Matches in SemOpenAlex for { <https://semopenalex.org/work/W4380451161> ?p ?o ?g. }
Showing items 1 to 75 of
75
with 100 items per page.
- W4380451161 endingPage "782" @default.
- W4380451161 startingPage "773" @default.
- W4380451161 abstract "Nowadays a greater number of users participates is used to create new issues and discussion on social media that form into different kinds of groups such as Positive and negative comments. This paper is focused on a group of user’s discussions and specifies from which category they belong to. The user messages are parsed in the social media data then they identified network relationships and applied the data mining techniques to a group of different types of communities. The collection of objects is considered as similar or non-similar Clustering structures in unsupervised approaches. The aim of this paper is to develop clusters depending on features and their characteristics that are included in the proposed model. This work helps the system to categorize people into groups which also helps to identify people groups that are participated in discussions. This paper shows the clustering algorithms like K-Means, DBSCAN, and Agglomerative to cluster data and to find large streams of clustering community messages in social media data. This paper throws light on a novel use-case of communities and a proposed algorithm that shows the best clustering results. This application tells us which group of people saw the post and who gave their opinions on the post; by this, we can categorize the users." @default.
- W4380451161 created "2023-06-14" @default.
- W4380451161 creator A5007926056 @default.
- W4380451161 creator A5064255137 @default.
- W4380451161 creator A5092152922 @default.
- W4380451161 creator A5092152923 @default.
- W4380451161 creator A5092152924 @default.
- W4380451161 date "2023-01-01" @default.
- W4380451161 modified "2023-09-25" @default.
- W4380451161 title "Development and Validation of Unsupervised Machine Learning Clustering Techniques" @default.
- W4380451161 cites W2494476292 @default.
- W4380451161 cites W2783509132 @default.
- W4380451161 cites W2944310332 @default.
- W4380451161 cites W2955109214 @default.
- W4380451161 cites W2999401168 @default.
- W4380451161 cites W3035703585 @default.
- W4380451161 cites W3102444842 @default.
- W4380451161 doi "https://doi.org/10.1007/978-981-99-0769-4_67" @default.
- W4380451161 hasPublicationYear "2023" @default.
- W4380451161 type Work @default.
- W4380451161 citedByCount "0" @default.
- W4380451161 crossrefType "book-chapter" @default.
- W4380451161 hasAuthorship W4380451161A5007926056 @default.
- W4380451161 hasAuthorship W4380451161A5064255137 @default.
- W4380451161 hasAuthorship W4380451161A5092152922 @default.
- W4380451161 hasAuthorship W4380451161A5092152923 @default.
- W4380451161 hasAuthorship W4380451161A5092152924 @default.
- W4380451161 hasConcept C119857082 @default.
- W4380451161 hasConcept C124101348 @default.
- W4380451161 hasConcept C136764020 @default.
- W4380451161 hasConcept C154945302 @default.
- W4380451161 hasConcept C2522767166 @default.
- W4380451161 hasConcept C33704608 @default.
- W4380451161 hasConcept C39235581 @default.
- W4380451161 hasConcept C41008148 @default.
- W4380451161 hasConcept C46576248 @default.
- W4380451161 hasConcept C518677369 @default.
- W4380451161 hasConcept C73555534 @default.
- W4380451161 hasConcept C8038995 @default.
- W4380451161 hasConcept C92835128 @default.
- W4380451161 hasConcept C94124525 @default.
- W4380451161 hasConcept C94641424 @default.
- W4380451161 hasConceptScore W4380451161C119857082 @default.
- W4380451161 hasConceptScore W4380451161C124101348 @default.
- W4380451161 hasConceptScore W4380451161C136764020 @default.
- W4380451161 hasConceptScore W4380451161C154945302 @default.
- W4380451161 hasConceptScore W4380451161C2522767166 @default.
- W4380451161 hasConceptScore W4380451161C33704608 @default.
- W4380451161 hasConceptScore W4380451161C39235581 @default.
- W4380451161 hasConceptScore W4380451161C41008148 @default.
- W4380451161 hasConceptScore W4380451161C46576248 @default.
- W4380451161 hasConceptScore W4380451161C518677369 @default.
- W4380451161 hasConceptScore W4380451161C73555534 @default.
- W4380451161 hasConceptScore W4380451161C8038995 @default.
- W4380451161 hasConceptScore W4380451161C92835128 @default.
- W4380451161 hasConceptScore W4380451161C94124525 @default.
- W4380451161 hasConceptScore W4380451161C94641424 @default.
- W4380451161 hasLocation W43804511611 @default.
- W4380451161 hasOpenAccess W4380451161 @default.
- W4380451161 hasPrimaryLocation W43804511611 @default.
- W4380451161 hasRelatedWork W1595915502 @default.
- W4380451161 hasRelatedWork W1978862868 @default.
- W4380451161 hasRelatedWork W2374388475 @default.
- W4380451161 hasRelatedWork W2474073737 @default.
- W4380451161 hasRelatedWork W2574513950 @default.
- W4380451161 hasRelatedWork W3037830725 @default.
- W4380451161 hasRelatedWork W3111251285 @default.
- W4380451161 hasRelatedWork W4361799919 @default.
- W4380451161 hasRelatedWork W4380451161 @default.
- W4380451161 hasRelatedWork W2548341733 @default.
- W4380451161 isParatext "false" @default.
- W4380451161 isRetracted "false" @default.
- W4380451161 workType "book-chapter" @default.