge Acquisition Bottlenecks in Intelligent Interface Design." Proceedings of the Human Factors Society Annual Meeting 35, no. 17 (1991): 1181–85. http://dx.doi.org/10.1177/154193129103501701.

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Matricano, Diego, Elena Candelo, Mario Sorrentino, and Aurora Martínez-Martínez. "Absorbing in-bound knowledge within open innovation processes. The case of Fiat Chrysler Automobiles." Journal of Knowledge Management 23, no. 4 (2019): 786–807. http://dx.doi.org/10.1108/jkm-10-2018-0625.

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Purpose The purpose of this paper is to investigate the way companies involved in Open Innovation Processes (OIPs) routinize the procedure through which they can absorb in-bound knowledge, i.e. knowledge that comes from the outside and, in particular, from the crowd. In-bound knowledge passes through the phases of acquisition, assimilation, transformation and exploitation. Thus, companies need to define mechanisms and paths – related to their potential and realized absorptive capacity –to manage and exploit it. Design/methodology/approach The present paper is based on a longitudinal case study
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Hao, L. N., Wen Lin Chen, X. F. Zhang, and Wan Shan Wang. "Rough Set Data Analysis System and Its Applications in Machinery Fault Diagnosis." Materials Science Forum 471-472 (December 2004): 850–54. http://dx.doi.org/10.4028/www.scientific.net/msf.471-472.850.

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The characteristics of fault diagnosis are as follows. First, features extraction is the key of improving diagnosis efficiency and correct rate. Secondly, fault diagnosis method based on rule reasoning has a wide application, but rule acquisition is one of the bottlenecks. Thirdly, rule modification is a key question of solving the real-time rule acquisition in the dynamic environments, and a primary question of knowledge base modification of expert system, etc. In this paper, Rough Set Theory (RST) was used to solve the key problems of machinery fault diagnosis, and a Rough Set Data Analysis
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Yau'Mee Hayati Hj Mohamed Yusof, Awanis Romli, Ruzaini Abdullah Arshah, and Azira Abdul Aziz. "A Sensitivity Analysis for Roles Selection in Hybrid Multi-Criteria Decision Making." Journal of Advanced Research in Applied Sciences and Engineering Technology 31, no. 1 (2023): 210–25. http://dx.doi.org/10.37934/araset.31.1.210225.

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The process of retaining leadership succession at higher education institutions (HEI) is crucial since it has entailed the process of selecting the ideal candidate. The goal is to guide universities toward maintaining organizations' excellence in their academic leadership and management (ALM) positions. Due to the lack of established standards for assessing the competency of possible successors at their home institutions, many ALM of Malaysia HEIs is difficult to identify the proper replacement for their posts. This study aims to propose a multi-criteria tacit knowledge acquisition framework (
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Stelitano, Giovanni, Mario Cocorullo, Matteo Mori, Stefania Villa, Fiorella Meneghetti, and Laurent Roberto Chiarelli. "Iron Acquisition and Metabolism as a Promising Target for Antimicrobials (Bottlenecks and Opportunities): Where Do We Stand?" International Journal of Molecular Sciences 24, no. 7 (2023): 6181. http://dx.doi.org/10.3390/ijms24076181.

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The emergence of multidrug-resistant (MDR) and extensively drug-resistant (XDR) infections is one of the most crucial challenges currently faced by the scientific community. Developments in the fundamental understanding of their underlying mechanisms may open new perspectives in drug discovery. In this review, we conducted a systematic literature search in PubMed, Web of Science, and Scopus, to collect information on innovative strategies to hinder iron acquisition in bacteria. In detail, we discussed the most interesting targets from iron uptake and metabolism pathways, and examined the main
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Carnevali, L., E. Ippoliti, F. Lanfranchi, S. Menconero, M. Russo, and V. Russo. "CLOSE-RANGE MINI-UAVS PHOTOGRAMMETRY FOR ARCHITECTURE SURVEY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2 (May 30, 2018): 217–24. http://dx.doi.org/10.5194/isprs-archives-xlii-2-217-2018.

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The survey of historical façades contains several bottlenecks, mainly related to the geometrical structure, the decorative framework, the presence of natural or artificial obstacles, the environment limitations. Urban context presents additional restrictions, binding by ground acquisition activity and leading to building data loss. The integration of TLS and close-range photogrammetry allows to go over such stuff, not overcoming the shadows effect due to the ground point of view. In the last year the massive use of UAVs in survey activity has permitted to enlarge survey capabilities, reaching
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Zhu, Jiahe. "The Psychological Mechanism of Acquiring English as a Second Language." Advances in Education, Humanities and Social Science Research 12, no. 1 (2024): 753. https://doi.org/10.56028/aehssr.12.1.753.2024.

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Language is not only the fundamental way of human communication, but also a key tool for promoting social progress and individual cognitive development. In a diverse global environment, the ability to master a second language is particularly important. Among them, as an international lingua franca, the acquisition process and effects of English have become a research hotspot in the interdisciplinary fields of linguistics, education, and even computer science. This article delves into the psychological mechanisms underlying the acquisition of English as a second language, including multiple dim
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Tarcz, Sebastian. "Going down the rabbit hole: insight into the future of Paramecium (Ciliophora, Protista) biodiversity surveys." Folia Biologica 72, no. 4 (2024): 130–42. https://doi.org/10.3409/fb_72-4.13.

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Paramecium, a research subject in many areas of life sciences, appeared to be a ciliate genus with a well known biodiversity structure. However, the understanding of its biological diversity has been evolving rapidly in recent years, driven by the discovery of new taxa and an expanded knowledge of the distribution of known species. Most future insights into Paramecium biodiversity are expected to come from molecular data, particularly through eDNA sampling. As one of the most recognisable microeukaryotes, commonly found in freshwater ecosystems, and with over a century of biodiversity research
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Shao, Jianming, Yong Li, Guoping Zhang, Shunkai Sun, Qi Xu, and Yingxiao Chi. "Research on Equipment Management Decision Model based on Semantic Analysis." Highlights in Science, Engineering and Technology 15 (November 26, 2022): 22–27. http://dx.doi.org/10.54097/hset.v15i.2198.

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In recent years, the industrial automation of cigarette enterprises has made great progress, and the underlying data acquisition, centralized control and condition monitoring systems have been established. The management has also established a large number of application systems. There are a large number of equipment data resources in these industrial automation systems and application systems, but incremental data value mining is difficult to really solve the problem. The exploration of big data and machine learning has gradually encountered bottlenecks and ceilings, Lack of integration of do
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Gong, Liheng, Xiao Zhang, and Ling Li. "An Artificial Intelligence Fusion Model for Cardiac Emergency Decision Making: Application and Robustness Analysis." JMIR Medical Informatics 8, no. 7 (2020): e19428. http://dx.doi.org/10.2196/19428.

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Background During cardiac emergency medical treatment, reducing the incidence of avoidable adverse events, ensuring the safety of patients, and generally improving the quality and efficiency of medical treatment have been important research topics in theoretical and practical circles. Objective This paper examines the robustness of the decision-making reasoning process from the overall perspective of the cardiac emergency medical system. Methods The principle of robustness was introduced into our study on the quality and efficiency of cardiac emergency decision making. We propose the concept o
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Siganul, Aimie Peace, and Surya Dewi Puspitasari. "Challenges and Opportunities in Implementing Green Building Materials in Malaysia." Civil and Sustainable Urban Engineering 5, no. 1 (2025): 69–87. https://doi.org/10.53623/csue.v5i1.689.

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Sustainable construction is essential for minimizing greenhouse gas emissions, reducing waste, and promoting cost efficiency. However, Malaysia faces persistent challenges in environmental management, development approval procedures, and the adoption of green technologies. While various studies have explored individual aspects of sustainability in construction, there remains a lack of comprehensive reviews that critically assess how regulatory frameworks, approval processes, and green technologies intersect to influence sustainable construction outcomes in the Malaysian context. This review ad
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Li, Jing Hua, Ying Hui Wang, Zong You Li, et al. "Exploration of Intelligent Development of Medical Heritage." Advances in Science and Technology 105 (April 2021): 272–81. http://dx.doi.org/10.4028/www.scientific.net/ast.105.272.

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With the rapid development of science and technology, more and more new methods and technologies have been added to the traditional Chinese Medicine Inheritance model, which makes the process of inheritance of famous doctors have more means, and the results of inheritance are more objective, rigorous and intelligent. In the process of inheriting the informationization of famous doctors, there are some bottlenecks, such as data acquisition difficulties, data processing difficulties, algorithm application difficulties, analysis and summary difficulties. Integration of artificial intelligence wit
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