The incorporation of information technologies （ITs） in the tourism sector has enabled marketing actions to be enhanced through websites. In this context, destinations＇ online portals have become a key tool to promo...The incorporation of information technologies （ITs） in the tourism sector has enabled marketing actions to be enhanced through websites. In this context, destinations＇ online portals have become a key tool to promote territories. Vast amount of money is invested in developing these virtual sites and lately, also increasing interest has been put towards their performance analysis. This study has been applied to Spain.info website in order to track virtual visitors＇ digital footprint. The analysis conducted through the Destination Web Monitor （DWM） system has allowed taking into consideration the behavior of visitors in the website in order to obtain results on their interests when visiting the portal. The article mainly focuses on Brazil, Russia, India, and China （BRIC）, considered as markets of opportunity for the tourism sector in Spain. Results provided insights on to whom, when, and how to develop potential e-marketing campaigns.展开更多
The paper aims to present a comparison of visitor behaviors and visitor spatial and temporal distribution in a mountain national park between the pre-Covid-19 period(2017-2019)and Covid-19 pandemic year(2020).The rese...The paper aims to present a comparison of visitor behaviors and visitor spatial and temporal distribution in a mountain national park between the pre-Covid-19 period(2017-2019)and Covid-19 pandemic year(2020).The research is based on pyroelectric sensor data from 2017-2020 and a survey of visitors designed to assess the spatial and temporal distribution of visitors and their behaviors and changes therein.The research data were used to identify two visitor clusters:Impact of Covid-19(IC)and No-Impact of Covid-19(N-IC).The research was conducted in Stolowe Mountains National Park(SMNP)in Poland using data from Monitoring System of tourist traffic(MSTT).A total of 374 respondents participated in the survey in 2020 period,which demonstrated a significant impact of the ongoing pandemic on many aspects of their behavior.These results were compared with the results obtained from 2,642 surveys carried out in 2017-2019.The findings are compared to findings reported by other authors.Some visitors did claim that the pandemic has not affected their behavior in any way.展开更多
In this paper we investigate the effectiveness of ensemble-based learners for web robot session identification from web server logs. We also perform multi fold robot session labeling to improve the performance of lear...In this paper we investigate the effectiveness of ensemble-based learners for web robot session identification from web server logs. We also perform multi fold robot session labeling to improve the performance of learner. We conduct a comparative study for various ensemble methods (Bagging, Boosting, and Voting) with simple classifiers in perspective of classification. We also evaluate the effectiveness of these classifiers (both ensemble and simple) on five different data sets of varying session length. Presently the results of web server log analyzers are not very much reliable because the input log files are highly inflated by sessions of automated web traverse software’s, known as web robots. Presence of web robots access traffic entries in web server log repositories imposes a great challenge to extract any actionable and usable knowledge about browsing behavior of actual visitors. So web robots sessions need accurate and fast detection from web server log repositories to extract knowledge about genuine visitors and to produce correct results of log analyzers.展开更多
文摘The incorporation of information technologies （ITs） in the tourism sector has enabled marketing actions to be enhanced through websites. In this context, destinations＇ online portals have become a key tool to promote territories. Vast amount of money is invested in developing these virtual sites and lately, also increasing interest has been put towards their performance analysis. This study has been applied to Spain.info website in order to track virtual visitors＇ digital footprint. The analysis conducted through the Destination Web Monitor （DWM） system has allowed taking into consideration the behavior of visitors in the website in order to obtain results on their interests when visiting the portal. The article mainly focuses on Brazil, Russia, India, and China （BRIC）, considered as markets of opportunity for the tourism sector in Spain. Results provided insights on to whom, when, and how to develop potential e-marketing campaigns.
文摘The paper aims to present a comparison of visitor behaviors and visitor spatial and temporal distribution in a mountain national park between the pre-Covid-19 period(2017-2019)and Covid-19 pandemic year(2020).The research is based on pyroelectric sensor data from 2017-2020 and a survey of visitors designed to assess the spatial and temporal distribution of visitors and their behaviors and changes therein.The research data were used to identify two visitor clusters:Impact of Covid-19(IC)and No-Impact of Covid-19(N-IC).The research was conducted in Stolowe Mountains National Park(SMNP)in Poland using data from Monitoring System of tourist traffic(MSTT).A total of 374 respondents participated in the survey in 2020 period,which demonstrated a significant impact of the ongoing pandemic on many aspects of their behavior.These results were compared with the results obtained from 2,642 surveys carried out in 2017-2019.The findings are compared to findings reported by other authors.Some visitors did claim that the pandemic has not affected their behavior in any way.
文摘In this paper we investigate the effectiveness of ensemble-based learners for web robot session identification from web server logs. We also perform multi fold robot session labeling to improve the performance of learner. We conduct a comparative study for various ensemble methods (Bagging, Boosting, and Voting) with simple classifiers in perspective of classification. We also evaluate the effectiveness of these classifiers (both ensemble and simple) on five different data sets of varying session length. Presently the results of web server log analyzers are not very much reliable because the input log files are highly inflated by sessions of automated web traverse software’s, known as web robots. Presence of web robots access traffic entries in web server log repositories imposes a great challenge to extract any actionable and usable knowledge about browsing behavior of actual visitors. So web robots sessions need accurate and fast detection from web server log repositories to extract knowledge about genuine visitors and to produce correct results of log analyzers.
