On-shelf Utility Mining of Sequence Data

by   Chunkai Zhang, et al.

Utility mining has emerged as an important and interesting topic owing to its wide application and considerable popularity. However, conventional utility mining methods have a bias toward items that have longer on-shelf time as they have a greater chance to generate a high utility. To eliminate the bias, the problem of on-shelf utility mining (OSUM) is introduced. In this paper, we focus on the task of OSUM of sequence data, where the sequential database is divided into several partitions according to time periods and items are associated with utilities and several on-shelf time periods. To address the problem, we propose two methods, OSUM of sequence data (OSUMS) and OSUMS+, to extract on-shelf high-utility sequential patterns. For further efficiency, we also designed several strategies to reduce the search space and avoid redundant calculation with two upper bounds time prefix extension utility (TPEU) and time reduced sequence utility (TRSU). In addition, two novel data structures were developed for facilitating the calculation of upper bounds and utilities. Substantial experimental results on certain real and synthetic datasets show that the two methods outperform the state-of-the-art algorithm. In conclusion, OSUMS may consume a large amount of memory and is unsuitable for cases with limited memory, while OSUMS+ has wider real-life applications owing to its high efficiency.


page 3

page 4

page 6

page 8

page 9

page 13

page 14

page 22


HUSP-SP: Faster Utility Mining on Sequence Data

High-utility sequential pattern mining (HUSPM) has emerged as an importa...

Seasonal Goods and Spoiled Milk: Pricing for a Limited Shelf-Life

We examine the case of items with a limited shelf-life where storing an ...

A Generic Algorithm for Top-K On-Shelf Utility Mining

On-shelf utility mining (OSUM) is an emerging research direction in data...

TKUS: Mining Top-K High-Utility Sequential Patterns

High-utility sequential pattern mining (HUSPM) has recently emerged as a...

High-utility itemset mining for subadditive monotone utility functions

High-utility Itemset Mining (HUIM) finds itemsets from a transaction dat...

Towards Sequence Utility Maximization under Utility Occupancy Measure

The discovery of utility-driven patterns is a useful and difficult resea...

Explainable Fuzzy Utility Mining on Sequences

Fuzzy systems have good modeling capabilities in several data science sc...

Please sign up or login with your details

Forgot password? Click here to reset