Mining Vague Association Rules
نویسندگان
چکیده
In many online shopping applications, traditional Association Rule (AR) mining has limitations as it only deals with the items that are sold but ignores the items that are almost sold. For example, those items that are put into the basket but not checked out. We say that those almost sold items carry hesitation information since customers are hesitating to buy them. The hesitation information of items is valuable knowledge for the design of good selling strategies. We apply vague set theory in the context of AR mining as to incorporate the hesitation information into the ARs. We define the concepts of attractiveness and hesitation of an item, which represent the overall information of a customer’s intent on an item. Based on these two concepts, we propose the notion of Vague Association Rules (VARs) and devise an efficient algorithm to mine the VARs. Our experiments show that our algorithm is efficient and the VARs capture more specific and richer information than traditional ARs.
منابع مشابه
Vague Set Theory for Profit Pattern and Decision Making in Uncertain Data
Problem of decision making, especially in financial issues is a crucial task in every business. Profit Pattern mining hit the target but this job is found very difficult when it is depends on the imprecise and vague environment, which is frequent in recent years. The concept of vague association rule is novel way to address this difficulty. Merely few researches have been carried out in associa...
متن کاملElephant Herding Optimization based Vague Association Rule Mining Algorithm
Huge amount of data is being gathered, processed and analyzed in every sector to derive useful information. So, automated tool like data mining has evolved in order to extract information and solve the overhead in manual approach. Association rule mining which is an essential part of data mining fails to address the vague and uncertain situations. In shopping applications, traditional approach ...
متن کاملIntegrating Vague Association Mining with Markov Model
The increasing demand of World Wide Web raises the need of predicting the user’s web page request. The most widely used approach to predict the web pages is the pattern discovery process of Web usage mining. This process involves inevitability of many techniques like Markov model, association rules and clustering. Fuzzy theory with different techniques has been introduced for the better results...
متن کاملA New Approach of Eliminating Redundant Association Rules
Two important constraints of association rule mining algorithm are support and confidence. However, such constraints-based algorithms generally produce a large number of redundant rules. In many cases, if not all, number of redundant rules is larger than number of essential rules, consequently the novel intention behind association rule mining becomes vague. To retain the goal of association ru...
متن کاملMining Hesitation Information by Vague Association Rules
In many online shopping applications, such as Amazon and eBay, traditional Association Rule (AR) mining has limitations as it only deals with the items that are sold but ignores the items that are almost sold (for example, those items that are put into the basket but not checked out). We say that those almost sold items carry hesitation information, since customers are hesitating to buy them. T...
متن کامل