presenter : yu-ting lu authors: christopher c. yang and tobun dorbin ng 2011. tsmca
DESCRIPTION
Analyzing and Visualizing Web Opinion Development and Social Interactions with Density-Based Clustering. Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA. Outlines. Motivation Objectives Methodology Experiments Conclusions Comments. Motivation. - PowerPoint PPT PresentationTRANSCRIPT
![Page 1: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/1.jpg)
Intelligent Database Systems Lab
Presenter: YU-TING LU
Authors: Christopher C. Yang and Tobun Dorbin Ng
2011. TSMCA
Analyzing and Visualizing Web Opinion Development and Social Interactions with Density-Based Clustering
![Page 2: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/2.jpg)
Intelligent Database Systems Lab
Outlines
MotivationObjectivesMethodologyExperimentsConclusionsComments
![Page 3: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/3.jpg)
Intelligent Database Systems Lab
Motivation• Analysis of developing Web opinions is
potentially valuable for discovering ongoing
topics.
• Typical document clustering techniques with
the goal of clustering all documents applied
to Web opinions produce unsatisfactory
performance.
![Page 4: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/4.jpg)
Intelligent Database Systems Lab
Objectives• We investigated the density-based clustering
algorithm and proposed the scalable distance-based
clustering technique for Web opinion clustering.
• This Web opinion clustering technique enables the
identification of themes within discussions in Web
social networks and their development, as well as the
interactions of active participants.
![Page 5: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/5.jpg)
Intelligent Database Systems Lab
Methodology
![Page 6: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/6.jpg)
Intelligent Database Systems Lab
Methodology-content clustering• Core Thread Concept Selection for Clustering
![Page 7: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/7.jpg)
Intelligent Database Systems Lab
Methodology-content clustering• SDC Algorithm
![Page 8: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/8.jpg)
Intelligent Database Systems Lab
Methodology-Interactive information visualization
![Page 9: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/9.jpg)
Intelligent Database Systems Lab
Methodology-Interactive information visualization
![Page 10: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/10.jpg)
Intelligent Database Systems Lab
Methodology-Interactive information visualization
![Page 11: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/11.jpg)
Intelligent Database Systems Lab
Experiments
![Page 12: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/12.jpg)
Intelligent Database Systems Lab
Experiments
![Page 13: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/13.jpg)
Intelligent Database Systems Lab
Experiments
![Page 14: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/14.jpg)
Intelligent Database Systems Lab
Conclusions
• The SDC algorithm overcomes the weakness of DBSCAN
algorithm by grouping less number of less relevant
clusters together when they are density-reachable.
• The result has shown that they are promising to extract
clusters of threads with important topics and filter the
noise.
![Page 15: Presenter : Yu-Ting LU Authors: Christopher C. Yang and Tobun Dorbin Ng 2011. TSMCA](https://reader035.vdocuments.mx/reader035/viewer/2022062805/56814d19550346895dba5313/html5/thumbnails/15.jpg)
Intelligent Database Systems Lab
Comments
• Advantages- SDC performs better than DBSCAN.- Effective noise filtering.
• Applications- Web opinions clustering.- Density-based clustering.