Please use this identifier to cite or link to this item:
http://hdl.handle.net/123456789/4204
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Tan, Wai Hong | en_US |
dc.date.accessioned | 2023-01-11T09:22:36Z | - |
dc.date.available | 2023-01-11T09:22:36Z | - |
dc.date.issued | 2022 | - |
dc.identifier.issn | 2948-5037 | - |
dc.identifier.uri | http://hdl.handle.net/123456789/4204 | - |
dc.description | Others | en_US |
dc.description.abstract | For the entirety of my odyssey to complete writing my dissertation, I had devoted time and assiduous efforts to formulate models based on the theory of point process, which aim to predict the numbers of reposts (or retweets) stemming from the original posts (or tweets) on a renowned microblogging platform called Twitter. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Caknawan UMK | en_US |
dc.relation.ispartof | Caknawan | en_US |
dc.subject | en_US | |
dc.subject | Tweet | en_US |
dc.subject | Retweet | en_US |
dc.subject | Point Process | en_US |
dc.subject | Temporal | en_US |
dc.subject | Poisson Process | en_US |
dc.subject | Self-Exciting | en_US |
dc.subject | Hawkes Process | en_US |
dc.subject | Formulation | en_US |
dc.subject | Prediction | en_US |
dc.subject | Popularity | en_US |
dc.title | Point Processes at a Glance | en_US |
dc.type | National | en_US |
dc.volume | 1(3) | en_US |
dc.description.type | Article in Magazine/Newsletter/Bulletin/Newspaper | en_US |
item.fulltext | With Fulltext | - |
item.openairetype | National | - |
item.languageiso639-1 | en | - |
item.grantfulltext | open | - |
Appears in Collections: | Faculty of Entrepreneurship and Business - Other Publication |
Files in This Item:
File | Description | Size | Format | |
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Point Processes at a Glance.pdf | An Article in Caknawan | 143.28 kB | Adobe PDF | View/Open |
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