Academic literature on the topic 'Taxonomy refinement'
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Journal articles on the topic "Taxonomy refinement"
Freeman, Julie, Geraint Wiggins, Gavin Starks, and Mark Sandler. "A Concise Taxonomy for Describing Data as an Art Material." Leonardo 51, no. 1 (February 2018): 75–79. http://dx.doi.org/10.1162/leon_a_01414.
Full textLeeder, Chris, Karen Markey, and Elizabeth Yakel. "A Faceted Taxonomy for Rating Student Bibliographies in an Online Information Literacy Game." College & Research Libraries 73, no. 2 (March 1, 2012): 115–33. http://dx.doi.org/10.5860/crl-223.
Full textDing, Yepeng, and Hiroyuki Sato. "Formalism-Driven Development: Concepts, Taxonomy, and Practice." Applied Sciences 12, no. 7 (March 27, 2022): 3415. http://dx.doi.org/10.3390/app12073415.
Full textWilliams, Monnica T., Matthew D. Skinta, and Renée Martin-Willett. "After Pierce and Sue: A Revised Racial Microaggressions Taxonomy." Perspectives on Psychological Science 16, no. 5 (September 2021): 991–1007. http://dx.doi.org/10.1177/1745691621994247.
Full textÖpik, Maarja, John Davison, Mari Moora, and Martin Zobel. "DNA-based detection and identification of Glomeromycota: the virtual taxonomy of environmental sequences." Botany 92, no. 2 (February 2014): 135–47. http://dx.doi.org/10.1139/cjb-2013-0110.
Full textLove, Kristina. "Towards a further analysis of teacher talk." Australian Review of Applied Linguistics 14, no. 2 (January 1, 1991): 30–72. http://dx.doi.org/10.1075/aral.14.2.02lov.
Full textda Silva, David V., João M. Duarte, Maria G. Miguel, and José M. Leitão. "AFLP assessment of the genetic relationships among 12 Thymus taxa occurring in Portugal." Plant Genetic Resources 15, no. 1 (July 27, 2015): 89–92. http://dx.doi.org/10.1017/s1479262115000337.
Full textKadmin, A. F., R. A. Hamzah, M. N. Abd Manap, M. S. Hamid, and S. F. Abd Gani. "mproved Stereo Matching Algorithm based on Census Transform and Dynamic Histogram Cost Computation." International Journal of Emerging Technology and Advanced Engineering 11, no. 8 (August 19, 2021): 48–57. http://dx.doi.org/10.46338/ijetae0821_07.
Full textCimino, J. J. "Formal Descriptions and Adaptive Mechanisms for Changes in Controlled Medical Vocabularies." Methods of Information in Medicine 35, no. 03 (May 1996): 202–10. http://dx.doi.org/10.1055/s-0038-1634662.
Full textMARTIN, JENNIFER M., and ERIC J. HILTON. "A taxonomic review of the family Trachipteridae (Acanthomorpha: Lampridiformes), with an emphasis on taxa distributed in the western Pacific Ocean." Zootaxa 5039, no. 3 (September 16, 2021): 301–51. http://dx.doi.org/10.11646/zootaxa.5039.3.1.
Full textDissertations / Theses on the topic "Taxonomy refinement"
NOBANI, NAVID. "Empowering XAI and LMI with Human-in-the-loop." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2023. https://hdl.handle.net/10281/404831.
Full textOnce aimed to mimic the human brain and existed only as mathematical models in academia, the vast family of Artificial Intelligence methods are well passed that initial goal; models with billions of parameters trained on millions of mostly human-generated data. Such models are present in almost each and every aspect of our lives, from the weather forecasts and social network content to how our banks detect fraudulent transactions connected to our accounts and maps that guide us to a restaurant through unknown streets of a new city. All these advancements, though, have a common limitation: their performance is bounded to the amount of human knowledge we can feed them, i.e. training data that should chase the ever-growing model parameters both in terms of quantity and quality. Unfortunately, such a requirement often comes with a high cost, given that generating machine-friendly data and updating and maintaining them is enormously labour-intensive. One way to overcome this issue is the Human-in-the-Loop (HITL) paradigm: looking at humans not only as a passive part of the system, i.e. provider of inputs and consumer of outputs but as an active part of AI systems that participate in the creation and validation of data, model parameters and model inputs. By doing so, we inject the system with up-to-date human knowledge that otherwise should have arrived through expensive and often outdated training sets. This thesis proposes novel methods for integrating HITL with the eXplainable Artificial Intelligence (XAI) and Labour Market Intelligence (LMI) fields: In part I, We propose and implement a conversational explanation system called \convxai by extending the current state-of-the-art and introducing a new conversation type, i.e. Clarification conversation. Following the HITL paradigm, \convxai differentiates itself from the classic XAI systems that create one-size-fits-all explanations regardless of the user's knowledge level, background and need by providing explanations that fit the user's context and using the information provided by the user. This model is made by anonymous data provided by Digital Attitude S.r.l company. In part II, we provide a model called \taxorefs, which achieves its objective, i.e. taxonomy refinement, by considering domain experts as providers of the input data (taxonomy) and in the same time, as final validators of the model's suggestions. This method was developed by data provided by Tabulaex/Burning Glass Technologies company.
Scime, Anthony. "Taxonomic information retrieval (TAXIR) from the World Wide Web knowledge-based query and results refinement with user profiles and decision models /." 1997. http://catalog.hathitrust.org/api/volumes/oclc/39258102.html.
Full textBooks on the topic "Taxonomy refinement"
Rhodes, Ryan E., David M. Williams, and Mark T. Conner. Affective Determinants of Health Behavior. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780190499037.003.0021.
Full textForshaw, Joseph M., Mark Shephard OAM, and Anthony Pridham. Grassfinches in Australia. CSIRO Publishing, 2012. http://dx.doi.org/10.1071/9780643107878.
Full textBook chapters on the topic "Taxonomy refinement"
Malandri, Lorenzo, Fabio Mercorio, Mario Mezzanzanica, and Navid Nobani. "TaxoRef: Embeddings Evaluation for AI-driven Taxonomy Refinement." In Machine Learning and Knowledge Discovery in Databases. Research Track, 612–27. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86523-8_37.
Full textBell, Rayna C., Luis M. P. Ceríaco, Lauren A. Scheinberg, and Robert C. Drewes. "The Amphibians of the Gulf of Guinea Oceanic Islands." In Biodiversity of the Gulf of Guinea Oceanic Islands, 479–504. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-06153-0_18.
Full text"Ascoli, Wylton, And Alnwick On Scotuss Formal Distinction: Taxonomy, Refinement, And Interaction." In Philosophical Debates at Paris in the Early Fourteenth Century, 127–49. BRILL, 2009. http://dx.doi.org/10.1163/ej.9789004175662.i-526.20.
Full text"Cutthroat Trout: Evolutionary Biology and Taxonomy." In Cutthroat Trout: Evolutionary Biology and Taxonomy, edited by Luke Schultz, Neil F. Thompson, C. Nathan Cathcart, and Thomas H. Williams. American Fisheries Society, 2018. http://dx.doi.org/10.47886/9781934874509.ch14.
Full text"Advances in Understanding Landscape Influences on Freshwater Habitats and Biological Assemblages." In Advances in Understanding Landscape Influences on Freshwater Habitats and Biological Assemblages, edited by Jefferson T. Deweber, Logan Sleezer, and Emmanuel A. Frimpong. American Fisheries Society, 2019. http://dx.doi.org/10.47886/9781934874561.ch16.
Full textConference papers on the topic "Taxonomy refinement"
"IMPRECISE EMPIRICAL ONTOLOGY REFINEMENT - Application to Taxonomy Acquisition." In 9th International Conference on Enterprise Information Systems. SciTePress - Science and and Technology Publications, 2007. http://dx.doi.org/10.5220/0002391800310038.
Full textFatima, Iram, Sharifullah Khan, and Khalid Latif. "Refinement Methodology for Automatic Document Alignment Using Taxonomy in Digital Libraries." In 2009 IEEE International Conference on Semantic Computing (ICSC). IEEE, 2009. http://dx.doi.org/10.1109/icsc.2009.45.
Full textAly, Rami, Shantanu Acharya, Alexander Ossa, Arne Köhn, Chris Biemann, and Alexander Panchenko. "Every Child Should Have Parents: A Taxonomy Refinement Algorithm Based on Hyperbolic Term Embeddings." In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics. Stroudsburg, PA, USA: Association for Computational Linguistics, 2019. http://dx.doi.org/10.18653/v1/p19-1474.
Full textXiao, Renbin, Ji Zhou, Jun Yu, and Jianzhong Cha. "A New Approach to Intelligent Design." In ASME 1995 Design Engineering Technical Conferences collocated with the ASME 1995 15th International Computers in Engineering Conference and the ASME 1995 9th Annual Engineering Database Symposium. American Society of Mechanical Engineers, 1995. http://dx.doi.org/10.1115/detc1995-0014.
Full textCao, Dongxing, Ming Wang Fu, Yongmao Gu, and Haipeng Jia. "Port-Based Ontology Modeling for Product Conceptual Design." In ASME 2008 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/detc2008-49726.
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