Please use this identifier to cite or link to this item:
https://rda.sliit.lk/handle/123456789/970
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kannangara, L. | - |
dc.contributor.author | Harsha, S. | - |
dc.contributor.author | Isuru, T. | - |
dc.contributor.author | Wijesiriwardhane, C. | - |
dc.contributor.author | Wijendra, D.R. | - |
dc.contributor.author | Kishara, J. | - |
dc.date.accessioned | 2022-02-07T07:09:38Z | - |
dc.date.available | 2022-02-07T07:09:38Z | - |
dc.date.issued | 2021-12-09 | - |
dc.identifier.issn | 978-1-6654-0862-2/21 | - |
dc.identifier.uri | http://rda.sliit.lk/handle/123456789/970 | - |
dc.description.abstract | Television commercials are a passive type of advertising technique that does not consider consumer demographics who are viewing the television at a specific time. As a result, the user sees irrelevant advertisements, which tends to reduce user engagement and sales conversions.As Sales ,which is the expected target of any advertisement campaign, a user-based advertising approach can be considered as a solution to mitigate the negative aspects. A user-based advertisement suggesting system for television, which is extensively utilized in every other digital media, is expected to be given as the solution. For the suggestion process, user attributes such as age, gender, peer group, and the mood identified in which the advertising is shown were taken into consideration. This will result in more relevant commercials for consumers, making television advertisements more user-friendly, resulting in greater sales conversion for the advertising agency. | en_US |
dc.description.sponsorship | Co-Sponsor:Institute of Electrical and Electronic Engineers (IEEE) Academic sponsor:SLIIT UNI Gold Sponsor :London Stock Exchange Group (LSEG) | en_US |
dc.language.iso | en | en_US |
dc.publisher | 2021 3rd International Conference on Advancements in Computing (ICAC), SLIIT | en_US |
dc.subject | advertisements | en_US |
dc.subject | ad recommendation | en_US |
dc.subject | age estimation | en_US |
dc.subject | blockchain | en_US |
dc.subject | data security | en_US |
dc.subject | gender estimation | en_US |
dc.subject | human emotions | en_US |
dc.subject | image processing | en_US |
dc.title | Artificial Intelligence-based Business Strategy for Optimized Advertising | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1109/ICAC54203.2021.9671204 | en_US |
Appears in Collections: | 3rd International Conference on Advancements in Computing (ICAC) | 2021 Department of Computer systems Engineering-Scopes |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Artificial_Intelligence-based_Business_Strategy_for_Optimized_Advertising (1).pdf Until 2050-12-31 | 2.01 MB | Adobe PDF | View/Open Request a copy |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.