TY - GEN
T1 - Big Data Real-Time Clickstream Data Ingestion Paradigm for E-Commerce Analytics
AU - Pal, Gautam
AU - Li, Gangmin
AU - Atkinson, Katie
N1 - Funding Information:
This work is supported by Xi’an Jiaotong-Liverpool University Big Data research fund (Ref: RDF 15-02-35)
Publisher Copyright:
© 2018 IEEE.
PY - 2018/10
Y1 - 2018/10
N2 - E-Commerce websites track visitors browsing records to uncover their intent and preferences for effective online marketing. User clicks or clickstream is a series of page requests which generates a URL on each click event. Clickstream data is an information trail a user leaves behind while visiting websites. Click URLs can be graphically represented for clickstream reporting. In this work, we study Big Data real-Time clickstream data ingestion model in e-commerce Domain, which builds on top of standard Big Data tools like Kafka, Flume, Spark and Cassandra. In particular, we focus on high velocity, fault-tolerant streaming data acquisition pipelines in a distributed setup rather than mining and searching patterns in it.
AB - E-Commerce websites track visitors browsing records to uncover their intent and preferences for effective online marketing. User clicks or clickstream is a series of page requests which generates a URL on each click event. Clickstream data is an information trail a user leaves behind while visiting websites. Click URLs can be graphically represented for clickstream reporting. In this work, we study Big Data real-Time clickstream data ingestion model in e-commerce Domain, which builds on top of standard Big Data tools like Kafka, Flume, Spark and Cassandra. In particular, we focus on high velocity, fault-tolerant streaming data acquisition pipelines in a distributed setup rather than mining and searching patterns in it.
KW - Clickstream
KW - Flume
KW - Kafka
KW - Real-time data processing
KW - Watermark
UR - http://www.scopus.com/inward/record.url?scp=85084125601&partnerID=8YFLogxK
U2 - 10.1109/I2CT42659.2018.9058112
DO - 10.1109/I2CT42659.2018.9058112
M3 - Conference Proceeding
AN - SCOPUS:85084125601
T3 - 2018 4th International Conference for Convergence in Technology, I2CT 2018
BT - 2018 4th International Conference for Convergence in Technology, I2CT 2018
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference for Convergence in Technology, I2CT 2018
Y2 - 27 October 2018 through 28 October 2018
ER -