Book ChapterDOI
A Diversification-Aware itemset Placement Framework for Long-term Sustainability of Retail Businesses
Parul Chaudhary,Anirban Mondal,Polepalli Krishna Reddy +2 more
- pp 103-118
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TLDR
This paper presents a framework and schemes for efficiently retrieving the top-utility itemsets of any given itemset size based on both revenue as well as the degree of diversification and shows the overall effectiveness and scalability of the proposed schemes.Abstract:
In addition to maximizing the revenue, retailers also aim at diversifying product offerings for facilitating sustainable revenue generation in the long run. Thus, it becomes a necessity for retailers to place appropriate itemsets in a limited k number of premium slots in retail stores for achieving the goals of revenue maximization and itemset diversification. In this regard, research efforts are being made to extract itemsets with high utility for maximizing the revenue, but they do not consider itemset diversification i.e., there could be duplicate (repetitive) items in the selected top-utility itemsets. Furthermore, given utility and support thresholds, the number of candidate itemsets of all sizes generated by existing utility mining approaches typically explodes. This leads to issues of memory and itemset retrieval times. In this paper, we present a framework and schemes for efficiently retrieving the top-utility itemsets of any given itemset size based on both revenue as well as the degree of diversification. Here, higher degree of diversification implies less duplicate items in the selected top-utility itemsets. The proposed schemes are based on efficiently determining and indexing the top-λ high-utility and diversified itemsets. Experiments with a real dataset show the overall effectiveness and scalability of the proposed schemes in terms of execution time, revenue and degree of diversification w.r.t. a recent existing scheme.read more
Citations
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Journal ArticleDOI
An improved scheme for determining top-revenue itemsets for placement in retail businesses
TL;DR: This paper proposes a novel flexible and efficient index, designated as Slot Type Utility (STU) index, for facilitating quick retrieval of the top-utility itemsets for a given number of slots, and conducts an extensive performance evaluation to demonstrate the overall effectiveness of the STU index.
Book ChapterDOI
An Efficient Premiumness and Utility-Based Itemset Placement Scheme for Retail Stores
TL;DR: This paper proposes the notion of premiumness of slots in a given retail store, and discusses a framework for efficiently identifying itemsets from a transactional database and placing these itemsets by mapping itemsets with different revenue to slots with varied premiumness for maximizing retailer revenue.
Proceedings ArticleDOI
PEAR: A Product Expiry-Aware and Revenue-Conscious Itemset Placement Scheme
TL;DR: In this paper, a Product Expiry-Aware and Revenue-conscious itemset placement scheme is proposed for improving retailer revenue. But, the authors do not consider the time-period of expiry across items.
Journal ArticleDOI
A framework for itemset placement with diversification for retail businesses
TL;DR: This work proposes an efficient framework for retrieval of high-revenue itemsets with a varying size and a varying degree of diversification, and proposes the kUI (kU tility I temset) index for quick and efficient retrieval of diverse top-λ high- re revenue itemsets.
Proceedings ArticleDOI
Improving Product Placement in Retail with Generalized High-Utility Itemsets
TL;DR: This work proposes the generalized utility itemset (GUI) index for retrieving generalized high-utility (revenue) itemsets and presents a framework, which leverages the GUI index towards retail product placement to improve revenue.
References
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Proceedings Article
Fast Algorithms for Mining Association Rules in Large Databases
Journal ArticleDOI
Mining frequent patterns without candidate generation
Jiawei Han,Jian Pei,Yiwen Yin +2 more
TL;DR: This study proposes a novel frequent pattern tree (FP-tree) structure, which is an extended prefix-tree structure for storing compressed, crucial information about frequent patterns, and develops an efficient FP-tree-based mining method, FP-growth, for mining the complete set of frequent patterns by pattern fragment growth.
Book ChapterDOI
Discovering Frequent Closed Itemsets for Association Rules
TL;DR: This paper proposes a new algorithm, called A-Close, using a closure mechanism to find frequent closed itemsets, and shows that this approach is very valuable for dense and/or correlated data that represent an important part of existing databases.
Proceedings ArticleDOI
Mining high utility itemsets without candidate generation
Mengchi Liu,Junfeng Qu +1 more
TL;DR: This paper proposes an algorithm, called HUI-Miner (High Utility Itemset Miner), which can efficiently mine high utility itemsets from the utility-lists constructed from a mined database and compares it with the state-of-the-art algorithms on various databases.
Proceedings ArticleDOI
Mining high utility itemsets
TL;DR: A new pruning strategy based on utilities that allow pruning of low utility itemsets to be done by means of a weaker but antimonotonic condition is developed and shows that it does not require a user specified minimum utility and hence is effective in practice.