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  • == What is an Ontology? == ...of interpretation by both humans and computers[http://www.bioontology.org/learning-about-ontologies NCBO] .
    1 KB (188 words) - 17:15, 24 January 2013

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  • Mashup Editor has a steeper learning curve and can do much more than Yahoo! Pipes. However the need to be profic ...XHTML. Developers can directly embed meta-data from various models such an ontology, taxonomy or a tag cloud into their API descriptions. The embedded meta-dat
    18 KB (2,860 words) - 15:12, 20 April 2011
  • * [[metaLearning]]: Meta-Learning Multi-Agent Communication, ''Qi Zhang (PI), June 2021'' * [[Advancing Neuro-symbolic AI with Deep Knowledge-infused Learning]]
    10 KB (1,249 words) - 16:26, 19 February 2024
  • ==<b>Drug Abuse Ontology</b>== ...se see here for our work on [http://wiki.aiisc.ai/index.php/DAO Drug Abuse Ontology.]
    21 KB (2,884 words) - 18:55, 1 December 2022
  • ...sis.org/library/resource.php?id=00149 Semantic (Web) Technology In Action: Ontology Driven Information Systems for Search, Integration and Analysis], IEEE Data ...ge and by a variety of information-retrieval, statistical, and AI (machine learning and natural-language processing) techniques, at the Web scale. Semantic ana
    27 KB (3,973 words) - 01:41, 11 November 2023
  • required. Figure 2 shows an annotation referring to an ontology from from Ruby) but lacks an ontology’s
    14 KB (2,071 words) - 15:59, 30 July 2010
  • ...loged at the [http://www.bioontology.org US National Center for Biomedical Ontology] ). Semantic models such the nonfunctional/system/ ontology
    22 KB (3,193 words) - 15:34, 3 August 2010
  • typically as an ontology. Then, we extract relevant use them to populate the ontology. Finally, we
    20 KB (3,011 words) - 18:12, 27 February 2014
  • The Semantics conveyed by ontology schemas ex-pressed in RDFS (http://www.w3.org/TR/rdf-schema/) or OWL (http: ...seen as a top-down approach to relationship extraction. Beginning with an ontology schema containing a rich set of named relationships (and their synonyms), w
    24 KB (3,561 words) - 17:20, 22 November 2010
  • ...rocessing tool that allows biologists to formulate complex queries without learning the query language syntax. We demonstrate the significance of SPSE by usin ...ow complex SPARQL queries can be formulated easily with minimal skills and ontology background.
    8 KB (1,115 words) - 19:49, 11 July 2011
  • ...iption logics in the case of OWL-DL. It is very difficult to keep a single ontology logically consistent while maintaining high expressiveness and high connect ...ocks of knowledge that are not supposed to change frequently. The field of ontology was concerned with the essence and categorization of things, not with the t
    39 KB (6,172 words) - 22:36, 11 January 2013
  • ...ning course, open to registered members of the official American Red Cross learning management platform, takes two hours online. After completion, participant ...takeholders in emergency response. Step one is to create a common, modular ontology leveraging knowledge of these differences and flexible data management. The
    23 KB (3,252 words) - 21:13, 29 September 2014
  • ...logy KnoEO of the concepts and relationships concerned with an event. This ontology must be general enough so that it can be used on various events. Here is an ...construct a lexicon of words expressing relationships defined in the event ontology, and on the other hand, we extract the relationship indicators (e.g., the v
    9 KB (1,431 words) - 00:13, 20 November 2011
  • *Machine Learning *Ontology Development.
    12 KB (1,688 words) - 20:33, 11 December 2014
  • ...of Semantics in Computer Science, from the formal, top-down approaches in ontology engineering to the bottom-up approaches of social knowledge accumulation th * [[Human Performance and Cognition Ontology]]
    8 KB (1,093 words) - 22:43, 11 January 2013
  • ...on vocabularies. An example of a common vocabulary is the Dublin Core (DC) ontology, a set of universally accepted metadata used to describe a resource (e.g. d ...and mappings between terms having the same meaning. Taxonomies, a form of ontology, can express simple relationships in the materials domain.
    35 KB (5,077 words) - 20:54, 23 November 2015
  • ...n the Web, this knowledge is aligned with concepts in the DOLCE Ultra Lite ontology[http://www.loa-cnr.it/ontologies/DUL.owl]. Figure 1 provides a simple examp ...tructure learning that derives qualitative dependencies and (ii) parameter learning that quantifies dependencies. We have investigated how to combine these app
    61 KB (8,752 words) - 18:31, 23 October 2014
  • ...the observation (note: prefix ssn is used to denote concepts from the SSN ontology). A feature (ssn:Feature) is an object or event in an environment, and a p ...tructure learning that derives qualitative dependencies and (ii) parameter learning that quantifies dependencies. We have investigated how to combine these app
    50 KB (7,247 words) - 18:36, 1 August 2014
  • ..., such as the Semantic Web, Natural Language Processing (NLP), and Machine Learning (ML), to advance the analysis of social media data for drug abuse epidemiol * [[DAO]]: Drug Abuse Ontology
    18 KB (2,521 words) - 23:32, 2 November 2022
  • ...cus term, we check whether there is a direct match to a class label in the ontology as the type. If a candidate type is not found, we further analyze focus ter ...D.H.: Knowledge acquisition via incremental conceptual clustering. Machine learning 2(2), 139–172 (1987) <br>
    14 KB (2,314 words) - 16:16, 11 April 2016
  • ...an mind. This conceptual knowledge, represented formally in the form of an ontology, can be used to annotate data and infer new knowledge from interpreted data ...on to form additional input for the CC system. CC systems utilize machine learning and other AI techniques in achieving all this without being explicitly prog
    24 KB (3,538 words) - 20:33, 21 May 2015
  • ...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
  • ...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
  • 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
  • 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
  • ...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
  • ...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
  • ...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
  • ...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
    77 KB (9,862 words) - 08:42, 20 March 2024
  • ...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
  • ...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
  • ...'' 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
  • ...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
  • ...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
  • * Ontology quality and best practices * Ontology methodology to reuse ontologies
    24 KB (3,149 words) - 14:27, 21 March 2023
  • ...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
  • ...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
  • ...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