Analysis of Users’ Behavior in Structured e-Commerce Websites
Online shopping is becoming more and more common in our daily lives. Understanding users' interests and behavior is essential to adapt e-commerce Web sites to customers' requirements. The information about users' behavior is stored in the Web server logs. The analysis of such informat...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2017-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/7933069/ |
| _version_ | 1818641737204105216 |
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| author | Sergio Hernandez Pedro Alvarez Javier Fabra Joaquin Ezpeleta |
| author_facet | Sergio Hernandez Pedro Alvarez Javier Fabra Joaquin Ezpeleta |
| author_sort | Sergio Hernandez |
| collection | DOAJ |
| description | Online shopping is becoming more and more common in our daily lives. Understanding users' interests and behavior is essential to adapt e-commerce Web sites to customers' requirements. The information about users' behavior is stored in the Web server logs. The analysis of such information has focused on applying data mining techniques, where a rather static characterization is used to model users' behavior, and the sequence of the actions performed by them is not usually considered. Therefore, incorporating a view of the process followed by users during a session can be of great interest to identify more complex behavioral patterns. To address this issue, this paper proposes a linear-temporal logic model checking approach for the analysis of structured e-commerce Web logs. By defining a common way of mapping log records according to the e-commerce structure, Web logs can be easily converted into event logs where the behavior of users is captured. Then, different predefined queries can be performed to identify different behavioral patterns that consider the different actions performed by a user during a session. Finally, the usefulness of the proposed approach has been studied by applying it to a real case study of a Spanish e-commerce Web site. The results have identified interesting findings that have made possible to propose some improvements in the Web site design with the aim of increasing its efficiency. |
| first_indexed | 2024-12-16T23:31:55Z |
| format | Article |
| id | doaj.art-f80e5d51138b44328c87205219f7ef64 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T23:31:55Z |
| publishDate | 2017-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f80e5d51138b44328c87205219f7ef642022-12-21T22:11:51ZengIEEEIEEE Access2169-35362017-01-015119411195810.1109/ACCESS.2017.27076007933069Analysis of Users’ Behavior in Structured e-Commerce WebsitesSergio Hernandez0https://orcid.org/0000-0002-4950-7246Pedro Alvarez1Javier Fabra2Joaquin Ezpeleta3Department of Computer Science and Systems Engineering, Aragón Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, SpainDepartment of Computer Science and Systems Engineering, Aragón Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, SpainDepartment of Computer Science and Systems Engineering, Aragón Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, SpainDepartment of Computer Science and Systems Engineering, Aragón Institute of Engineering Research (I3A), University of Zaragoza, Zaragoza, SpainOnline shopping is becoming more and more common in our daily lives. Understanding users' interests and behavior is essential to adapt e-commerce Web sites to customers' requirements. The information about users' behavior is stored in the Web server logs. The analysis of such information has focused on applying data mining techniques, where a rather static characterization is used to model users' behavior, and the sequence of the actions performed by them is not usually considered. Therefore, incorporating a view of the process followed by users during a session can be of great interest to identify more complex behavioral patterns. To address this issue, this paper proposes a linear-temporal logic model checking approach for the analysis of structured e-commerce Web logs. By defining a common way of mapping log records according to the e-commerce structure, Web logs can be easily converted into event logs where the behavior of users is captured. Then, different predefined queries can be performed to identify different behavioral patterns that consider the different actions performed by a user during a session. Finally, the usefulness of the proposed approach has been studied by applying it to a real case study of a Spanish e-commerce Web site. The results have identified interesting findings that have made possible to propose some improvements in the Web site design with the aim of increasing its efficiency.https://ieeexplore.ieee.org/document/7933069/Data mininge-commerceweb logs analysisbehavioral patternsmodel checking |
| spellingShingle | Sergio Hernandez Pedro Alvarez Javier Fabra Joaquin Ezpeleta Analysis of Users’ Behavior in Structured e-Commerce Websites IEEE Access Data mining e-commerce web logs analysis behavioral patterns model checking |
| title | Analysis of Users’ Behavior in Structured e-Commerce Websites |
| title_full | Analysis of Users’ Behavior in Structured e-Commerce Websites |
| title_fullStr | Analysis of Users’ Behavior in Structured e-Commerce Websites |
| title_full_unstemmed | Analysis of Users’ Behavior in Structured e-Commerce Websites |
| title_short | Analysis of Users’ Behavior in Structured e-Commerce Websites |
| title_sort | analysis of users x2019 behavior in structured e commerce websites |
| topic | Data mining e-commerce web logs analysis behavioral patterns model checking |
| url | https://ieeexplore.ieee.org/document/7933069/ |
| work_keys_str_mv | AT sergiohernandez analysisofusersx2019behaviorinstructuredecommercewebsites AT pedroalvarez analysisofusersx2019behaviorinstructuredecommercewebsites AT javierfabra analysisofusersx2019behaviorinstructuredecommercewebsites AT joaquinezpeleta analysisofusersx2019behaviorinstructuredecommercewebsites |