Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
An Integrated Framework for Web Data Preprocessing Towards Modeling User Behavior. / Ali, No'aman M.; Gadallah, Ahmed M.; Hefny, Hesham A.; Novikov, Boris.
2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020. Institute of Electrical and Electronics Engineers Inc., 2020. 9271467 (2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020).Результаты исследований: Публикации в книгах, отчётах, сборниках, трудах конференций › статья в сборнике материалов конференции › научная › Рецензирование
}
TY - GEN
T1 - An Integrated Framework for Web Data Preprocessing Towards Modeling User Behavior
AU - Ali, No'aman M.
AU - Gadallah, Ahmed M.
AU - Hefny, Hesham A.
AU - Novikov, Boris
N1 - Publisher Copyright: © 2020 IEEE. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020/10/6
Y1 - 2020/10/6
N2 - Extracting useful and relevant information from the massive amount of data by web users becomes a challenging task. This work regarding applications based on the use of Web Usage Mining (WUM). Clickstream, transaction data, and user profile data represent various sources of web usage data. Preprocessing is an essential process in WUM for understanding the user's life as a whole within a session on a website. It signifies the aggregation of consequent series of page views executed by a singular user traversing through a website. Therefore, it represents a critical task that involves converting raw web log data to obtain a suitable pattern for efficient analysis. The importance of these processes relies on the complex nature of web architecture, and it takes almost 80% of the mining process. This work introduces a complete framework for data preprocessing with a comprehensive demonstration of a real dataset.
AB - Extracting useful and relevant information from the massive amount of data by web users becomes a challenging task. This work regarding applications based on the use of Web Usage Mining (WUM). Clickstream, transaction data, and user profile data represent various sources of web usage data. Preprocessing is an essential process in WUM for understanding the user's life as a whole within a session on a website. It signifies the aggregation of consequent series of page views executed by a singular user traversing through a website. Therefore, it represents a critical task that involves converting raw web log data to obtain a suitable pattern for efficient analysis. The importance of these processes relies on the complex nature of web architecture, and it takes almost 80% of the mining process. This work introduces a complete framework for data preprocessing with a comprehensive demonstration of a real dataset.
KW - clickstream analysis
KW - data preprocessing
KW - link prediction
KW - server log
KW - web mining
KW - web usage mining
UR - http://www.scopus.com/inward/record.url?scp=85098912683&partnerID=8YFLogxK
U2 - 10.1109/FarEastCon50210.2020.9271467
DO - 10.1109/FarEastCon50210.2020.9271467
M3 - Conference contribution
AN - SCOPUS:85098912683
T3 - 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020
BT - 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 International Multi-Conference on Industrial Engineering and Modern Technologies, FarEastCon 2020
Y2 - 6 October 2020 through 9 October 2020
ER -
ID: 72796541