Shodhganga : a reservoir of Indian theses @ INFLIBNET
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Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/273160
| Title: | Unsupervised and semi supervised algorithms for discovery of aspects from code mixed social media data |
| Researcher: | Asnani, Kavita Sanjay |
| Guide(s): | Pawar, Jyoti D |
| Keywords: | BabelNet based coherent topic based aspect filtering Code mixed probabilistic latent semantic analysis Code mixed social media data Engineering and Technology,Computer Science,Computer Science Software Engineering Multilingual message based semantic processing Sentiment analysis Unsupervised and semi supervised algorithms |
| University: | Goa University |
| Completed Date: | 2017 |
| Abstract: | Available |
| Pagination: | 119 p. |
| URI: | http://hdl.handle.net/10603/273160 |
| Appears in Departments: | Department of Computer Science and Technology |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 01_title.pdf | Attached File | 81.69 kB | Adobe PDF | View/Open |
| 02_certificate.pdf | 49.49 kB | Adobe PDF | View/Open | |
| 03_acknowledgement.pdf | 53.86 kB | Adobe PDF | View/Open | |
| 04_abstract.pdf | 78.11 kB | Adobe PDF | View/Open | |
| 05_list of tables and figures.pdf | 76.16 kB | Adobe PDF | View/Open | |
| 06_table of content.pdf | 57.94 kB | Adobe PDF | View/Open | |
| 07_chapter 1.pdf | 155.67 kB | Adobe PDF | View/Open | |
| 08_chapter 2.pdf | 213.53 kB | Adobe PDF | View/Open | |
| 09_chapter 3.pdf | 165.47 kB | Adobe PDF | View/Open | |
| 10_chapter 4.pdf | 298.07 kB | Adobe PDF | View/Open | |
| 11_chapter 5.pdf | 227.69 kB | Adobe PDF | View/Open | |
| 12_chapter 6.pdf | 201.49 kB | Adobe PDF | View/Open | |
| 13_chapter 7.pdf | 272.1 kB | Adobe PDF | View/Open | |
| 14_chapter 8.pdf | 207.24 kB | Adobe PDF | View/Open | |
| 15_chapter 9.pdf | 476.28 kB | Adobe PDF | View/Open | |
| 16_chapter 10.pdf | 268.07 kB | Adobe PDF | View/Open | |
| 17_chapter 11.pdf | 127.41 kB | Adobe PDF | View/Open | |
| 18_references.pdf | 118.06 kB | Adobe PDF | View/Open |
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