Matches in SemOpenAlex for { <https://semopenalex.org/work/W4308581010> ?p ?o ?g. }
Showing items 1 to 89 of
89
with 100 items per page.
- W4308581010 endingPage "2344" @default.
- W4308581010 startingPage "2344" @default.
- W4308581010 abstract "Big data technology has gained attention in all fields, particularly with regard to research and financial institutions. This technology has changed the world tremendously. Researchers and data scientists are currently working on its applicability in different domains such as health care, medicine, and the stock market, among others. The data being generated at an unexpected pace from multiple sources like social media, health care contexts, and Internet of things have given rise to big data. Management and processing of big data represent a challenge for researchers and data scientists, as there is heterogeneity and ambiguity. Heterogeneity is considered to be an important characteristic of big data. The analysis of heterogeneous data is a very complex task as it involves the compilation, storage, and processing of varied data based on diverse patterns and rules. The proposed research has focused on the heterogeneity problem in big data. This research introduces the hybrid support vector machine (H-SVM) classifier, which uses the support vector machine as a base. In the proposed algorithm, the heterogeneous Euclidean overlap metric (HEOM) and Euclidean distance are introduced to form clusters and classify the data on the basis of ordinal and nominal values. The performance of the proposed learning classifier is compared with linear SVM, random forest, and k-nearest neighbor. The proposed algorithm attained the highest accuracy as compared to other classifiers." @default.
- W4308581010 created "2022-11-12" @default.
- W4308581010 creator A5003548007 @default.
- W4308581010 creator A5004467455 @default.
- W4308581010 creator A5018679386 @default.
- W4308581010 creator A5059777297 @default.
- W4308581010 date "2022-11-08" @default.
- W4308581010 modified "2023-10-14" @default.
- W4308581010 title "A Hybrid Support Vector Machine Algorithm for Big Data Heterogeneity Using Machine Learning" @default.
- W4308581010 cites W1898843043 @default.
- W4308581010 cites W1989575944 @default.
- W4308581010 cites W2005624335 @default.
- W4308581010 cites W2019759670 @default.
- W4308581010 cites W2045621032 @default.
- W4308581010 cites W2046858834 @default.
- W4308581010 cites W2072750586 @default.
- W4308581010 cites W2125126592 @default.
- W4308581010 cites W2126623642 @default.
- W4308581010 cites W2131742948 @default.
- W4308581010 cites W2149140091 @default.
- W4308581010 cites W2157954477 @default.
- W4308581010 cites W2159588611 @default.
- W4308581010 cites W2161713006 @default.
- W4308581010 cites W2163952039 @default.
- W4308581010 cites W2413899610 @default.
- W4308581010 cites W2497722157 @default.
- W4308581010 cites W2576683119 @default.
- W4308581010 cites W2618637662 @default.
- W4308581010 cites W2776723052 @default.
- W4308581010 cites W2807319534 @default.
- W4308581010 cites W4233518571 @default.
- W4308581010 doi "https://doi.org/10.3390/sym14112344" @default.
- W4308581010 hasPublicationYear "2022" @default.
- W4308581010 type Work @default.
- W4308581010 citedByCount "2" @default.
- W4308581010 countsByYear W43085810102023 @default.
- W4308581010 crossrefType "journal-article" @default.
- W4308581010 hasAuthorship W4308581010A5003548007 @default.
- W4308581010 hasAuthorship W4308581010A5004467455 @default.
- W4308581010 hasAuthorship W4308581010A5018679386 @default.
- W4308581010 hasAuthorship W4308581010A5059777297 @default.
- W4308581010 hasBestOaLocation W43085810101 @default.
- W4308581010 hasConcept C119857082 @default.
- W4308581010 hasConcept C120174047 @default.
- W4308581010 hasConcept C12267149 @default.
- W4308581010 hasConcept C124101348 @default.
- W4308581010 hasConcept C13280743 @default.
- W4308581010 hasConcept C154945302 @default.
- W4308581010 hasConcept C169258074 @default.
- W4308581010 hasConcept C199360897 @default.
- W4308581010 hasConcept C205649164 @default.
- W4308581010 hasConcept C2777526511 @default.
- W4308581010 hasConcept C2780522230 @default.
- W4308581010 hasConcept C41008148 @default.
- W4308581010 hasConcept C75684735 @default.
- W4308581010 hasConceptScore W4308581010C119857082 @default.
- W4308581010 hasConceptScore W4308581010C120174047 @default.
- W4308581010 hasConceptScore W4308581010C12267149 @default.
- W4308581010 hasConceptScore W4308581010C124101348 @default.
- W4308581010 hasConceptScore W4308581010C13280743 @default.
- W4308581010 hasConceptScore W4308581010C154945302 @default.
- W4308581010 hasConceptScore W4308581010C169258074 @default.
- W4308581010 hasConceptScore W4308581010C199360897 @default.
- W4308581010 hasConceptScore W4308581010C205649164 @default.
- W4308581010 hasConceptScore W4308581010C2777526511 @default.
- W4308581010 hasConceptScore W4308581010C2780522230 @default.
- W4308581010 hasConceptScore W4308581010C41008148 @default.
- W4308581010 hasConceptScore W4308581010C75684735 @default.
- W4308581010 hasIssue "11" @default.
- W4308581010 hasLocation W43085810101 @default.
- W4308581010 hasLocation W43085810102 @default.
- W4308581010 hasOpenAccess W4308581010 @default.
- W4308581010 hasPrimaryLocation W43085810101 @default.
- W4308581010 hasRelatedWork W1996541855 @default.
- W4308581010 hasRelatedWork W2985924212 @default.
- W4308581010 hasRelatedWork W3014300295 @default.
- W4308581010 hasRelatedWork W3195168932 @default.
- W4308581010 hasRelatedWork W3195610867 @default.
- W4308581010 hasRelatedWork W4308191010 @default.
- W4308581010 hasRelatedWork W4321636153 @default.
- W4308581010 hasRelatedWork W4327511089 @default.
- W4308581010 hasRelatedWork W4377964522 @default.
- W4308581010 hasRelatedWork W4381414210 @default.
- W4308581010 hasVolume "14" @default.
- W4308581010 isParatext "false" @default.
- W4308581010 isRetracted "false" @default.
- W4308581010 workType "article" @default.