scholarly journals Comparing Rule Evaluation Metrics for the Evolutionary Discovery of Multi-relational Association Rules in the Semantic Web

2018 ◽  
pp. 289-305 ◽  
Author(s):  
Minh Duc Tran ◽  
Claudia d’Amato ◽  
Binh Thanh Nguyen ◽  
Andrea G. B. Tettamanzi
Keyword(s):  
Semantic Web ◽  
Association Rules ◽  
Evaluation Metrics ◽  
Rule Evaluation

On Reducing Redundancy in Mining Relational Association Rules from the Semantic Web

2008 ◽  
pp. 205-213 ◽  
Author(s):  
Joanna Józefowska ◽  
Agnieszka Ławrynowicz ◽  
Tomasz Łukaszewski
Keyword(s):  
Semantic Web ◽  
Association Rules

scholarly journals WINFRA: A Web-Based Platform for Semantic Data Retrieval and Data Analytics

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 2090
Author(s):  
Addi Ait-Mlouk ◽  
Xuan-Son Vu ◽  
Lili Jiang
Keyword(s):  
Semantic Web ◽  
Association Rules ◽  
Language Processing ◽  
Data Analytics ◽  
Data Retrieval ◽  
Heterogeneous Data ◽  
Graph Representation ◽  
Knowledge Graph ◽  
Multiple Sources ◽  
Semantic Data

Given the huge amount of heterogeneous data stored in different locations, it needs to be federated and semantically interconnected for further use. This paper introduces WINFRA, a comprehensive open-access platform for semantic web data and advanced analytics based on natural language processing (NLP) and data mining techniques (e.g., association rules, clustering, classification based on associations). The system is designed to facilitate federated data analysis, knowledge discovery, information retrieval, and new techniques to deal with semantic web and knowledge graph representation. The processing step integrates data from multiple sources virtually by creating virtual databases. Afterwards, the developed RDF Generator is built to generate RDF files for different data sources, together with SPARQL queries, to support semantic data search and knowledge graph representation. Furthermore, some application cases are provided to demonstrate how it facilitates advanced data analytics over semantic data and showcase our proposed approach toward semantic association rules.

scholarly journals A RELIABILITY EVALUATION SYSTEM OF ASSOCIATION RULES

2016 ◽  
Vol III-2 ◽  
pp. 53-60
Author(s):  
Jiangping Chen ◽  
Wanshu Feng ◽  
Minghai Luo
Keyword(s):  
Association Rules ◽  
Evaluation System ◽  
Three Dimensional ◽  
Reliability Evaluation ◽  
Data Sets ◽  
Simulation Data ◽  
Data Set ◽  
Actual Problem ◽  
Research Fields ◽  
Rule Evaluation

In mining association rules, the evaluation of the rules is a highly important work because it directly affects the usability and applicability of the output results of mining. In this paper, the concept of reliability was imported into the association rule evaluation. The reliability of association rules was defined as the accordance degree that reflects the rules of the mining data set. Such degree contains three levels of measurement, namely, accuracy, completeness, and consistency of rules. To show its effectiveness, the "accuracy-completeness-consistency" reliability evaluation system was applied to two extremely different data sets, namely, a basket simulation data set and a multi-source lightning data fusion. Results show that the reliability evaluation system works well in both simulation data set and the actual problem. The three-dimensional reliability evaluation can effectively detect the useless rules to be screened out and add the missing rules thereby improving the reliability of mining results. Furthermore, the proposed reliability evaluation system is applicable to many research fields; using the system in the analysis can facilitate obtainment of more accurate, complete, and consistent association rules.

Finding association rules in semantic web data

2012 ◽  
Vol 25 (1) ◽  
pp. 51-62 ◽  
Author(s):  
Victoria Nebot ◽  
Rafael Berlanga
Keyword(s):  
Semantic Web ◽  
Association Rules ◽  
Web Data

scholarly journals A RELIABILITY EVALUATION SYSTEM OF ASSOCIATION RULES

2016 ◽  
Vol III-2 ◽  
pp. 53-60
Author(s):  
Jiangping Chen ◽  
Wanshu Feng ◽  
Minghai Luo
Keyword(s):  
Association Rules ◽  
Evaluation System ◽  
Three Dimensional ◽  
Reliability Evaluation ◽  
Data Sets ◽  
Simulation Data ◽  
Data Set ◽  
Actual Problem ◽  
Research Fields ◽  
Rule Evaluation

In mining association rules, the evaluation of the rules is a highly important work because it directly affects the usability and applicability of the output results of mining. In this paper, the concept of reliability was imported into the association rule evaluation. The reliability of association rules was defined as the accordance degree that reflects the rules of the mining data set. Such degree contains three levels of measurement, namely, accuracy, completeness, and consistency of rules. To show its effectiveness, the "accuracy-completeness-consistency" reliability evaluation system was applied to two extremely different data sets, namely, a basket simulation data set and a multi-source lightning data fusion. Results show that the reliability evaluation system works well in both simulation data set and the actual problem. The three-dimensional reliability evaluation can effectively detect the useless rules to be screened out and add the missing rules thereby improving the reliability of mining results. Furthermore, the proposed reliability evaluation system is applicable to many research fields; using the system in the analysis can facilitate obtainment of more accurate, complete, and consistent association rules.

Sign in / Sign up

Export Citation Format

Share Document