scholarly journals Research of Contextual Semantic Reasoning Model Based on Domain Ontology

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Jinhai Li ◽  
Yunlei Ma ◽  
Xiang Zhan ◽  
Jiaming Pei
Keyword(s):  
Conditional Entropy ◽  
Mobile Network ◽  
Domain Ontology ◽  
Mobile Environment ◽  
Model Framework ◽  
Semantic Reasoning ◽  
Model Based ◽  
Contextual Sensitivity ◽  
Information Recommendation ◽  
Mobile Context

With the development of mobile network technology and the popularization of mobile terminals, traditional information recommendation systems are gradually changing in the direction of real-time and mobile information recommendation. Information recommendation brings the problem of user contextual sensitivity within the mobile environment. For this problem, first, this paper constructs a domain ontology, which is applicable to the contextual semantic reasoning model. Second, based on the “5W + 1H” method, this paper constructs a context pedigree of the mobile environment using a model framework of a domain ontology. The contextual factors of the mobile environment are divided into six categories: the What-object context, the Where-place context, the When-time context, the Who-subject context, the Why-reason context, and the How-effect context. Then, considering the degree of influence of each contextual factor from the mobile context pedigree to the user is different, this paper uses contextual conditional entropy to calculate the contextual weight of each contextual attribute in the recommendation process. Based on this, a contextual semantic reasoning model based on a domain ontology is constructed. Finally, based on the open dataset provided by GroupLens, this paper verifies the validity and efficiency of the model through a simulation experiment.

Analysis of Personalized Recommendation Models Based on Multi-Dimensional Ontology

2014 ◽  
Vol 998-999 ◽  
pp. 1347-1351
Author(s):  
Xiao Yan Yuan
Keyword(s):  
Domain Ontology ◽  
Personalized Recommendation ◽  
Single Dimension ◽  
Model Based ◽  
Knowledge Based ◽  
Multiple Dimensions ◽  
Information Recommendation

In order to solve the problem of information recommendation from single dimension, a personalized recommendation model based on multi-dimensional ontology is proposed in this paper. The necessity of multi-dimensional ontology is analyzed firstly. A multi-dimensional ontology, including domain ontology, time ontology and user ontology, etc., is then established using the examples of IT forefront knowledge. Based on this new ontology, recommendation of resources from multiple dimensions, i.e., the semantic, time, and comprehensive dimensions, is analyzed. Finally the personalized multi-dimensional recommendation model is presented.

scholarly journals Variability in Estimated Modelled Insulin Secretion

2021 ◽  
pp. 193229682199112
Author(s):  
Jennifer J. Ormsbee ◽  
Hannah J. Burden ◽  
Jennifer L. Knopp ◽  
J. Geoffrey Chase ◽  
Rinki Murphy ◽  
...  
Keyword(s):  
Insulin Secretion ◽  
Kinetic Parameters ◽  
Pancreatic Beta Cells ◽  
Compartment Model ◽  
Interquartile Range ◽  
Cumulative Distribution ◽  
Model Framework ◽  
Intravenous Glucose ◽  
C Peptide ◽  
Model Based

Background: The ability to measure insulin secretion from pancreatic beta cells and monitor glucose-insulin physiology is vital to current health needs. C-peptide has been used successfully as a surrogate for plasma insulin concentration. Quantifying the expected variability of modelled insulin secretion will improve confidence in model estimates. Methods: Forty-three healthy adult males of Māori or Pacific peoples ancestry living in New Zealand participated in an frequently sampled, intravenous glucose tolerance test (FS-IVGTT) with an average age of 29 years and a BMI of 33 kg/m2. A 2-compartment model framework and standardized kinetic parameters were used to estimate endogenous pancreatic insulin secretion from plasma C-peptide measurements. Monte Carlo analysis (N = 10 000) was then used to independently vary parameters within ±2 standard deviations of the mean of each variable and the 5th and 95th percentiles determined the bounds of the expected range of insulin secretion. Cumulative distribution functions (CDFs) were calculated for each subject for area under the curve (AUC) total, AUC Phase 1, and AUC Phase 2. Normalizing each AUC by the participant’s median value over all N = 10 000 iterations quantifies the expected model-based variability in AUC. Results: Larger variation is found in subjects with a BMI > 30 kg/m2, where the interquartile range is 34.3% compared to subjects with a BMI ≤ 30 kg/m2 where the interquartile range is 24.7%. Conclusions: Use of C-peptide measurements using a 2-compartment model and standardized kinetic parameters, one can expect ~±15% variation in modelled insulin secretion estimates. The variation should be considered when applying this insulin secretion estimation method to clinical diagnostic thresholds and interpretation of model-based analyses such as insulin sensitivity.

A Semantic Retrieval Model Based on Domain Ontology of Orchard Disease and Pests

2016 ◽  
Vol 25 (3) ◽  
pp. 460-466 ◽  
Author(s):  
Jiajia Hou ◽  
Hui Han ◽  
Chengjing Qiu ◽  
Dongmei Li
Keyword(s):  
Domain Ontology ◽  
Semantic Retrieval ◽  
Retrieval Model ◽  
Model Based

Consumer Behavior in the Mobile Environment

2016 ◽  
pp. 1168-1182
Author(s):  
Jean-Eric Pelet ◽  
Panagiota Papadopoulou
Keyword(s):  
Social Media ◽  
Consumer Behavior ◽  
Qualitative Study ◽  
Ease Of Use ◽  
Mobile Environment ◽  
Privacy And Security ◽  
Business Opportunities ◽  
Negative Effect ◽  
Mobile Context ◽  
And Behavior

Consumer behavior in the omnipresent mobile environment constitutes a challenge for m-commerce vendors, as they seek to understand factors that affect it, positively and negatively, and to integrate social media in their mobile strategy. This paper presents an exploratory qualitative study about the use of smartphones and social media, in the context of m-commerce. The authors' objective is to facilitate the understanding of consumers' perceptions and behavior in m-commerce and social media and explore the potential of social media for m-commerce purposes. The results of their qualitative analysis show that reputation, design aspects, such as ease of use, as well as privacy and security are important factors for m-commerce and social media adoption and use. Their qualitative results also reveal factors having a negative effect to m-commerce. Business opportunities enabled by social media for m-commerce and how these can be leveraged in this promising mobile context are also discussed.

A model-based expert system based on a domain ontology

2002 ◽  
pp. 171-196
Author(s):  
Y KITAMURA ◽  
M IKEDA ◽  
R MIZOGUCHI
Keyword(s):  
Expert System ◽  
Domain Ontology ◽  
Model Based

Exploring M-Commerce and Social Media

2017 ◽  
pp. 1-21 ◽  
Author(s):  
Panagiota Papadopoulou
Keyword(s):  
Social Media ◽  
Mobile Devices ◽  
Mobile Phones ◽  
Mobile Environment ◽  
Commercial Activity ◽  
Business Opportunities ◽  
Negative Effect ◽  
Similarities And Differences ◽  
Use Of Social Media ◽  
Mobile Context

The proliferation of mobile phones and tablets shape a new arena for online commercial activity with unprecedented opportunities and challenges. In this omnipresent mobile environment, understanding consumer behavior constitutes a challenge for m-commerce vendors, as they seek to understand factors that affect it, positively and negatively, and to integrate social media in their mobile strategy and across mobile devices. This paper presents an exploratory qualitative research examining separately mobile phones and tablets and the use of social media, in the context of m-commerce. The results of our qualitative analysis show important factors for m-commerce and social media adoption and use, highlighting the similarities and differences between mobile phones and tablets. Our qualitative results also reveal factors having a negative effect to m-commerce, for both mobile devices. Business opportunities enabled by social media for m-commerce and how these can be leveraged in this promising multiple-device mobile context are also discussed.

scholarly journals Combining Information from Multiple Data Sources to Assess Population Health

2020 ◽  
Author(s):  
Trivellore Raghunathan ◽  
Kaushik Ghosh ◽  
Allison Rosen ◽  
Paul Imbriano ◽  
Susan Stewart ◽  
...  
Keyword(s):  
Population Health ◽  
Full Range ◽  
Complete Information ◽  
Health Conditions ◽  
Accurate Information ◽  
Elderly Age ◽  
Model Framework ◽  
Dummy Variables ◽  
Model Based ◽  
The Impact

Abstract Information about an extensive set of health conditions on a well-defined sample of subjects is essential for assessing population health, gauging the impact of various policies, modeling costs, and studying health disparities. Unfortunately, there is no single data source that provides accurate information about health conditions. We combine information from several administrative and survey data sets to obtain model-based dummy variables for 107 health conditions (diseases, preventive measures, and screening for diseases) for elderly (age 65 and older) subjects in the Medicare Current Beneficiary Survey (MCBS) over the fourteen-year period, 1999–2012. The MCBS has prevalence of diseases assessed based on Medicare claims and provides detailed information on all health conditions but is prone to underestimation bias. The National Health and Nutrition Examination Survey (NHANES), on the other hand, collects self-reports and physical/laboratory measures only for a subset of the 107 health conditions. Neither source provides complete information, but we use them together to derive model-based corrected dummy variables in MCBS for the full range of existing health conditions using a missing data and measurement error model framework. We create multiply imputed dummy variables and use them to construct the prevalence rate and trend estimates. The broader goal, however, is to use these corrected or modeled dummy variables for a multitude of policy analysis, cost modeling, and analysis of other relationships either using them as predictors or as outcome variables.

scholarly journals Journalism Model Based on Blockchain with Sharing Space

Symmetry ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 19
Author(s):  
Byeowool Kim ◽  
Yongik Yoon
Keyword(s):  
The Internet ◽  
Fake News ◽  
Mobile Environment ◽  
Sharing Value ◽  
Model Based ◽  
Blockchain Technology ◽  
Reasonable Alternative ◽  
Proposed Model ◽  
Revenue Structure ◽  
Sharing Space

The challenge that journalism is facing these days in the Internet mobile environment is greater than ever before. Journalism is losing its revenue structure to platform operators favoring a certain markets, and also the trust of its readers in light of fake news and infected news. To alleviate this situation, we propose a blockchain technology that is applicable to journalism in order to achieve decentralization as a reasonable alternative. The journalism model based on hybrid blockchain aims to achieve the following: the delivery of articles with sharing value, what we call proof of sharing; the distribution of roles of personalized agenda settings; and finally, the use of agora to collect public opinions. With all these, we attempt to resolve the issues with current journalism with our proposed model based on blockchain.

A Nueral Network-Based Mobile Architecture for Mobile Agents

2011 ◽  
pp. 285-296
Author(s):  
A. Kuppuswami
Keyword(s):  
Mobile Agents ◽  
Service Providers ◽  
Mobile Network ◽  
Area Network ◽  
Wide Area Network ◽  
Mobile Environment ◽  
Minimal Processing ◽  
Communication Techniques ◽  
Processing Power ◽  
Research Level

Wide area network (WAN) offers advantages like providing myriad services available on globally diversified computers with reasonably simple process. The ability to dynamically create networks offers the processing powers of various processors at our command. With the advent of protocols like SOAP and Web services, the consumption of services are more organized. In spite of various advances in communication techniques, the consumption of services through mobile gadgets is still only at the research level. The major impedances in implementing such systems on a mobile network are the latency factor, abrupt disconnection in service, lower bandwidth and minimal processing power. The mobile agent’s paradigm proves to be an effective solution to various issues raised. It has received serious attention in the last decade and several systems based on this paradigm have been proposed and built. All such systems have been designed for a static network, where the service providers and the requestors are connected to the server on a permanent basis. This chapter presents a new framework of managing the mobile environment and the participating nodes with active intelligent migration. The functioning of the mobile agents in such a scenario is also presented.

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