Mining Skyline Frequent-Utility Patterns using the EMSFUI_D algorithm (SPMF documentation)

This example explains how to run the EMSFUI_D algorithm using the SPMF open-source data mining library.

How to run this example?

• If you are using the graphical interface, (1) choose the "EMSFUI_D" algorithm, (2) select the input file "contextHUIM.txt", (3) set the output file name (e.g. "output.txt") and (4) click "Run algorithm".
• If you want to execute this example from the command line, then execute this command:
  java -jar spmf.jar run EMSFUI_D contextHUIM.txt output.txt in a folder containing spmf.jar and the example input contextHUIM.txt.
• If you are using the source code version of SPMF, launch the file "MainTestEMSFUI_D.java" in the package ca.pfv.SPMF.tests.

What is EMSFUI_D?

EMSFUI_D is an algorithm for discovering skyline frequent-utility patterns (SFUPs) in a transaction database containing utility information. The EMSFUI_D algorithm discovers SFUPs by exploring a utility-list structure using a depth-first search.

 What is the input?

EMSFUI_D takes as input a transaction database with utility information. Let's consider the following database consisting of 7 transactions (t1,t2, ..., t7) and 5 items (1, 2, 3, 4, 5). This database is provided in the text file "contextHUIM.txt" in the package ca.pfv.spmf.tests of the SPMF distribution.

Each line of the database is:

• a set of items (the first column of the table),
• the sum of the utilities (e.g. profit) of these items in this transaction (the second column of the table),
• the utility of each item for this transaction (e.g. profit generated by this item for this transaction)(the third column of the table).

Note that the value in the second column for each line is the sum of the values in the third column.
What are real-life examples of such a database? There are several applications in real life. One application is a customer transaction database. Imagine that each transaction represents the items purchased by a customer. The first customer named "t1" bought items 2, 3 and 4. The amount of money spent for each item is respectively 2 $, 2 $ and 5 $. The total amount of money spent in this transaction is 2 + 2 + 5 = 9 $.

What is the output?

The output of EMSFUI_D is the set of skyline frequent-utility patterns. An itemset X in a database D is a skyline frequent-utility patterns (SFUP) iff it is not dominated by any other itemset in the database by considering both the frequent and utility factors. An itemset X dominates another itemset Y in D, iff f(X) >= f(Y) and u(X) >= u(Y). For example, if we run EMSFUI_D, we obtain 3 skyline frequent-utility patterns.

Input file format

The input file format of EMSFUI_D is defined as follows. It is a text file. Each lines represents a transaction. Each line is composed of three sections, as follows.

• First, the items contained in the transaction are listed. An item is represented by a positive integer. Each item is separated from the next item by a single space. It is assumed that all items within a same transaction (line) are sorted according to a total order (e.g. ascending order) and that no item can appear twice within the same transaction.
• Second, the symbol ":" appears and is followed by the transaction utility (an integer).
• Third, the symbol ":" appears and is followed by the utility of each item in this transaction (an integer), separated by single spaces.

For example, for the previous example, the input file is defined as follows:
2 3 4:9:2 2 5
1 2 3 4 5:18:4 2 3 5 4
1 3 4:11:4 2 5
3 4 5:11:2 5 4
1 2 4 5:22:5 4 5 8
1 2 3 4:17:3 8 1 5
4 5:9:5 4

Consider the first line. It means that the transaction {2, 3, 4} has a total utility of 9 and that items 2, 3 and 4 respectively have a utility of 2, 2 and 5 in this transaction. The following lines follow the same format.

Output file format

The output file format of the algorithm is defined as follows. It is a text file, the first line record the count of skyline frequent-utility patterns. And each following line represents a skyline frequent-utility pattern. On each line, the items of the itemset are first listed. Each item is represented by an integer, followed by a single space. After, all the items, the keyword "#SUP:" appears, which is followed by a integer value indicating the support of that itemset and the keyword " #UTIL: " appears and is followed by the utility of the itemset. For example, we show below the output file for this example.
Total skyline frequent-utility itemset: 3
2 1 4 #SUP:3 #UTIL:41
5 4 #SUP:4 #UTIL:40
4 #SUP:7 #UTIL:35

For example, the first line indicates that there are 3 skyline frequent-utility patterns in the example. The second line indicates that the itemset {2, 1, 4} is a skyline frequent-utility itemset which has support equals to 3 and utility equals to 41. The following lines follows the same format.

Implementation details

The version implemented here is the original implementation of EMSFUI_D. Note that the input format is not exactly the same as described in the original article. But it is equivalent.

Where can I get more information about the EMSFUI_D algorithm?

This is the reference of the article describing the EMSFUI_D algorithm:

Xuan Liu, Genlang Chen, Wanli Zuo (2022) Effective algorithms to mine skyline frequent-utility itemsets. EAAI journal.

Besides, for a general overview of high utility itemset mining, you may read this survey paper.