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• Swapnil Soni Thesis
  ...h information for a given query <ref>Alexander Pretschner and Susan Gauch. Ontology based personalized search. InToolswith Artificial Intelligence, 1999. Proce ...on popularity, relevancy, and reliability. We have evaluated many machine learning algorithms and selected one of them based on an evaluation matrix. The algo
  11 KB (1,771 words) - 14:30, 20 December 2016
• Social and Physical Sensing Enabled Decision Support
  ...http://kidl2020.aiisc.ai/ "Hypertext 2020 Tutorial: Knowledge-infused Deep Learning"], In 31st ACM Conference on Hypertext and Social Media (HT'20), Florida, U ..., Amelie Gyrard, Amit Sheth. [https://arxiv.org/abs/1810.12510 empathi: An ontology for Emergency Managing and Planning about Hazard Crisis]. International Con
  19 KB (2,457 words) - 20:03, 5 June 2020
• HeadEx
  Then, we use a learning approach, employing proposed syntactic features derived from parsing, HeadEx utilizes [[CEVO]] Ontology.
  1 KB (188 words) - 16:35, 29 April 2016
• Vinh Nguyen
  Had the breakout session at the Ontology Summit Symposium Invited speaker at the Ontology Summit 2018: Contexts in Open Knowledge Network.
  26 KB (3,491 words) - 14:24, 12 January 2022
• SmartIoTWorkshopAAAI2018
  ...the possibilities of using Artificial Intelligence (AI) including machine learning, NLP, and semantic Web techniques to create new solutions that exploit the * Machine Learning, knowledge-enabled and spatio-temporal processing applied IoT data
  17 KB (2,359 words) - 15:08, 20 February 2018
• KE4WoTChallengeWWW2018
  ...n Geospatial Consortium (OGC)''' standard, extending and improving the SSN ontology published in 2011. ....linkeddata.es/def/wot/index-en.html]. At the current date of writing, WoT ontology is not aligned with W3C SSN ontologies. A healthcare scenario has been desi
  39 KB (5,707 words) - 13:23, 23 March 2021
• Knowledge will Propel Machine Understanding of Content
  ...xploitation of multimodal data and continued incorporation of knowledge in learning techniques. ...m the Web-scale unlabeled data that is freely available for consumption by learning systems such as deep neural nets. However, many traditional research proble
  48 KB (7,173 words) - 13:20, 13 May 2018
• AmelieGyrard
  ...ntologies] (e.g., ISO/IEC SC41 IoT and Digital Twin, ISO/IEC SC42 AI, IEEE Ontology for Autonomous Robotics) or follows them (ETSI SmartM2M, W3C, iot.schema.or ...s/Internet of Things (IoT), semantic web best practices and methodologies, ontology engineering, Artificial Intelligence (AI) such as semantic reasoning, and i
  78 KB (10,067 words) - 13:15, 15 April 2024
• ReaCTrack
  ...llects and analyzes the messages. Through different analysis using machine learning (ML) and natural language processing (NLP), ReaCTrack extracts relevant inf ...tive of the medications against a few knowledge sources such as Drug Abuse Ontology (DOA), Medical Dictionary for Regulatory Activities (MedDRA) [11], and prim
  14 KB (1,982 words) - 18:52, 9 September 2021
• Semantic, Cognitive, and Perceptual Computing: Paradigms That Shape Human Experience
  ...ation, these operators often explicitly model the domain of interest as an ontology or a knowledge graph. ...proximates human cognition. CC systems, another research area, use machine learning and other AI techniques without explicit programming. CC systems learn from
  35 KB (5,073 words) - 18:51, 30 October 2022
• Knoesis Alchemy of Healthcare
  ...'' A semantic platform providing the rich functionality of NLP and Machine learning over an integrated knowledge base comprising of diverse domain-specific med .... Existing support systems are developed using labor-intensive statistical learning processes. Our approach utilizes existing human-curated knowledge bases (KB
  13 KB (1,859 words) - 20:14, 4 September 2018
• Answer-Robotic-SemanticWeb-IoT-Workshop-IROS2019
  ...lytics on [http://lov4iot.appspot.com/?p=lov4iot-robotics LOV4IoT-Robotics ontology catalog] following the research ideas from the [http://wiki.knoesis.org/ind ...applicative domain within this ontology (e.g., healthcare) useful when the ontology covers several domains (e.g., robots for cooking, robots for surgery).
  29 KB (4,093 words) - 16:14, 4 November 2019
• Knowledge Graphs and Knowledge Networks: The Story in Brief
  ...brevity, we will not review the literature on richer (but usually manual) ontology modeling and development in the Semantic Web community (see [1] for a recen ...s enterprises, and enhancing already very popular AI techniques of machine learning and natural language processing (NLP).
  31 KB (4,569 words) - 02:30, 19 July 2019
• AIISC Knowledge Graph
  * Ontology quality and best practices * Ontology methodology to reuse ontologies
  24 KB (3,149 words) - 14:27, 21 March 2023
• Advancing Neuro-symbolic AI with Deep Knowledge-infused Learning
  ...anced form called deep-infusion. This project focuses on developing a deep learning architecture and associated algorithms that involve interleaving broader va ...graphs. We specifically focus on the knowledge graph's integration in deep learning algorithms (e.g., deep language models) to achieve explainability and inter
  39 KB (5,333 words) - 22:21, 20 December 2023
• Smart manufacturing
  ...we obtained from public data sources. Figure 1 includes the approaches to learning from rare event data that we exemplified from the comprehensive survey. ===Figure 1: Approaches to learning from rare event data===
  11 KB (1,538 words) - 19:27, 25 February 2024
• Neurosymbolic Artificial Intelligence Research at AIISC
  ...ognition from raw data using neural networks trained using self-supervised learning objectives such as next-word prediction or object recognition. On the other ...A. (2021). Semantics of the black-box: Can knowledge graphs help make deep learning systems more interpretable and explainable? IEEE Internet Computing, 25 (1)
  14 KB (1,772 words) - 15:34, 1 March 2024

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