dc.contributor.author | Jasevičiūtė, Vita | |
dc.contributor.author | Plonis, Darius | |
dc.contributor.author | Serackis, Artūras | |
dc.date.accessioned | 2023-09-18T16:35:09Z | |
dc.date.available | 2023-09-18T16:35:09Z | |
dc.date.issued | 2016 | |
dc.identifier.other | (BIS)VGT02-000032347 | |
dc.identifier.uri | https://etalpykla.vilniustech.lt/handle/123456789/115223 | |
dc.description.abstract | Paper focuses on the optimization of the advertising and other additional costs for the small business ecommerce web sites. The aim of this paper was to propose a dynamic neural network based algorithm to predict number of clicks on a particular advertising link in three web pages of three different small companies working in the same business segment. The dynamic neural network based algorithm was proposed for forecasting the upcoming values of the advertisement clicks. The best results of 10% average forecasting uncertainty was received for two layer NARX network with three additional inputs: bounce rate, average session time and average page load time. The application of NAR neural network without external inputs increased the forecasting uncertainty to 25% which is similar to received 26% LPC uncertainty. | eng |
dc.format | PDF | |
dc.format.extent | p. 1-4 | |
dc.format.medium | tekstas / txt | |
dc.language.iso | eng | |
dc.relation.isreferencedby | Scopus | |
dc.relation.isreferencedby | IEEE Xplore | |
dc.relation.isreferencedby | Conference Proceedings Citation Index - Science (Web of Science) | |
dc.source.uri | http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7485928&newsearch=true&queryText=Plonis | |
dc.subject | IK04 - Skaitmeninės signalų apdorojimo technologijos / Digital signal processing technologies | |
dc.title | Application of dynamic neural network for prediction of advertisement clicks | |
dc.type | Straipsnis konferencijos darbų leidinyje Web of Science DB / Paper in conference publication in Web of Science DB | |
dcterms.references | 10 | |
dc.type.pubtype | P1a - Straipsnis konferencijos darbų leidinyje Web of Science DB / Article in conference proceedings Web of Science DB | |
dc.contributor.institution | Vilniaus Gedimino technikos universitetas | |
dc.contributor.faculty | Elektronikos fakultetas / Faculty of Electronics | |
dc.subject.researchfield | N 009 - Informatika / Computer science | |
dc.subject.researchfield | T 001 - Elektros ir elektronikos inžinerija / Electrical and electronic engineering | |
dc.subject.ltspecializations | L106 - Transportas, logistika ir informacinės ir ryšių technologijos (IRT) / Transport, logistic and information and communication technologies | |
dc.subject.en | Decision support systems | |
dc.subject.en | Google | |
dc.subject.en | Predictive models | |
dc.subject.en | Web sites | |
dcterms.sourcetitle | 2016 Open Conference of Electrical, Electronic and Information Sciences (eStream) : proceedings of the conference, April 19, 2016, Vilnius, Lithuania / Vilnius Gediminas Technical University | |
dc.publisher.name | IEEE | |
dc.publisher.city | New York | |
dc.identifier.doi | 000389317400017 | |
dc.identifier.doi | 2-s2.0-84978758943 | |
dc.identifier.elaba | 17001006 | |