Analysis of Users’ Behavior in Structured e-Commerce Websites

Hernández, Sergio; Álvarez, Pedro; Fabra, Javier; Ezpeleta, J.

doi:10.1109/access.2017.2707600

Cited by 37 publications

(31 citation statements)

References 36 publications

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“…A special model known as Linear-temporal logic model was proposed in [1]. This model maps the web logs with the e-commerce website structure, changing the normal web logs to event transactions from which the user patterns are derived.…”

Section: Literature Reviewmentioning

confidence: 99%

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Research Aligned Analysis on Web Access Behavioral Pattern Mining for User Identification

Gokulapriya¹,

R²

2019

IJEAT

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Human activity understanding includes activity recognition and activity pattern discovery. Monitoring human activity and finding abnormality in their activities used by many field like medical applications, security systems etc. Basically it helps and support in decision making systems. Mining user activity from web logs can helps in finding hidden information about the user access pattern which reveals the web access behaviour of the users. Clustering and Classification techniques are used for web user identification. Clustering is the task of grouping similar patterns for web user identification. Classification is the process of classifying web patterns for user identification. In this paper we have implemented the existing works and discussed the results here to find the limitations. In existing methods, many data mining techniques were introduced for web user behaviour identification. But, the user identification accuracy was not improved and time consumption was not reduced. Our objective is to study the existing work and explore the possibility to improve the identification accuracy and reduce the time consumption using machine learning and deep learning techniques

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Section: Literature Reviewmentioning

confidence: 99%

“…The information to be mined is obtained from the server logs. Linear temporal logic model is used in [1] for examination of structured e-commerce logs. This model maps each page involved with the e-commerce site with the web log data and thus converts the normal web log into event log.…”

Section: A User Behavioral Analysis In E-commerce Websitesmentioning

confidence: 99%

Research Aligned Analysis on Web Access Behavioral Pattern Mining for User Identification

Gokulapriya¹,

R²

2019

IJEAT

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“…The process mining in a recent research discipline which is used to the discover knowledge from the event logs and the process can be extracted from the available information system like to transaction log file from a normal database table. The process mining is a suitable for application in any industry and process [9] [10]. In this company have a several factories in different region and they can usually are difference between the reliability of deliveries.…”

Section: Introductionmentioning

confidence: 99%

Practise Mining to Predict Type of Client Performence

2019

IJITEE

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Abstract: The aim of process mining implement is firstly to discover the typical customer fulfillment business process-process mining act as a bridge between data mining and web mining. Process mining in an active innovative research area in recent year. The goal is to be extract process -related information from the event log by observing events recorded by some of the information system using the click stream method. Finally we are classifying the different categories of customer behavior using weka tool after we applied the knowledge miner. The result provides to find the different type of customer and their behavior and its helps the company to improve the product and satisfied customer needs.

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“…However, because there is so much information to search, traditional search engine technology is becoming less and less useful. Many studies show that the majority of search terms for search engines are not short and clear, and users can have completely different intentions for the same query [1], [2], [3]. This can be described by the search term "office" or "Jaguar".…”

Section: Introductionmentioning

confidence: 99%

“…Currently, web search personalization primarily uses user profile and weblog data information to learn the necessary personalization. Most of these tasks are performed by the majority of users [2], [3], [7], [8] to provide a solution based on historical activities in the form of Web log data or explicit user feedback learning. Many research on personalized web searches focuses on new mechanisms to get automatically be trained for the user preferences exclusive of the user's direct effort because they are unwilling to give "explicit feedback" on their interests.…”

Section: Introductionmentioning

confidence: 99%

A Web Search Personalization Based on Probability of Semantic Similarity between User Log and Query with Web Page

Raju¹,

Babu²,

Anuradha³

2018

IJET

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Web search personalization is recognized as a competent solution to address the problem of query-relevant search as per the user interest, while it able to present dissimilar search results based upon the preferences and information requirements of users. The popular search engines provide their search results interpreting the user query only, which mostly have unrelated results due to the keywords ambiguity problem. In order to have satisfied and user interesting result, it is important to personalize the results according to their relevancies. In this paper, we propose a Web search Personalization based on a Probability of Semantic Similarity (WP-PSS) between user log and query with search result webpage. It performs a probability of semantic similarities computation between the user query and search result webpage snippet, and compute the frequency of link associated with the log data. Based on these two computed factors a probability of similarities association is computed to group and re-rank the search results for the personalization. Experiment evaluation over a set of multi-domain web searched data collection shows an accuracy improvisation.

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Analysis of Users’ Behavior in Structured e-Commerce Websites

Cited by 37 publications

References 36 publications

Research Aligned Analysis on Web Access Behavioral Pattern Mining for User Identification

Research Aligned Analysis on Web Access Behavioral Pattern Mining for User Identification

Practise Mining to Predict Type of Client Performence

A Web Search Personalization Based on Probability of Semantic Similarity between User Log and Query with Web Page

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