On Mining Most Popular Packages

Volume 9, Issue 4, Page No 60-72, 2024

Author’s Name: Yangjun Chen*, Bobin Chen

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Department of Applied Computer Science, University of Winnpeg, Manitoba, R3B 2E9, Canada

^a)whom correspondence should be addressed. E-mail: y.chen@uwinnipeg.ca

Adv. Sci. Technol. Eng. Syst. J. 9(4), 60-72 (2024); DOI: 10.25046/aj090407

Keywords: Data Mining, Most popular packages, NP-complete, Priority-first tree search, Tries, Trie-like graphs

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Abstract

In this paper, we will discuss two algorithms to solve the so-called package design problem, by which a set of queries (referred to as a query log) is represented by a collection of bit strings with each indicating the favourite activities or items of customers. For such a query log, we are required to design a package of activities (or items) so that as many customers as possible can be satisfied. It is a typical problem of data mining. For this problem, the existing algorithm requires at least O(n2m) time, where m is the number of activities (or items) and n is the number of queries. We try to improve this time complexity. The main idea of our first algorithm is to use a new tree search strategy to explore the query log. Its average time complexity is bounded by O(nm2 + m2m/2). By our second algorithm, all query bit strings are organized into a graph, called a trie-like graph. Searching such a graph bottom-up, we can find a most popular package in O(n2m3(log2 nm)log2 nm) time. Both of them work much better than any existing strategy for this problem.

Received: 22 April 2024, Revised: 11 June 2024, Accepted: 31 July 2024, Published Online: 07 August, 2024

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On Mining Most Popular Packages