scholarly journals Defining degree of semantic similarity using description logic tools

2021 ◽  
pp. 016-026
Author(s):  
O.V. Zakharova ◽  
Keyword(s):  
Semantic Similarity ◽  
Description Logic ◽  
Special Functions ◽  
Estimation Methods ◽  
Knowledge Based ◽  
Specific Concept ◽  
Semantic Proximity ◽  
Quantitative Indicators ◽  
The Impact

Establishing the semantic similarity of information is an integral part of the process of solving any information retrieval tasks, including tasks related to big data processing, discovery of semantic web services, categorization and classification of information, etc. The special functions to determine quantitative indicators of degree of se­mantic similarity of the information allow ranking the found information on its semantic proximity to the pur­po­se or search request/template. Forming such measures should take into account many aspects from the mea­nings of the matched concepts to the specifics of the business-task in which it is done. Usually, to construct such si­milarity functions, semantic ap­proaches are combined with structural ones, which provide syntactic comparison of concepts descriptions. This allows to do descriptions of the concepts more detail, and the impact of syntactic matching can be significantly reduced by using more expressive descriptive logics to represent information and by moving the focus to semantic properties. Today, DL-ontologies are the most developed tools for representing semantics, and the mechanisms of reasoning of descriptive logics (DL) provide the possibility of logical inference. Most of the estimates presented in this paper are based on basic DLs that support only the intersection constructor, but the described approaches can be applied to any DL that provides basic reasoning services. This article contains the analysis of existing approaches, models and measures based on descriptive logics. Classification of the estimation methods both on the levels of defining similarity and the matching types is proposed. The main attention is paid to establishing the similarity between concepts (conceptual level models). The task of establishing the value of similarity between instances and between concept and instance consists of finding the most specific concept for the instance / instances and evaluating the similarity between the concepts. The term of existential similarity is introduced. In this paper the examples of applying certain types of measures to evaluate the degree of semantic similarity of notions and/or knowledge based on the geometry ontology is demonstrated.

scholarly journals Defining degree of semantic similarity using description logic tools

2021 ◽  
pp. 024-033
Author(s):  
O.V. Zakharova
Keyword(s):  
Semantic Similarity ◽  
Description Logic ◽  
Special Functions ◽  
Estimation Methods ◽  
Knowledge Based ◽  
Specific Concept ◽  
Semantic Proximity ◽  
Quantitative Indicators ◽  
The Impact

Establishing the semantic similarity of information is an integral part of the process of solving any information retrieval tasks, including tasks related to big data processing, discovery of semantic web services, categorization and classification of information, etc. The special functions to determine quantitative indicators of degree of semantic similarity of the information allow ranking the found information on its semantic proximity to the purpose or search request/template. Forming such measures should take into account many aspects from the meanings of the matched concepts to the specifics of the business-task in which it is done. Usually, to construct such similarity functions, semantic approaches are combined with structural ones, which provide syntactic comparison of concepts descriptions. This allows to do descriptions of the concepts more detail, and the impact of syntactic matching can be significantly reduced by using more expressive descriptive logics to represent information and by moving the focus to semantic properties. Today, DL-ontologies are the most developed tools for representing semantics, and the mechanisms of reasoning of descriptive logics (DL) provide the possibility of logical inference. Most of the estimates presented in this paper are based on basic DLs that support only the intersection constructor, but the described approaches can be applied to any DL that provides basic reasoning services. This article contains the analysis of existing approaches, models and measures based on descriptive logics. Classification of the estimation methods both on the levels of defining similarity and the matching types is proposed. The main attention is paid to establishing the similarity between concepts (conceptual level models). The task of establishing the value of similarity between instances and between concept and instance consists of finding the most specific concept for the instance / instances and evaluating the similarity between the concepts. The term of existential similarity is introduced. In this paper the examples of applying certain types of measures to evaluate the degree of semantic similarity of notions and/or knowledge based on the geometry ontology is demonstrated.

scholarly journals Accounting, accountability, social media and big data: revolution or hype?

2017 ◽  
Vol 30 (4) ◽  
pp. 762-776 ◽  
Author(s):  
Michela Arnaboldi ◽  
Cristiano Busco ◽  
Suresh Cuganesan
Keyword(s):  
Social Media ◽  
Big Data ◽  
Future Research ◽  
Data Governance ◽  
Content Type ◽  
Knowledge Based ◽  
Decision Making Processes ◽  
Key Aspects ◽  
The Impact

Purpose The purpose of this paper is to outline an agenda for researching the relationship between technology-enabled networks – such as social media and big data – and the accounting function. In doing so, it links the contents of an unfolding area research with the papers published in this special issue of Accounting, Auditing and Accountability Journal. Design/methodology/approach The paper surveys the existing literature, which is still in its infancy, and proposes ways in which to frame early and future research. The intention is not to offer a comprehensive review, but to stimulate and conversation. Findings The authors review several existing studies exploring technology-enabled networks and highlight some of the key aspects featuring social media and big data, before offering a classification of existing research efforts, as well as opportunities for future research. Three areas of investigation are identified: new performance indicators based on social media and big data; governance of social media and big data information resources; and, finally, social media and big data’s alteration of information and decision-making processes. Originality/value The authors are currently experiencing a technological revolution that will fundamentally change the way in which organisations, as well as individuals, operate. It is claimed that many knowledge-based jobs are being automated, as well as others transformed with, for example, data scientists ready to replace even the most qualified accountants. But, of course, similar claims have been made before and therefore, as academics, the authors are called upon to explore the impact of these technology-enabled networks further. This paper contributes by starting a debate and speculating on the possible research agendas ahead.

scholarly journals IMPACT OF POLARIMETRIC SAR SPECKLE REDUCTION ON CLASSIFICATION OF AGRICULTURE LANDS

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 379-385
Author(s):  
R. Farhadiani ◽  
S. Homayouni ◽  
A. Safari
Keyword(s):  
Speckle Reduction ◽  
Support Vector ◽  
Svm Classifier ◽  
Comparison Study ◽  
Polarimetric Synthetic Aperture Radar ◽  
Processing Step ◽  
Reduction Methods ◽  
Quantitative Indicators ◽  
The Impact

Abstract. Presence of speckle in the Polarimetric Synthetic Aperture Radar (PolSAR) images could decrease the performance of information extraction applications such as classification, segmentation, change detection, etc. Hence, an essential pre-processing step named de-speckling is needed to suppress this granular noise-like phenomenon from the PolSAR images. In this paper, a comparison study is conducted between several new PolSAR speckle reduction methods such as POSSC, PNGF, and ANLM. For this comparison, a 4-look L-band AIRSAR NASA/JPL PolSAR dataset that obtained over an agriculture land from Flevoland, Netherlands, was employed. The de-speckling assessment was completed based on some no-reference quantitative indicators. All the de-speckling methods were evaluated in terms of speckle reduction form homogeneous areas, details, and radiometric preservation, and retaining the polarimetric information. Furthermore, the impact of PolSAR de-speckling on classification was evaluated. For this purpose, Support Vector Machine (SVM) classifier was used to classify H/A/Alpha decomposition. Experimental results showed that the ANLM method was better to suppress the speckle, followed by the PNGF method. Also, the classification results showed that a proper PolSAR de-speckling could effectively increase the classification accuracy. The improvement of the Overall Accuracy based on de-speckling using the ANLM method was approximately 22% and 13% higher than the POSSC and PNGF methods, respectively.

scholarly journals ASSESSMENT OF RELIABILITY OF THE DRIVER – CAR – ROAD – ENVIRONMENT (DCRЕ) SYSTEM IN MOUNTAIN CONDITIONS

2020 ◽  
Vol 20 (1) ◽  
pp. 38-46
Author(s):  
S. S. Saydulozoda ◽  
◽  
K. T. Mambetalin ◽  
A. M. Umirzokov ◽  
U. M. Mullaboev ◽  
...  
Keyword(s):  
Periodic Function ◽  
Estimation Methods ◽  
Factors Affecting ◽  
External Influences ◽  
Detailed Classification ◽  
Stable Frequency ◽  
Probabilistic Character ◽  
Probabilistic Nature ◽  
The Impact

The article provides an assessment of the factors affecting the reliability of the DCRE system in mountain conditions. A more detailed classification of factors affecting the reliability of the DCRE system in mountain conditions is given for such groups of features as design and technological, operational and road-climatic. In addition, the article gives a classification of factors affecting the reliability of the DCRE system in mountain conditions based on controllability. In both classifications, particular importance is given to such factors as altitude, the reliability structure of the elements of the DCRE system, the reliability structure of the elements of the car, the subsystems of the DCRE system, the probabilistic nature of the influence of external influences on the elements of the car, the types and frequency of maneuvers, their dynamism, etc. The specifics of the influence of the main factors determining the reliability and durability of heavy-duty mining car in difficult and extreme conditions of cargo transportation in mountain conditions are analyzed and justified. To assess the influence of the stochastic nature of external influences that determine the dynamics of the interaction of the car with the roadway, depending on the sample size, the nature of the process, the state of the object under study and other factors, the most rational methods based on probability theory are substantiated. Three of them are recommended for an adequate assessment of the impact of external influences on the output indicators of the car, in particular to assess the process of interaction of the car with the roadbed, which has a probabilistic character. Among the recommended estimation methods are included such methods as the method of approximating the external load with a periodic function such as a sinusoid with certain values of the amplitude and period of oscillation, the method of expanding the periodic function in Fourier series and the probabilistic-statistical method, which is based on taking into account the action of many random factors characterized by stable frequency.

On Scientific Realism and Instrumentalism in Manoeuvring Target Modelling and Tracking

2011 ◽  
Vol 57 (2) ◽  
pp. 199-208 ◽  
Author(s):  
Mirosław Sankowski
Keyword(s):  
State Estimation ◽  
Scientific Realism ◽  
Traffic Control ◽  
Moving Objects ◽  
Basic Problem ◽  
Estimation Methods ◽  
Tracking Filter ◽  
The Impact ◽  
Made In

On Scientific Realism and Instrumentalism in Manoeuvring Target Modelling and Tracking The basic problem of tracking manoeuvring moving objects (e.g. aircrafts, ships) lies in unpredictability of object manoeuvres, with respect to the time of occurrence, duration and the type of trajectory. In this paper most representative methods of modelling and state estimation techniques applied to Manoeuvring Target Tracking (MTT) are briefly reviewed. Classification of existing approaches is made in the context of realistic and instrumentalistic paradigms of the philosophy of science. A practical example is also given that shows the impact of selecting models and estimation methods on the performance of the tracking filter for Air Traffic Control (ATC) radar.

scholarly journals Input and Output Indicators of the Higher Education Institutions for Quality of Life in Portugal

2021 ◽  
Vol 10 (2) ◽  
pp. 299
Author(s):  
Ana Luísa Fonseca Rodrigues ◽  
Luísa Cerdeira ◽  
Tomás Patrocínio ◽  
Belmiro Cabrito ◽  
Pedro Mucharreira
Keyword(s):  
Quality Of Life ◽  
Higher Education ◽  
Higher Education Institutions ◽  
Education Policies ◽  
Knowledge Based ◽  
Higher Education Policies ◽  
Definition Of ◽  
Quantitative Indicators ◽  
The Impact

Higher education institutions (HEIs) contribute substantially to the quality of life (QoL) of the regions where they operate and to the progress and sustainable development of a country. This research intends to have an innovative approach in the study of the HEIs’ impact on the QoL of regions by taking into consideration both qualitative and quantitative indicators. This study aims to identify, collect and systematize indicators that can be used to measure the impact of HEIs on QoL: on the demand-side based on expenditure (inputs) and the knowledge-based supply side (outputs). For accomplishing this, the authors carried out a literature review, an analysis of available statistical data in Portugal and interviews for the analysis and consolidation of indicators. The results will facilitate the measurement of the HEIs’ impact on QoL and regions and allow the elaboration of a matrix of reliable indicators, which will hopefully assist in the definition of new higher education policies.

The Impact of Missing and Error-Prone Auxiliary Information on Sparse-Matrix Sub-Population Parameter Estimates

Methodology ◽  
2015 ◽  
Vol 11 (3) ◽  
pp. 89-99 ◽  
Author(s):  
Leslie Rutkowski ◽  
Yan Zhou
Keyword(s):  
Sparse Matrix ◽  
Small Body ◽  
Auxiliary Information ◽  
Poor Quality ◽  
Quality Data ◽  
Estimation Methods ◽  
Parameter Estimates ◽  
Population Parameter ◽  
Conditioning Model ◽  
The Impact

Abstract. Given a consistent interest in comparing achievement across sub-populations in international assessments such as TIMSS, PIRLS, and PISA, it is critical that sub-population achievement is estimated reliably and with sufficient precision. As such, we systematically examine the limitations to current estimation methods used by these programs. Using a simulation study along with empirical results from the 2007 cycle of TIMSS, we show that a combination of missing and misclassified data in the conditioning model induces biases in sub-population achievement estimates, the magnitude and degree to which can be readily explained by data quality. Importantly, estimated biases in sub-population achievement are limited to the conditioning variable with poor-quality data while other sub-population achievement estimates are unaffected. Findings are generally in line with theory on missing and error-prone covariates. The current research adds to a small body of literature that has noted some of the limitations to sub-population estimation.

Use of Nutrition Information and Understanding of “Percent Daily Value” on Nutrition Facts Tables: Evaluating the Impact of a National Public Education Campaign among Youth and Young Adults in Canada

2019 ◽  
Vol 80 (4) ◽  
pp. 200-204 ◽  
Author(s):  
Brittany Cormier ◽  
Lana Vanderlee ◽  
David Hammond
Keyword(s):  
Population Level ◽  
Correct Recall ◽  
Nutrition Information ◽  
Education Campaign ◽  
Knowledge Based ◽  
Public Education Campaign ◽  
Youth And Young Adults ◽  
Campaign Message ◽  
Health Canada ◽  
The Impact

Purpose: In 2010, Health Canada implemented a national campaign to improve understanding of “percent daily value” (%DV) in Nutrition Facts Tables (NFTs). This study examined sources of nutrition information and knowledge of %DV information communicated in the campaign. Methods: Respondents aged 16–30 years completed the Canada Food Study in 2016 (n = 2665). Measures included sources of nutrition information, NFT use, and %DV knowledge based on the campaign message (“5% DV or less is a little; 15% DV or more is a lot”). A logistic regression examined correlates of providing “correct” responses to %DV questions related to the campaign messaging. Results: Overall, 7.2% (n = 191) respondents correctly indicated that 5% is “a little”, and 4.3% (n = 115) correctly indicated 15% DV was “a lot”. Only 4.0% (n = 107) correctly answered both. Correct recall of %DV amounts was not associated with number of information sources reported, but was greater among those who were female, were younger, and reported greater NFT understanding and serving size information use (P < 0.05 for all). Conclusions: Results show low awareness of messaging from the Nutrition Facts Education Campaign among young Canadians. Such a mass media campaign may be insufficient on its own to enhance population-level understanding of %DV.

ON THE CLASSIFICATION OF DIGITAL TECHNOLOGIES IN CIVIL PROCESS

2019 ◽  
pp. 27-35
Author(s):  
Alexandr Neznamov
Keyword(s):  
Information Processing ◽  
Scientific Community ◽  
Digital Technologies ◽  
Significant Feature ◽  
Legal Proceedings ◽  
Civil Process ◽  
Civil Proceedings ◽  
Processing Information ◽  
The Impact

Digital technologies are no longer the future but are the present of civil proceedings. That is why any research in this direction seems to be relevant. At the same time, some of the fundamental problems remain unattended by the scientific community. One of these problems is the problem of classification of digital technologies in civil proceedings. On the basis of instrumental and genetic approaches to the understanding of digital technologies, it is concluded that their most significant feature is the ability to mediate the interaction of participants in legal proceedings with information; their differentiating feature is the function performed by a particular technology in the interaction with information. On this basis, it is proposed to distinguish the following groups of digital technologies in civil proceedings: a) technologies of recording, storing and displaying (reproducing) information, b) technologies of transferring information, c) technologies of processing information. A brief description is given to each of the groups. Presented classification could serve as a basis for a more systematic discussion of the impact of digital technologies on the essence of civil proceedings. Particularly, it is pointed out that issues of recording, storing, reproducing and transferring information are traditionally more «technological» for civil process, while issues of information processing are more conceptual.

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