Matches in SemOpenAlex for { <https://semopenalex.org/work/W2890217313> ?p ?o ?g. }
Showing items 1 to 48 of
48
with 100 items per page.
- W2890217313 endingPage "64" @default.
- W2890217313 startingPage "55" @default.
- W2890217313 abstract "Social Network (SN) is an online platform broadly used as communication tool by millions of users in order to build social relationships with others for knowledge point of view, career purposes and many more. Social Networks such as Twitter, Facebook, and LinkedIn have become the most leading tools on the web. Spam, floods the Internet with many copies of the same message and it can be manifest in numerous ways, it includes bulk messages, malicious links, fake friends, fraudulent reviews and personally identifiable information. The aim of this paper is to classify the tweets into spam and non-spam using Machine Learning and which will give the best results." @default.
- W2890217313 created "2018-09-27" @default.
- W2890217313 creator A5010674744 @default.
- W2890217313 creator A5022580522 @default.
- W2890217313 date "2018-09-18" @default.
- W2890217313 modified "2023-10-14" @default.
- W2890217313 title "Spam Detection Using Machine Learning in R" @default.
- W2890217313 cites W2158076717 @default.
- W2890217313 cites W2473377937 @default.
- W2890217313 cites W2474087371 @default.
- W2890217313 cites W2528518939 @default.
- W2890217313 cites W2567035653 @default.
- W2890217313 cites W2618766417 @default.
- W2890217313 doi "https://doi.org/10.1007/978-981-10-8681-6_7" @default.
- W2890217313 hasPublicationYear "2018" @default.
- W2890217313 type Work @default.
- W2890217313 sameAs 2890217313 @default.
- W2890217313 citedByCount "5" @default.
- W2890217313 countsByYear W28902173132021 @default.
- W2890217313 countsByYear W28902173132022 @default.
- W2890217313 crossrefType "book-chapter" @default.
- W2890217313 hasAuthorship W2890217313A5010674744 @default.
- W2890217313 hasAuthorship W2890217313A5022580522 @default.
- W2890217313 hasConcept C119857082 @default.
- W2890217313 hasConcept C154945302 @default.
- W2890217313 hasConcept C41008148 @default.
- W2890217313 hasConceptScore W2890217313C119857082 @default.
- W2890217313 hasConceptScore W2890217313C154945302 @default.
- W2890217313 hasConceptScore W2890217313C41008148 @default.
- W2890217313 hasLocation W28902173131 @default.
- W2890217313 hasOpenAccess W2890217313 @default.
- W2890217313 hasPrimaryLocation W28902173131 @default.
- W2890217313 hasRelatedWork W2961085424 @default.
- W2890217313 hasRelatedWork W3046775127 @default.
- W2890217313 hasRelatedWork W3107474891 @default.
- W2890217313 hasRelatedWork W3170094116 @default.
- W2890217313 hasRelatedWork W4205958290 @default.
- W2890217313 hasRelatedWork W4285260836 @default.
- W2890217313 hasRelatedWork W4286629047 @default.
- W2890217313 hasRelatedWork W4306321456 @default.
- W2890217313 hasRelatedWork W4306674287 @default.
- W2890217313 hasRelatedWork W4224009465 @default.
- W2890217313 isParatext "false" @default.
- W2890217313 isRetracted "false" @default.
- W2890217313 magId "2890217313" @default.
- W2890217313 workType "book-chapter" @default.