Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/461261
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | ||
dc.date.accessioned | 2023-02-18T06:35:13Z | - |
dc.date.available | 2023-02-18T06:35:13Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/461261 | - |
dc.description.abstract | newline | |
dc.format.extent | ||
dc.language | English | |
dc.relation | ||
dc.rights | university | |
dc.title | Textual Sentiment Classification With Feature Selection Using Deep Learning Approach Via Autoencoders for Information Retrieval | |
dc.title.alternative | ||
dc.creator.researcher | Abha Kiran Rajpoot | |
dc.subject.keyword | Computer Science | |
dc.subject.keyword | Computer Science Artificial Intelligence | |
dc.subject.keyword | Engineering and Technology | |
dc.description.note | ||
dc.contributor.guide | Parma Nand and Ali Imam Abidi | |
dc.publisher.place | Greater Noida | |
dc.publisher.university | Sharda University | |
dc.publisher.institution | Department of Computer Science and Engineering (CSE) | |
dc.date.registered | ||
dc.date.completed | 2022 | |
dc.date.awarded | 2022 | |
dc.format.dimensions | ||
dc.format.accompanyingmaterial | DVD | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Department of Computer Science & Engineering (CSE) |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 178.24 kB | Adobe PDF | View/Open |
02_prelim.pdf | 2.12 MB | Adobe PDF | View/Open | |
03_content.pdf | 699.62 kB | Adobe PDF | View/Open | |
04_abstract.pdf | 4.9 MB | Adobe PDF | View/Open | |
05_chapter 1.pdf | 17.35 MB | Adobe PDF | View/Open | |
06_chapter 2.pdf | 6.77 MB | Adobe PDF | View/Open | |
07_chapter 3.pdf | 6.88 MB | Adobe PDF | View/Open | |
08_chapter 4.pdf | 6.74 MB | Adobe PDF | View/Open | |
09_chapter 5.pdf | 6.64 MB | Adobe PDF | View/Open | |
10_annexures.pdf | 7.07 MB | Adobe PDF | View/Open | |
80_recommendation.pdf | 2.29 MB | Adobe PDF | View/Open |
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