dc.contributor.author | Kaklauskas, Artūras | |
dc.contributor.author | Ubartė, Ieva | |
dc.contributor.author | Vetlovienė, Ingrida | |
dc.contributor.author | Skirmantas, Darius | |
dc.date.accessioned | 2023-09-18T16:20:36Z | |
dc.date.available | 2023-09-18T16:20:36Z | |
dc.date.issued | 2020 | |
dc.identifier.issn | 2415-0924 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/113338 | |
dc.description.abstract | Real-time ad personalization is a major research area in modern marketing. According to Ecommerce Europe, 90% of offline shoppers say that personalized ads play a big role in their decisions to buy, while 51% of buyers would share their personal details if that would mean they see only relevant ads equated to information in the consumer’s mind. The idea of this research is to explore neuroadvertising by integrating research methods and to develop ViNeRS, a new method, and system. The ViNeRS method can process big data and offers automated online tips on ways to make ads more effective. Well-targeted ads can make businesses more efficient, help save resources, attract more users, and create opportunities for faster expansion. The researchs aim is to create the Intelligent tutoring system for the impact analysis and assessment of online ads and intuitive online ad serving, which will analyze and assess the impact of online ads (unfinished ad content), the efficiency of ads at each stage of their creation, determine their advantages and disadvantages, improve them until the most catchy version is achieved, enables integrated assessment of neurobiological viewer response and can make real-time selection of the most effective ad option. The system will be able to determine how many times a promotional message should be repeated in a certain part of your video to achieve an effective promotional campaign. | eng |
dc.format | PDF | |
dc.format.extent | p. 16-22 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Index Copernicus | |
dc.relation.isreferencedby | RePec | |
dc.relation.isreferencedby | Dimensions | |
dc.rights | Laisvai prieinamas internete | |
dc.source.uri | https://talpykla.elaba.lt/elaba-fedora/objects/elaba:136664720/datastreams/MAIN/content | |
dc.title | Intelligent tutoring system for the impact analysis and assessment of online ads and intuitive online ad serving | |
dc.type | Straipsnis kitoje DB / Article in other DB | |
dcterms.accessRights | This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. | |
dcterms.license | Creative Commons – Attribution – NonCommercial – NoDerivatives – 4.0 International | |
dcterms.references | 15 | |
dc.type.pubtype | S3 - Straipsnis kitoje DB / Article in other DB | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Statybos fakultetas / Faculty of Civil Engineering | |
dc.contributor.department | Tvariosios statybos institutas / Institute of Sustainable Construction | |
dc.subject.researchfield | T 002 - Statybos inžinerija / Construction and engineering | |
dc.subject.researchfield | S 003 - Vadyba / Management | |
dc.subject.vgtuprioritizedfields | SD0303 - Architektūra ir urbanistinė aplinka / Architecture and Built Environment | |
dc.subject.ltspecializations | L102 - Energetika ir tvari aplinka / Energy and a sustainable environment | |
dc.subject.en | neuromarketing | |
dc.subject.en | intelligent tutoring system | |
dc.subject.en | personalization | |
dc.subject.en | analysis | |
dc.subject.en | online ads | |
dcterms.sourcetitle | International journal of technology and engineering studies | |
dc.description.issue | iss. 1 | |
dc.description.volume | vol. 6 | |
dc.publisher.name | KKG Publications | |
dc.publisher.city | Barcelona | |
dc.identifier.doi | 10.20469/ijtes.6.10003-1 | |
dc.identifier.elaba | 136664720 | |