Filters








10,487 Hits in 3.0 sec

Granular Computing Based Ontology Learning Model and Its Applications

Hongcan Yan, Feng Zhang, Baoxiang Liu
2015 Cybernetics and Information Technologies  
The empirical research of the traditional Chinese medicine ontology shows that these algorithms are correct and efficient, and provide a good technical way for ontology learning.  ...  In this paper the concepts "Ontology granule" and "Compatible granule" were defined, applying the granular computing ideas and an ontology model, an Ontology granular set; and thus ontology tree generation  ...  Conclusion Based on the granular computing theory, we have successfully completed the ontology concept hierarchy model of the learning process.  ... 
doi:10.1515/cait-2015-0071 fatcat:bci4adl2p5fevjbqbg445v642q

Data-Driven Granular Computing Systems and Applications

Ruidan Su, George Panoutsos, Xiaodong Yue
2020 Granular Computing  
The paper employs Granular Computing as a framework for merging the existing domain ontologies thereby unifying multiple domain ontologies into a single representative domain ontology.  ...  Subsequently, Shu Zhao et al. present their work on A Multi-Granular Network Representation Learning Method which introduces Quotient Space Theory, one of Granular Computing theories into network embedding  ... 
doi:10.1007/s41066-020-00222-6 fatcat:ockd3jhe7favvnookoreowbkti

A Methodology for Hierarchical Classification of Semantic Answer Types of Questions

Ammar Ammar, Remzi Celebi, Shervin Mehryar
2020 Zenodo  
Predicting granular answer types for a question from a big knowledge graph is a greater challenge due to the large number of possible classes.  ...  We use a multi-class text classification algorithm built-in fastai library for these two models.  ...  . • Predicting granular answer types for a question from an ontology is a greater challenge due to the large number of possible classes.  ... 
doi:10.5281/zenodo.4513823 fatcat:evpmu4wz3bbijnwf4fjcfngcku

MGFN: A Multi-Granularity Fusion Convolutional Neural Network for Remote Sensing Scene Classification

Zhiguo Zeng, Xihong Chen, Zhihua Song
2021 IEEE Access  
So we choose the best modified deep learning models such as AlexNet, GoogLeNet for comparison.  ...  Images with 0.3m spatial resolution can describe a lot of geomorphic details, leading to the high classification accuracy for nearly all the deep learning models.  ... 
doi:10.1109/access.2021.3081922 fatcat:lnabnm7zung3jadqzkcusq3m3q

Ontology-Based Formal Modeling of the Pedagogical World: Tutor Modeling [chapter]

Riichiro Mizoguchi, Yusuke Hayashi, Jacqueline Bourdeau
2010 Studies in Computational Intelligence  
This chapter discusses an ontological approach to tutoring actions design as a special case of target-world modeling.  ...  The authors have been performing ontological modeling of learning/instructional theories to remedy this situation.  ...  However, unlike expert systems which model the problem space according to the heuristics of human experts, OMNIBUS models the problem space by target-world modeling, that is, the problem space is modeled  ... 
doi:10.1007/978-3-642-14363-2_11 fatcat:z3ovx4r3cjcz3i62maj6vrd4xu

Impact of Semantic Granularity on Geographic Information Search Support

Noemi Mauro, Liliana Ardissono, Laura Di Rocco, Michela Bertolotto, Giovanna Guerrini
2018 2018 IEEE/WIC/ACM International Conference on Web Intelligence (WI)  
A comparative analysis of the performance of a query expansion model, using three spatial ontologies defined at different semantic granularity levels, reveals that a fine-grained representation enhances  ...  types of information to search for.  ...  DATASETS FOR TRAINING THE CS MODEL We used the AOL query log 1 as a source of search sessions.  ... 
doi:10.1109/wi.2018.00-73 dblp:conf/webi/MauroARBG18 fatcat:ho7muh2zjbgldbg7x2owxdh3ju

Fuzzy Ontology Mining and Semantic Information Granulation for Effective Information Retrieval Decision Making

Chapmann C.L. Lai, Raymond Y.K. Lau, Yuefeng Li
2011 International Journal of Computational Intelligence Systems  
Our TREC-based experiment reveals that the proposed fuzzy ontology based granular IR system outperforms a classical vector space based IR system in domain specific IR.  ...  One main component of the proposed computational model is the fuzzy ontology mining mechanism which can automatically build domain-specific ontology for the estimation of semantic granularity of documents  ...  based on the classical vector space model 23 .  ... 
doi:10.2991/ijcis.2011.4.1.5 fatcat:gvpfbcbhsbhjrgjygi4me2f2jq

Fuzzy Ontology Mining and Semantic Information Granulation for Effective Information Retrieval Decision Making

Raymond Y.K. Lau, Chapmann C.L. Lai, Yuefeng Li
2011 International Journal of Computational Intelligence Systems  
Our TREC-based experiment reveals that the proposed fuzzy ontology based granular IR system outperforms a classical vector space based IR system in domain specific IR.  ...  One main component of the proposed computational model is the fuzzy ontology mining mechanism which can automatically build domain-specific ontology for the estimation of semantic granularity of documents  ...  based on the classical vector space model 23 .  ... 
doi:10.1080/18756891.2011.9727763 fatcat:qck4byizgbemzlssdyglwmwnpq

An Ontology-Based Framework for Authoring Tools in the Domain of Sustainable Energy Education

Sotirios Karetsos, Dias Haralampopoulos, Konstantinos Kotis
2011 International Journal of Agricultural and Environmental Information Systems  
This paper presents an "ontology-based" framework for the production of learning designs, focusing in the domain of sustainable energy education.  ...  We envisage this framework both as a means to support the authoring of learning scenarios and as a provisioning of a field for conversation about which should be the appropriate form of an authoring tool  ...  Our research approach is consistent with a pathway for future research efforts in the learning design domain, proposed by Agostinho (2008) , underlying the need to work globally as one community and focusing  ... 
doi:10.4018/jaeis.2011010103 fatcat:rbpupoksknhflorj4b5u2cf5dq

A survey on ontologies for human behavior recognition

Natalia Díaz Rodríguez, M. P. Cuéllar, Johan Lilius, Miguel Delgado Calvo-Flores
2014 ACM Computing Surveys  
We focus on a more detailed analysis of ontologies, since properties like flexibility, reasoning, information sharing, and knowledge representation make these models one of the most promising tools for  ...  As a result, any missing features, which are relevant for modeling daily human behaviors, are identified as future challenges.  ...  the Spanish Ministry of Economy and Competitiveness, and the project Development of an Intelligent System for Behaviour Detection and Control in a Tagged World (TIN2009-14538-C02-01).  ... 
doi:10.1145/2523819 fatcat:kvlfg5ghsfgpbewnbebhpakk4i

Computational Intelligence in Decision Making

Tianrui Li, Pawan Lingras, Yuefeng Li, Joseph Herbert
2011 International Journal of Computational Intelligence Systems  
The authors propose a three-way view decision model based on decision-theoretic rough set model, in which optimistic decision, pessimistic decision, and equable decision are provided according to the cost  ...  It contains 86 final accepted papers from 229 online submissions for RSKT2009.  ...  Experimental results show that the proposed fuzzy ontology based granular IR system outperforms a classical vector space based IR system in domain specific IR.  ... 
doi:10.1080/18756891.2011.9727758 fatcat:k4agqubsmnbuhl5zhowxyhmwiy

AUTOMATIC IDENTIFICATION AND EXTRACTION OF ADAPTIVE LEARNING OBJECTS FROM TRADITIONAL COURSEWARE

Mohammed Atef, Shehab Gamalel-Din, Gamal Tharwat
2021 Journal of Al-Azhar University Engineering Sector  
However, the main hurdle for the adaptive model is building the repository of micro learning objects (MLOs) with reasonable sizes suitable for reassembling into lessons in a way that is more suitable for  ...  Noteworthy, there is a wealth of digital learning contents and open-source educational curricula available online, but in the large granular traditional format.  ...  ACKNOWLEDGMENT This research is partially supported by the Egyptian Information Technology Industry Development Authority (ITIDA) under ITAC project number CFP159 titled "EduEdges: An Adaptive e-Learning  ... 
doi:10.21608/auej.2021.187978 fatcat:srufi5ijyzcllmb4fj2ucbt4cm

Leveraging cognitive context knowledge for argumentation based object classification in multi-sensor networks

Zhiyong Hao, Junfeng Wu, Tingting Liu, Xiaohong Chen
2019 IEEE Access  
To address this category of granularity inconsistent problem in multi-sensor collaborative object classification tasks, we propose a cognitive context knowledge-enriched method for classification conflict  ...  It is a great challenge to achieve interpretable collaborative object classification in multisensor networks.  ...  Considering the aforementioned space object classification tasks, the domain Ontology of space objects is a shared understanding within a community of domain experts, and can be used for reasoning about  ... 
doi:10.1109/access.2019.2919073 fatcat:azmkmxylcneppjga45mct7nmcq

EAPB: entropy-aware path-based metric for ontology quality

Ying Shen, Daoyuan Chen, Buzhou Tang, Min Yang, Kai Lei
2018 Journal of Biomedical Semantics  
(data quality), and a case study (ontology structure and text visualization).  ...  We believe that EAPB is helpful for managing ontology development and evaluation projects.  ...  Other datasets generated and/or analyzed during the current study are available in the Disease Ontology (DO) repository (http:// www.obofoundry.org/ontology/doid.html) [19] , Infectious Disease Ontology  ... 
doi:10.1186/s13326-018-0188-7 pmid:30097014 pmcid:PMC6086046 fatcat:j57ethjd7rfxxgzn576b4tjhte

Using Word Embeddings to Learn a Better Food Ontology

Jason Youn, Tarini Naravane, Ilias Tagkopoulos
2020 Frontiers in Artificial Intelligence  
This work demonstrates how high-dimensional representations of food can be used to populate ontologies and paves the way for learning ontologies that integrate contextual information from a variety of  ...  We propose a semi-supervised framework for the automated ontology population from an existing ontology scaffold by using word embeddings.  ...  ACKNOWLEDGMENTS We would like to thank the members of the Tagkopoulos lab and the reviewers for their suggestions.  ... 
doi:10.3389/frai.2020.584784 pmid:33733222 pmcid:PMC7861243 fatcat:aym73wiqg5aopd6m7rm7afmgym
« Previous Showing results 1 — 15 out of 10,487 results