Data analytics for social microblogging platforms
<B>Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites</b><br>1. Introduction to Microblogging Sites<br>2. Data structures and data storage<br>3. Data Collection using Twitter API<br><br><b&...
Ausführliche Beschreibung
Autor*in: |
Dutta, Soumi - 1986- [verfasserIn] Das, Asit Kumar [verfasserIn] Ghosh, Saptarshi [verfasserIn] Samanta, Debabrata - 1987- [verfasserIn] |
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Format: |
E-Book |
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Sprache: |
Englisch |
Erschienen: |
Amsterdam: Academic Press ; 2022 |
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Schlagwörter: |
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Umfang: |
1 Online-Ressource (1 online resource) |
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Reihe: |
Hybrid computational intelligence for pattern analysis and understanding |
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Links: | |
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ISBN: |
978-0-323-97230-7 0-323-97230-6 |
Katalog-ID: |
1839111615 |
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520 | |a <B>Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites</b><br>1. Introduction to Microblogging Sites<br>2. Data structures and data storage<br>3. Data Collection using Twitter API<br><br><b>Section 2: Microblogging dataset Applications and Implications</b><br>4. Brief overview of existing algorithms and Applications<br>Attribute Selection Methods -- Filter Method, Wrapper Method, Other attribute selection algorithms<br>5. Spam detection -- Spam detection in OSM -- Attribute selection for spam detection<br>6. Summarization -- Automatic Document Summarization, Summarization of microblogs, Comparing algorithms for microblog summarization, Summarization Validation<br>7. Cluster Analysis, Clustering Algorithms, Partition based Clustering, Hierarchical Clustering, Density-based Clustering, Graph clustering algorithms, Cluster Validation Indices, Clustering in Online Social Microblogging Sites<br><br><b>Section 3: Attribute Selection to Improve Spam Classification</b><br>8. Introduction of Attribute Selection to Improve Spam Classification<br>9. Attribute Selection Based in Basics of Rough Set Theory and Attribute selection algorithm.<br>10. Experimental Dataset Description<br>11. Evaluating performance and Evaluation measures<br>12. Fake news, scams, recruiting by terrorist or criminal organizations<br><br><b>Section 4: Microblog Summarization</b><br>13. Introduction of Microblog Summarization<br>14. Base summarization algorithms<br>15. Unsupervised ensemble summarization approach<br>16. Supervised ensemble summarisation approach<br>17. Experiments and results and Performance analysis<br>18. Demonstrating summarization examples<br><br><b>Section 5: Microblog Clustering</b><br>19. Introduction of Microblog Clustering<br>Experimental Dataset -- will be posted on Mendeley and link included at end of Chapter 19<br>20. Graph Based Clustering Technique<br>21. Genetic Algorithm based Clustering<br>22. Clustering based on Feature Selection<br>23. Clustering Microblogs using Dimensionality Reduction<br>24. Evaluating performance and result Analysis<br><br><b>Section 6: Conclusion and Future Directions on Social Microblogging Sites</b> | ||
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9780323972307 e-book 978-0-323-97230-7 0323972306 0-323-97230-6 (DE-627)1839111615 (DE-599)KEP089719875 (ELSEVIER)on1352014706 (EBP)089719875 DE-627 eng DE-627 rda eng XA-NL TK5105.8884 006.752 Dutta, Soumi 1986- verfasserin aut Data analytics for social microblogging platforms Soumi Dutta, Asit Kumar Das, Saptarshi Ghosh, Debabrata Samanta Amsterdam Academic Press 2022 1 Online-Ressource (1 online resource) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hybrid computational intelligence for pattern analysis and understanding <B>Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites</b><br>1. Introduction to Microblogging Sites<br>2. Data structures and data storage<br>3. Data Collection using Twitter API<br><br><b>Section 2: Microblogging dataset Applications and Implications</b><br>4. Brief overview of existing algorithms and Applications<br>Attribute Selection Methods -- Filter Method, Wrapper Method, Other attribute selection algorithms<br>5. Spam detection -- Spam detection in OSM -- Attribute selection for spam detection<br>6. Summarization -- Automatic Document Summarization, Summarization of microblogs, Comparing algorithms for microblog summarization, Summarization Validation<br>7. Cluster Analysis, Clustering Algorithms, Partition based Clustering, Hierarchical Clustering, Density-based Clustering, Graph clustering algorithms, Cluster Validation Indices, Clustering in Online Social Microblogging Sites<br><br><b>Section 3: Attribute Selection to Improve Spam Classification</b><br>8. Introduction of Attribute Selection to Improve Spam Classification<br>9. Attribute Selection Based in Basics of Rough Set Theory and Attribute selection algorithm.<br>10. Experimental Dataset Description<br>11. Evaluating performance and Evaluation measures<br>12. Fake news, scams, recruiting by terrorist or criminal organizations<br><br><b>Section 4: Microblog Summarization</b><br>13. Introduction of Microblog Summarization<br>14. Base summarization algorithms<br>15. Unsupervised ensemble summarization approach<br>16. Supervised ensemble summarisation approach<br>17. Experiments and results and Performance analysis<br>18. Demonstrating summarization examples<br><br><b>Section 5: Microblog Clustering</b><br>19. Introduction of Microblog Clustering<br>Experimental Dataset -- will be posted on Mendeley and link included at end of Chapter 19<br>20. Graph Based Clustering Technique<br>21. Genetic Algorithm based Clustering<br>22. Clustering based on Feature Selection<br>23. Clustering Microblogs using Dimensionality Reduction<br>24. Evaluating performance and result Analysis<br><br><b>Section 6: Conclusion and Future Directions on Social Microblogging Sites</b> Microblogs Data processing Das, Asit Kumar verfasserin aut Ghosh, Saptarshi verfasserin aut Samanta, Debabrata 1987- verfasserin aut 9780323972307 e-book 0323972306 e-book 9780323917858 (pbk.) 9780323972307 ePub ebook 9780323917858 Erscheint auch als Druck-Ausgabe 9780323917858 https://www.sciencedirect.com/science/book/9780323917858 X:ELSEVIER Verlag lizenzpflichtig GBV-33-Freedom 2023 ZDB-33-ESD ZDB-33-ECMC 2023 BSZ-33-ESD-L1FH GBV_ILN_23 ISIL_DE-830 SYSFLAG_1 GBV_KXP GBV_ILN_105 ISIL_DE-841 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2057 ISIL_DE-L189 BO 045F 006.752 23 01 0830 4297267039 olr-else2 i z 25-03-23 105 01 0841 4497134288 OLR-ELV-TEST Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Testzugang ZHB Lübeck z 07-03-24 370 01 4370 4540274325 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2057 01 DE-L189 4467490302 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 23 01 0830 https://www.sciencedirect.com/science/book/9780323917858 105 01 0841 https://www.sciencedirect.com/science/book/9780323917858 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780323917858 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780323917858 23 01 0830 olr-else2 105 01 0841 OLR-ELV-TEST 370 01 4370 EBS Elsevier |
spelling |
9780323972307 e-book 978-0-323-97230-7 0323972306 0-323-97230-6 (DE-627)1839111615 (DE-599)KEP089719875 (ELSEVIER)on1352014706 (EBP)089719875 DE-627 eng DE-627 rda eng XA-NL TK5105.8884 006.752 Dutta, Soumi 1986- verfasserin aut Data analytics for social microblogging platforms Soumi Dutta, Asit Kumar Das, Saptarshi Ghosh, Debabrata Samanta Amsterdam Academic Press 2022 1 Online-Ressource (1 online resource) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hybrid computational intelligence for pattern analysis and understanding <B>Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites</b><br>1. Introduction to Microblogging Sites<br>2. Data structures and data storage<br>3. Data Collection using Twitter API<br><br><b>Section 2: Microblogging dataset Applications and Implications</b><br>4. Brief overview of existing algorithms and Applications<br>Attribute Selection Methods -- Filter Method, Wrapper Method, Other attribute selection algorithms<br>5. Spam detection -- Spam detection in OSM -- Attribute selection for spam detection<br>6. Summarization -- Automatic Document Summarization, Summarization of microblogs, Comparing algorithms for microblog summarization, Summarization Validation<br>7. Cluster Analysis, Clustering Algorithms, Partition based Clustering, Hierarchical Clustering, Density-based Clustering, Graph clustering algorithms, Cluster Validation Indices, Clustering in Online Social Microblogging Sites<br><br><b>Section 3: Attribute Selection to Improve Spam Classification</b><br>8. Introduction of Attribute Selection to Improve Spam Classification<br>9. Attribute Selection Based in Basics of Rough Set Theory and Attribute selection algorithm.<br>10. Experimental Dataset Description<br>11. Evaluating performance and Evaluation measures<br>12. Fake news, scams, recruiting by terrorist or criminal organizations<br><br><b>Section 4: Microblog Summarization</b><br>13. Introduction of Microblog Summarization<br>14. Base summarization algorithms<br>15. Unsupervised ensemble summarization approach<br>16. Supervised ensemble summarisation approach<br>17. Experiments and results and Performance analysis<br>18. Demonstrating summarization examples<br><br><b>Section 5: Microblog Clustering</b><br>19. Introduction of Microblog Clustering<br>Experimental Dataset -- will be posted on Mendeley and link included at end of Chapter 19<br>20. Graph Based Clustering Technique<br>21. Genetic Algorithm based Clustering<br>22. Clustering based on Feature Selection<br>23. Clustering Microblogs using Dimensionality Reduction<br>24. Evaluating performance and result Analysis<br><br><b>Section 6: Conclusion and Future Directions on Social Microblogging Sites</b> Microblogs Data processing Das, Asit Kumar verfasserin aut Ghosh, Saptarshi verfasserin aut Samanta, Debabrata 1987- verfasserin aut 9780323972307 e-book 0323972306 e-book 9780323917858 (pbk.) 9780323972307 ePub ebook 9780323917858 Erscheint auch als Druck-Ausgabe 9780323917858 https://www.sciencedirect.com/science/book/9780323917858 X:ELSEVIER Verlag lizenzpflichtig GBV-33-Freedom 2023 ZDB-33-ESD ZDB-33-ECMC 2023 BSZ-33-ESD-L1FH GBV_ILN_23 ISIL_DE-830 SYSFLAG_1 GBV_KXP GBV_ILN_105 ISIL_DE-841 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2057 ISIL_DE-L189 BO 045F 006.752 23 01 0830 4297267039 olr-else2 i z 25-03-23 105 01 0841 4497134288 OLR-ELV-TEST Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Testzugang ZHB Lübeck z 07-03-24 370 01 4370 4540274325 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2057 01 DE-L189 4467490302 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 23 01 0830 https://www.sciencedirect.com/science/book/9780323917858 105 01 0841 https://www.sciencedirect.com/science/book/9780323917858 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780323917858 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780323917858 23 01 0830 olr-else2 105 01 0841 OLR-ELV-TEST 370 01 4370 EBS Elsevier |
allfields_unstemmed |
9780323972307 e-book 978-0-323-97230-7 0323972306 0-323-97230-6 (DE-627)1839111615 (DE-599)KEP089719875 (ELSEVIER)on1352014706 (EBP)089719875 DE-627 eng DE-627 rda eng XA-NL TK5105.8884 006.752 Dutta, Soumi 1986- verfasserin aut Data analytics for social microblogging platforms Soumi Dutta, Asit Kumar Das, Saptarshi Ghosh, Debabrata Samanta Amsterdam Academic Press 2022 1 Online-Ressource (1 online resource) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hybrid computational intelligence for pattern analysis and understanding <B>Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites</b><br>1. Introduction to Microblogging Sites<br>2. Data structures and data storage<br>3. Data Collection using Twitter API<br><br><b>Section 2: Microblogging dataset Applications and Implications</b><br>4. Brief overview of existing algorithms and Applications<br>Attribute Selection Methods -- Filter Method, Wrapper Method, Other attribute selection algorithms<br>5. Spam detection -- Spam detection in OSM -- Attribute selection for spam detection<br>6. Summarization -- Automatic Document Summarization, Summarization of microblogs, Comparing algorithms for microblog summarization, Summarization Validation<br>7. Cluster Analysis, Clustering Algorithms, Partition based Clustering, Hierarchical Clustering, Density-based Clustering, Graph clustering algorithms, Cluster Validation Indices, Clustering in Online Social Microblogging Sites<br><br><b>Section 3: Attribute Selection to Improve Spam Classification</b><br>8. Introduction of Attribute Selection to Improve Spam Classification<br>9. Attribute Selection Based in Basics of Rough Set Theory and Attribute selection algorithm.<br>10. Experimental Dataset Description<br>11. Evaluating performance and Evaluation measures<br>12. Fake news, scams, recruiting by terrorist or criminal organizations<br><br><b>Section 4: Microblog Summarization</b><br>13. Introduction of Microblog Summarization<br>14. Base summarization algorithms<br>15. Unsupervised ensemble summarization approach<br>16. Supervised ensemble summarisation approach<br>17. Experiments and results and Performance analysis<br>18. Demonstrating summarization examples<br><br><b>Section 5: Microblog Clustering</b><br>19. Introduction of Microblog Clustering<br>Experimental Dataset -- will be posted on Mendeley and link included at end of Chapter 19<br>20. Graph Based Clustering Technique<br>21. Genetic Algorithm based Clustering<br>22. Clustering based on Feature Selection<br>23. Clustering Microblogs using Dimensionality Reduction<br>24. Evaluating performance and result Analysis<br><br><b>Section 6: Conclusion and Future Directions on Social Microblogging Sites</b> Microblogs Data processing Das, Asit Kumar verfasserin aut Ghosh, Saptarshi verfasserin aut Samanta, Debabrata 1987- verfasserin aut 9780323972307 e-book 0323972306 e-book 9780323917858 (pbk.) 9780323972307 ePub ebook 9780323917858 Erscheint auch als Druck-Ausgabe 9780323917858 https://www.sciencedirect.com/science/book/9780323917858 X:ELSEVIER Verlag lizenzpflichtig GBV-33-Freedom 2023 ZDB-33-ESD ZDB-33-ECMC 2023 BSZ-33-ESD-L1FH GBV_ILN_23 ISIL_DE-830 SYSFLAG_1 GBV_KXP GBV_ILN_105 ISIL_DE-841 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2057 ISIL_DE-L189 BO 045F 006.752 23 01 0830 4297267039 olr-else2 i z 25-03-23 105 01 0841 4497134288 OLR-ELV-TEST Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Testzugang ZHB Lübeck z 07-03-24 370 01 4370 4540274325 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2057 01 DE-L189 4467490302 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 23 01 0830 https://www.sciencedirect.com/science/book/9780323917858 105 01 0841 https://www.sciencedirect.com/science/book/9780323917858 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780323917858 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780323917858 23 01 0830 olr-else2 105 01 0841 OLR-ELV-TEST 370 01 4370 EBS Elsevier |
allfieldsGer |
9780323972307 e-book 978-0-323-97230-7 0323972306 0-323-97230-6 (DE-627)1839111615 (DE-599)KEP089719875 (ELSEVIER)on1352014706 (EBP)089719875 DE-627 eng DE-627 rda eng XA-NL TK5105.8884 006.752 Dutta, Soumi 1986- verfasserin aut Data analytics for social microblogging platforms Soumi Dutta, Asit Kumar Das, Saptarshi Ghosh, Debabrata Samanta Amsterdam Academic Press 2022 1 Online-Ressource (1 online resource) Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Hybrid computational intelligence for pattern analysis and understanding <B>Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites</b><br>1. Introduction to Microblogging Sites<br>2. Data structures and data storage<br>3. Data Collection using Twitter API<br><br><b>Section 2: Microblogging dataset Applications and Implications</b><br>4. Brief overview of existing algorithms and Applications<br>Attribute Selection Methods -- Filter Method, Wrapper Method, Other attribute selection algorithms<br>5. Spam detection -- Spam detection in OSM -- Attribute selection for spam detection<br>6. Summarization -- Automatic Document Summarization, Summarization of microblogs, Comparing algorithms for microblog summarization, Summarization Validation<br>7. Cluster Analysis, Clustering Algorithms, Partition based Clustering, Hierarchical Clustering, Density-based Clustering, Graph clustering algorithms, Cluster Validation Indices, Clustering in Online Social Microblogging Sites<br><br><b>Section 3: Attribute Selection to Improve Spam Classification</b><br>8. Introduction of Attribute Selection to Improve Spam Classification<br>9. Attribute Selection Based in Basics of Rough Set Theory and Attribute selection algorithm.<br>10. Experimental Dataset Description<br>11. Evaluating performance and Evaluation measures<br>12. Fake news, scams, recruiting by terrorist or criminal organizations<br><br><b>Section 4: Microblog Summarization</b><br>13. Introduction of Microblog Summarization<br>14. Base summarization algorithms<br>15. Unsupervised ensemble summarization approach<br>16. Supervised ensemble summarisation approach<br>17. Experiments and results and Performance analysis<br>18. Demonstrating summarization examples<br><br><b>Section 5: Microblog Clustering</b><br>19. Introduction of Microblog Clustering<br>Experimental Dataset -- will be posted on Mendeley and link included at end of Chapter 19<br>20. Graph Based Clustering Technique<br>21. Genetic Algorithm based Clustering<br>22. Clustering based on Feature Selection<br>23. Clustering Microblogs using Dimensionality Reduction<br>24. Evaluating performance and result Analysis<br><br><b>Section 6: Conclusion and Future Directions on Social Microblogging Sites</b> Microblogs Data processing Das, Asit Kumar verfasserin aut Ghosh, Saptarshi verfasserin aut Samanta, Debabrata 1987- verfasserin aut 9780323972307 e-book 0323972306 e-book 9780323917858 (pbk.) 9780323972307 ePub ebook 9780323917858 Erscheint auch als Druck-Ausgabe 9780323917858 https://www.sciencedirect.com/science/book/9780323917858 X:ELSEVIER Verlag lizenzpflichtig GBV-33-Freedom 2023 ZDB-33-ESD ZDB-33-ECMC 2023 BSZ-33-ESD-L1FH GBV_ILN_23 ISIL_DE-830 SYSFLAG_1 GBV_KXP GBV_ILN_105 ISIL_DE-841 GBV_ILN_370 ISIL_DE-1373 GBV_ILN_2057 ISIL_DE-L189 BO 045F 006.752 23 01 0830 4297267039 olr-else2 i z 25-03-23 105 01 0841 4497134288 OLR-ELV-TEST Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Die Weitergabe an Dritte sowie systematisches Downloaden sind untersagt. Testzugang ZHB Lübeck z 07-03-24 370 01 4370 4540274325 EBS Elsevier Vervielfältigungen (z.B. Kopien, Downloads) sind nur von einzelnen Kapiteln oder Seiten und nur zum eigenen wissenschaftlichen Gebrauch erlaubt. Keine Weitergabe an Dritte. Kein systematisches Downloaden durch Robots. i z 20-06-24 2057 01 DE-L189 4467490302 00 --%%-- --%%-- --%%-- n Campuslizenz l01 24-01-24 23 01 0830 https://www.sciencedirect.com/science/book/9780323917858 105 01 0841 https://www.sciencedirect.com/science/book/9780323917858 370 01 4370 E-Book: Zugriff im HCU-Netz. Zugriff von außerhalb nur für HCU-Angehörige möglich https://www.sciencedirect.com/science/book/9780323917858 2057 01 DE-L189 HTWK-Zugang https://www.sciencedirect.com/science/book/9780323917858 23 01 0830 olr-else2 105 01 0841 OLR-ELV-TEST 370 01 4370 EBS Elsevier |
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Data analytics for social microblogging platforms |
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<B>Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites</b><br>1. Introduction to Microblogging Sites<br>2. Data structures and data storage<br>3. Data Collection using Twitter API<br><br><b>Section 2: Microblogging dataset Applications and Implications</b><br>4. Brief overview of existing algorithms and Applications<br>Attribute Selection Methods -- Filter Method, Wrapper Method, Other attribute selection algorithms<br>5. Spam detection -- Spam detection in OSM -- Attribute selection for spam detection<br>6. Summarization -- Automatic Document Summarization, Summarization of microblogs, Comparing algorithms for microblog summarization, Summarization Validation<br>7. Cluster Analysis, Clustering Algorithms, Partition based Clustering, Hierarchical Clustering, Density-based Clustering, Graph clustering algorithms, Cluster Validation Indices, Clustering in Online Social Microblogging Sites<br><br><b>Section 3: Attribute Selection to Improve Spam Classification</b><br>8. Introduction of Attribute Selection to Improve Spam Classification<br>9. Attribute Selection Based in Basics of Rough Set Theory and Attribute selection algorithm.<br>10. Experimental Dataset Description<br>11. Evaluating performance and Evaluation measures<br>12. Fake news, scams, recruiting by terrorist or criminal organizations<br><br><b>Section 4: Microblog Summarization</b><br>13. Introduction of Microblog Summarization<br>14. Base summarization algorithms<br>15. Unsupervised ensemble summarization approach<br>16. Supervised ensemble summarisation approach<br>17. Experiments and results and Performance analysis<br>18. Demonstrating summarization examples<br><br><b>Section 5: Microblog Clustering</b><br>19. Introduction of Microblog Clustering<br>Experimental Dataset -- will be posted on Mendeley and link included at end of Chapter 19<br>20. Graph Based Clustering Technique<br>21. Genetic Algorithm based Clustering<br>22. Clustering based on Feature Selection<br>23. Clustering Microblogs using Dimensionality Reduction<br>24. Evaluating performance and result Analysis<br><br><b>Section 6: Conclusion and Future Directions on Social Microblogging Sites</b> |
abstractGer |
<B>Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites</b><br>1. Introduction to Microblogging Sites<br>2. Data structures and data storage<br>3. Data Collection using Twitter API<br><br><b>Section 2: Microblogging dataset Applications and Implications</b><br>4. Brief overview of existing algorithms and Applications<br>Attribute Selection Methods -- Filter Method, Wrapper Method, Other attribute selection algorithms<br>5. Spam detection -- Spam detection in OSM -- Attribute selection for spam detection<br>6. Summarization -- Automatic Document Summarization, Summarization of microblogs, Comparing algorithms for microblog summarization, Summarization Validation<br>7. Cluster Analysis, Clustering Algorithms, Partition based Clustering, Hierarchical Clustering, Density-based Clustering, Graph clustering algorithms, Cluster Validation Indices, Clustering in Online Social Microblogging Sites<br><br><b>Section 3: Attribute Selection to Improve Spam Classification</b><br>8. Introduction of Attribute Selection to Improve Spam Classification<br>9. Attribute Selection Based in Basics of Rough Set Theory and Attribute selection algorithm.<br>10. Experimental Dataset Description<br>11. Evaluating performance and Evaluation measures<br>12. Fake news, scams, recruiting by terrorist or criminal organizations<br><br><b>Section 4: Microblog Summarization</b><br>13. Introduction of Microblog Summarization<br>14. Base summarization algorithms<br>15. Unsupervised ensemble summarization approach<br>16. Supervised ensemble summarisation approach<br>17. Experiments and results and Performance analysis<br>18. Demonstrating summarization examples<br><br><b>Section 5: Microblog Clustering</b><br>19. Introduction of Microblog Clustering<br>Experimental Dataset -- will be posted on Mendeley and link included at end of Chapter 19<br>20. Graph Based Clustering Technique<br>21. Genetic Algorithm based Clustering<br>22. Clustering based on Feature Selection<br>23. Clustering Microblogs using Dimensionality Reduction<br>24. Evaluating performance and result Analysis<br><br><b>Section 6: Conclusion and Future Directions on Social Microblogging Sites</b> |
abstract_unstemmed |
<B>Section 1: Introduction of Intelligent Information Filtering and Organisation Systems for Social Microblogging Sites</b><br>1. Introduction to Microblogging Sites<br>2. Data structures and data storage<br>3. Data Collection using Twitter API<br><br><b>Section 2: Microblogging dataset Applications and Implications</b><br>4. Brief overview of existing algorithms and Applications<br>Attribute Selection Methods -- Filter Method, Wrapper Method, Other attribute selection algorithms<br>5. Spam detection -- Spam detection in OSM -- Attribute selection for spam detection<br>6. Summarization -- Automatic Document Summarization, Summarization of microblogs, Comparing algorithms for microblog summarization, Summarization Validation<br>7. Cluster Analysis, Clustering Algorithms, Partition based Clustering, Hierarchical Clustering, Density-based Clustering, Graph clustering algorithms, Cluster Validation Indices, Clustering in Online Social Microblogging Sites<br><br><b>Section 3: Attribute Selection to Improve Spam Classification</b><br>8. Introduction of Attribute Selection to Improve Spam Classification<br>9. Attribute Selection Based in Basics of Rough Set Theory and Attribute selection algorithm.<br>10. Experimental Dataset Description<br>11. Evaluating performance and Evaluation measures<br>12. Fake news, scams, recruiting by terrorist or criminal organizations<br><br><b>Section 4: Microblog Summarization</b><br>13. Introduction of Microblog Summarization<br>14. Base summarization algorithms<br>15. Unsupervised ensemble summarization approach<br>16. Supervised ensemble summarisation approach<br>17. Experiments and results and Performance analysis<br>18. Demonstrating summarization examples<br><br><b>Section 5: Microblog Clustering</b><br>19. Introduction of Microblog Clustering<br>Experimental Dataset -- will be posted on Mendeley and link included at end of Chapter 19<br>20. Graph Based Clustering Technique<br>21. Genetic Algorithm based Clustering<br>22. Clustering based on Feature Selection<br>23. Clustering Microblogs using Dimensionality Reduction<br>24. Evaluating performance and result Analysis<br><br><b>Section 6: Conclusion and Future Directions on Social Microblogging Sites</b> |
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Data analytics for social microblogging platforms |
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