Sentiment analysis for airline services on Twitter using deep learning with word embedding /
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| Main Author: | |
|---|---|
| Format: | Thesis Book |
| Language: | English |
| Published: |
2020.
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| Subjects: | |
| Online Access: | http://studentsrepo.um.edu.my/13325/ |
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| LEADER | 01720nam a2200421 i 4500 | ||
|---|---|---|---|
| 001 | u1149039 | ||
| 003 | SIRSI | ||
| 005 | 202110221457 | ||
| 008 | 211022s2020 my a m 000 0 eng | ||
| 040 | |a UMM |d AUM |e rda | ||
| 090 | |a QA76.758 |b UM 2020 Elk | ||
| 100 | 1 | |a El Khalifa, Mawada Mohamed Nour El Daim, |e author. | |
| 245 | 1 | 0 | |a Sentiment analysis for airline services on Twitter using deep learning with word embedding / |c Mawada Mohamed Nour El Daim El Khalifa. |
| 264 | 1 | |c 2020. | |
| 300 | |a xiv, 65 leaves : |b illustrations ; |c 30 cm | ||
| 336 | |a text |2 rdacontent | ||
| 336 | |a still image |2 rdacontent | ||
| 337 | |a unmediated |2 rdamedia | ||
| 337 | |a computer |2 rdamedia | ||
| 338 | |a volume |2 rdacarrier | ||
| 338 | |a computer disc |2 rdacarrier | ||
| 502 | |b M.Sofw.Eng. |c Jabatan Kejuruteraan Perisian, Fakulti Sains Komputer dan Teknologi Maklumat, Universiti Malaya |d 2020. | ||
| 504 | |a Bibliography: leaves 60-64. | ||
| 530 | |a Also issued in CD. | ||
| 630 | 0 | 0 | |a Twitter. |
| 650 | 0 | |a Online social networks |x Data processing. | |
| 650 | 0 | |a Natural language processing (Computer science) | |
| 650 | 0 | |a Computational linguistics. | |
| 650 | 0 | |a Data mining. | |
| 650 | 0 | |a Sentiment analysis. | |
| 650 | 0 | |a Airlines |x Management. | |
| 650 | 0 | |a Machine learning. | |
| 710 | 2 | |a Universiti Malaya. |b Jabatan Kejuruteraan Perisian, |e degree granting institution. | |
| 856 | 4 | 1 | |u http://studentsrepo.um.edu.my/13325/ |
| 900 | |a NNANS US | ||
| 596 | |a 1 25 | ||
| 999 | |a QA76.758 UM 2020 ELK |w LC |c 1 |i A517055846 |f 25/11/2021 |g 1 |l STACKS |m P01UTAMA |r Y |s Y |t TESIS |u 25/11/2021 |1 STEM | ||
| 999 | |a QA76.758 UM 2020 ELK |w LC |c 1 |i A517055877 |f 31/3/2022 |g 1 |l STACKS |m P25UMARCHI |r N |s Y |t CD |u 29/3/2022 |1 STEM |o .STAFF. MST-CD534 | ||