- Tytuł:
- Computerised Recommendations On E-Transaction Finalisation By Means Of Machine Learning
- Autorzy:
- Budnikas, Germanas
- Powiązania:
- https://bibliotekanauki.pl/articles/466046.pdf
- Data publikacji:
- 2015
- Wydawca:
- Główny Urząd Statystyczny
- Tematy:
-
online behaviour
Google Analytics
Naïve Bayes classifier
artificial neural network - Opis:
- Nowadays a vast majority of businesses are supported or executed online. Website-to-user interaction is extremely important and user browsing activity on a website is becoming important to analyse. This paper is devoted to the research on user online behaviour and making computerised advices. Several problems and their solutions are discussed: to know user behaviour online pattern with respect to business objectives and estimate a possible highest impact on user online activity. The approach suggested in the paper uses the following techniques: Business Process Modelling for formalisation of user online activity; Google Analytics tracking code function for gathering statistical data about user online activities; Naïve Bayes classifier and a feedforward neural network for a classification of online patterns of user behaviour as well as for an estimation of a website component that has the highest impact on a fulfilment of business objective by a user and which will be advised to be looked at. The technique is illustrated by an example.
- Źródło:
-
Statistics in Transition new series; 2015, 16, 2; 309-322
1234-7655 - Pojawia się w:
- Statistics in Transition new series
- Dostawca treści:
- Biblioteka Nauki
Artykuł