A Recommendation System in E-Commerce with Profit-Support Fuzzy Association Rule Mining (P-FARM)
نویسندگان
چکیده
E-commerce is snowballing with advancements in technology, and as a result, understanding complex transactional data has become increasingly important. To keep customers engaged, e-commerce systems need to have practical product recommendations. Some studies focused on finding the most frequent items recommend customers. However, this approach fails consider profitability, crucial aspect for companies. From researcher’s perspective, study introduces novel method called Profit-supported Association Rule Mining Fuzzy Theory (P-FARM), which goes beyond just recommending considers company’s profit while making suggestions. P-FARM an advanced mining technique that creates association rules by profitable item sets. practitioners’ standpoints, helps companies make better decisions providing them more products fewer rules. The results of show can be powerful tool improving sales maximizing businesses.
منابع مشابه
Association Rule Mining in E- Commerce: a Survey
Association Rule mining is one of the most popular data mining techniques which can be defined as extracting the interesting correlation and relation among large volume of transactions. E-commerce applications generate huge amount of operational and behavioral data. Applying association rule mining in e-commerce application can unearth the hidden knowledge from these data. In this paper a surve...
متن کاملFuzzy Association Rule Mining
Corresponding Author: Lekha. A., Research Scholar, Dr M G R Educational Research Institute, Chennai, India-600095, Assistant Professor, Department of MCA, PESIT, Bangalore Email: [email protected] Abstract: The paper attempts to propose a fuzzy logic association algorithm to predict the risks involved in identifying diseases like breast cancer. Fuzzy logic algorithm is used to find associatio...
متن کاملUsing Support Vector Machine in Fuzzy Association Rule Mining
Fuzzy rule based classification systems is one of the most popular in pattern classification problems. The rules in the fuzzy models can be weighted to show the importance of generated rules where all attributes in the antecedent part of the rules have been usually weighted equally. Whereas the contributed attributes in a fuzzy model may have different influences on the decision making, a new m...
متن کاملRobust Recommendation Based On Association Rule Mining
The open nature of collaborative recommender systems present a security problem. Attackers that are indistinguishable from ordinary users may inject biased profiles, degrading the objectivity and accuracy of the system over time. Standard memory-based collaborative filtering algorithms, such as k-nearest neighbor, have been shown quite vulnerable to such attacks. Model-based techniques, includi...
متن کاملCollaborative Recommendation via Adaptive Association Rule Mining
Collaborative recommender systems allow personalization for e-commerce by exploiting similarities and dissimilarities among users' preferences. We investigate the use of association rule mining as an underlying technology for collaborative recommender systems. Association rules have been used with success in other domains. However, most currently existing association rule mining algorithms were...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Theoretical and Applied Electronic Commerce Research
سال: 2023
ISSN: ['0718-1876']
DOI: https://doi.org/10.3390/jtaer18020043