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Construction of consultation systems on descriptive knowledge

SOFT COMPUTING 2004年第10期8卷 676-680页

作者： Watada, J Waseda Univ Grad Sch Informat Prod & Syst Kitakyushu Fukuoka 8080135 Japan

This paper proposes the method to design consultation systems on descriptive knowledge such as various kinds of regulations, manual, or specifications of instruments and machinery. In the method the semantic rule for the linguistic variable is employed for handling knowledge levels of users' who use the consultation system. The proper range and depth of the required knowledge is effectively elicited on the base of linguistic variables. Furthermore, a global search is effectively performed using fuzzy relations and logged data about the subject with which the user have concerned, even if the retrieval indices do not work. In this paper we exemplify the design method to build one consultation system on the descriptions of Japanese Industrial Standard (JIS).

关键词： descriptive knowledge consultation system knowledge depth

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Conveying Procedural and descriptive knowledge with Augmented Reality 22

Conveying Procedural and Descriptive Knowledge with Augmente...

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15th ACM International Conference on Pervasive Technologies Related to Assistive Environments (PETRA)

作者： Clemens, Hoffmann Sebastian, Buettner Michael, Prilla Volkswagen AG Wolfsburg Germany Tech Univ Clausthal Clausthal Zellerfeld Germany

ISBN: (纸本)9781450396318

Repairing or maintaining technical systems requires procedural knowledge. When dealing with complex problems, solid descriptive knowledge is also necessary to understand unexpected system states. Consequently, service technicians are taught both descriptive knowledge on product technology as well as procedural knowledge;the first in a theoretical way, the second typically in practical trainings. In the past, augmented reality (AR) training has been proposed for both aspects individually. Here we investigate initial AR training for joint theoretical and practical training. In an experiment under field conditions, this paper compares an initial AR training to conventional personal training for previously unknown repair and maintenance tasks. Our results show that the initial AR training resulted in similar outcomes for short-term and long-term memory of descriptive knowledge compared to the conventional training. Looking at the practical training part, AR outperforms conventional training regarding completion time, repair, and process quality. The results show that AR can provide an alternative to conventional training for unknown repair and maintenance tasks and thus can save financial resources, such as personnel costs (trainer) and costs for physical systems.

关键词： Augmented Reality Head-mounted Display Procedural knowledge descriptive knowledge Training Empirical Study Experiment

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Leveraging Machine-Executable descriptive knowledge in Design Science Research - The Case of Designing Socially-Adaptive Chatbots 14th

Leveraging Machine-Executable Descriptive Knowledge in Desig...

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14th International Conference on Designing for a Digital and Globalized World (DESRIST)

作者： Feine, Jasper Morana, Stefan Maedche, Alexander Karlsruhe Inst Technol KIT Inst Informat Syst & Mkt IISM Karlsruhe Germany

ISBN: (纸本)9783030195038;9783030195045

In Design Science Research (DSR) it is important to build on descriptive (Omega) and prescriptive (Lambda) state-of-the-art knowledge in order to provide a solid grounding. However, existing knowledge is typically made available via scientific publications. This leads to two challenges: first, scholars have to manually extract relevant knowledge pieces from the data-wise unstructured textual nature of scientific publications. Second, different research results can interact and exclude each other, which makes an aggregation, combination, and application of extracted knowledge pieces quite complex. In this paper, we present how we addressed both issues in a DSR project that focuses on the design of socially-adaptive chatbots. Therefore, we outline a twostep approach to transform phenomena and relationships described in the Omega-knowledge base in a machine-executable form using ontologies and a knowledge base. Following this new approach, we can design a system that is able to aggregate and combine existing Omega-knowledge in the field of chatbots. Hence, our work contributes to DSR methodology by suggesting a new approach for theory-guided DSR projects that facilitates the application and sharing of state-of-the-art Omega-knowledge.

关键词： Design science research descriptive knowledge Prescriptive knowledge Ontology Chatbot Conversational agent

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Enhancing RDF Verbalization with descriptive and Relational knowledge

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ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING 2023年第6期22卷 1-18页

作者： Zhang, Fan Zhang, Meishan Liu, Shuang Sun, Yueheng Duan, Nan Tianjin Univ 92 Weijin Rd Tianjin Peoples R China Harbin Inst Technol Shenzhen HIT Campus Univ Town Shenzhen Shenzhen Peoples R China Tianjin Univ 135 Yaguan RdHaihe Educ Pk Tianjin Peoples R China Microsoft Res Asia Tower 25 Danling St Beijing Peoples R China

RDF verbalization has received increasing interest, which aims to generate a natural language description of the knowledge base. Sequence-to-sequence models based on Transformer are able to obtain strong performance equipped with pre-trained language models such as BART and T5. However, in spite of the general performance gain introduced by the pre-trained models, the performance of the task is still limited by the small scale of the training dataset. To address the problem, we propose two orthogonal strategies to enhance the representation learning of RDF triples. Concretely, two types of knowledge are introduced, i.e., descriptive knowledge and relational knowledge, respectively. The descriptive knowledge indicates the semantic information of self definition, and the relational knowledge indicates the semantic information learned from the structural context. We further combine the descriptive and relational knowledge together to enhance the representation learning. Experimental results on the WebNLG and SemEval-2010 datasets show that the two types of knowledge can both enhance the model performance, and their combination is able to obtain further improvements in most cases, providing new state-of-the-art results.

关键词： RDF Verbalization descriptive knowledge Relational knowledge Pretrained Language Models

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Spanish Preservice Primary School Teachers' Understanding of the Tides Phenomenon

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INTERNATIONAL JOURNAL OF SCIENCE AND MATHEMATICS EDUCATION 2022年第7期20卷 1361-1386页

作者： Armario, Maria Maria Oliva, Jose Jimenez-Tenorio, Natalia Univ Cadiz Dept Educ Sci Educ Cadiz Spain

In this study, we analyzed the descriptive knowledge and mental models of the phenomenon of tides manifested by 111 preservice primary teachers. The instrument employed is an open-ended questionnaire, analyzed by means of an approach that explores the descriptions, explanations, and predictions in respect of this phenomenon by our subjects. First, we made a descriptive study of the kinds of ideas applied across different dimensions of analysis, and, subsequently, a cluster analysis was performed to check how those ideas were articulated and modeled. By means of this analysis, we were able to identify the mental models underlying the responses of preservice primary teachers. Furthermore, the results showed that the models they did have were not used when it came to making predictions in local situations. Instead, they employed heuristic rules based on everyday assumptions, not always consistent with tidal cycles of approximately 12 h. However, faced with situations that required thinking on a global scale, they did use their models, normally based on alternative conceptions. Lastly, from the results obtained, we consider some of the possible difficulties that preservice primary teachers may have in learning about the phenomenon of tides, and the implications for future teaching-learning designs aimed at overcoming those difficulties.

关键词： descriptive knowledge Models Modeling Preservice teachers' models Tides

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Introducing Experiential knowledge Platform: A Smart Decision Supporter for Field Experts

Introducing Experiential Knowledge Platform: A Smart Decisio...

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International Conference on Big Data and Smart Computing (BigComp)

作者： Han, Keejun Lee, Eunkyung G. Je, Hyunwoo Yi, Mun Y. Korea Adv Inst Sci & Technol Dept Knowledge Serv Engn Daejeon South Korea

ISBN: (纸本)9781467387965

Experiential knowledge is knowledge obtained through reflection on experience. In case of experiential knowledge within a specialized domain, this knowledge is strengthened over time as a field expert accumulates more experience in the chosen field. However, it is unfortunate that the knowledge is often confined within each individual in implicit form and it is hardly well-managed by an organization. Although there are several systems designed to acquire and exploit experiential knowledge, escalating maintenance costs pose serious challenges to their adoption and continuous use. In this paper, we propose a new knowledge-based system that acquires experiential knowledge through natural interactions with domain experts and keeps it growing by adding specialization rules, thereby reducing maintenance costs substantially. We also present the overall flow of how the acquired knowledge is processed and applied to decision supporting process, particularly in diagnosing potential diseases from blood tests.

关键词： experiential knowledge knowledge-based system procedural knowledge descriptive knowledge

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When Rating Format Induces Different Rating Processes: The Effects of descriptive and Evaluative Rating Modes on Discriminability and Accuracy

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JOURNAL OF BUSINESS AND PSYCHOLOGY 2015年第4期30卷 795-812页

作者： Cambon, Laurent Steiner, Dirk D. Univ Nice Sophia Antipolis Lab Anthropol & Psychol Cognit & Sociale F-06357 Nice 4 France

We examined how different kinds of rating formats, and their interaction with purposes of rating (administrative vs. developmental), induced different performance rating processes and their consequences for rating accuracy. In two experiments, participants rated seven targets presented via videotapes using modes of rating giving access to (a) descriptive knowledge (rating scales were a target's observable behaviors: descriptive Behavior-DB), (b) evaluative knowledge (rating scales were others' behaviors that the target tended to afford: Evaluative Behavior-EB), or (c) a mix of the two knowledge types (rating scales were traits). Indexes of discriminability (within- and between-ratee discriminability) and of accuracy (differential elevation and differential accuracy) were collected. The results showed that EB rating scales led to higher between-ratee discriminability and differential elevation than other modes of rating, whereas DB rating scales led to higher within-ratee discriminability than the other modes. Our results indicate that EB rating scales are more suited to comparing different ratees (e.g., an administrative purpose for rating), whereas DB scales are more suited to identifying strengths and weaknesses of a particular ratee (e.g., a developmental purpose). Our experiments are the first to apply dual-knowledge (descriptive vs. evaluative) theory to a performance appraisal context and to examine rating purpose in interaction with these two forms of person knowledge. The results, consistent with theoretical predictions, indicate that using rating scales with different types of content as a function of the rating purpose will produce more appropriate performance ratings.

关键词： Evaluative knowledge descriptive knowledge Performance appraisal Discriminability Rating format Accuracy Purpose of evaluation

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Mapping Design Contributions in Information Systems Research: The Design Research Activity Framework

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COMMUNICATIONS OF THE ASSOCIATION FOR INFORMATION SYSTEMS 2021年 49卷 355-378页

作者： Maedche, Alexander Gregor, Shirley Parsons, Jeffrey Karlsruhe Inst Technol KIT Informat Syst Karlsruhe Germany Australian Natl Univ Canberra ACT Australia Mem Univ Newfoundland Fac Business Adm Informat Syst St John NL Canada

Despite growing interest in design science research in information systems, our understanding about what constitutes a design contribution and the range of research activities that can produce design contributions remains limited. We propose the design research activity (DRA) framework for classifying design contributions based on the type of statements researchers use to express knowledge contributions and the researcher role with respect to the artifact. These dimensions combine to produce a DRA framework that contains four quadrants: construction, manipulation, deployment, and elucidation. We use the framework in two ways. First, we classify design contributions that the Journal of the Association for Information Systems (JAIS) published from 2007 to 2019 and show that the journal published a broad range of design research across all four quadrants. Second, we show how one can use our framework to analyze the maturity of design-oriented knowledge in a specific field as reflected in the degree of activity across the different quadrants. The DRA framework contributes by showing that design research encompasses both design science research and design-oriented behavioral research. The framework can help authors and reviewers assess research with design implications and help researchers position and understand design research as a journey through the four quadrants.

关键词： Design knowledge Classification Mapping IT Artifact Design Science Research Prescriptive knowledge descriptive knowledge

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Why we need design science in entrepreneurship research an idiosyncratic perspective based on the experiences and learnings of an ex-practitioner in training to be an entrepreneurship scholar

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Journal of Business Venturing Insights 2023年 19卷

作者： Chan Timothy Hor, Shoon School of Business Faculty of Management Queensland University of Technology Brisbane Australia

For entrepreneurship research to be relevant and impactful, entrepreneurship scholars must start by understanding the problems faced by ***, problems are different from research *** scholars, where do we start, and how do find these problems? And how do we ensure that we do user-inspired research that advances both understanding and practical relevance? Based on my experience and learnings as an ex-practitioner in training to be an entrepreneurship scholar, who took on the Me-search approach in my research to solve a problem in digital entrepreneurship, this essay presents my humble experiences in framing a real-world problem in solution-oriented entrepreneurship *** that I have taken a path less traveled, unintentionally, starting with a problem rather than from a theory orientation, I present my informal reflections on why entrepreneurship scholars need to develop both descriptive and prescriptive knowledge. © 2022 Elsevier Inc.

关键词： descriptive knowledge Design science Entrepreneurial problems Prescriptive knowledge Solution-oriented research

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