View a multi-dimensional time sequence database file with the MD Sequence Database Viewer (SPMF documentation)

Multi-dimensional time sequence databases are a type of data taken as input by some algorithms offered in SPMF such as the Fournier-Viger 2008 algorithm .

Put simply, a multi-dimensional timesequence database is a set of sequences that are annotated with some attributes (called dimensions), and that also contain timestamps.

SPMF offers a tool to view the content of a multi-dimensional time sequence database. This tool is called the MD Sequence Database Viewer.

This page explains how to use this tool with an example.

How to run this example?

If you want to run this example from the graphical interface of SPMF, (1) choose the algorithm "Open_md_time_sequence_database_with_viewer", (2) choose the ContextMDSequence.txt file as input, and then (3) click "run algorithm" .

• If you want to run this example from the source code of SPMF, run the file MainTestMDSequenceDatabaseViewerWithTime, which is located in the package ca.pfv.spmf.tests
• If you want to execute this example from the command line interface of SPMF, then execute this command:
  
  java -jar spmf.jar run Open_md_time_sequence_database_with_viewer ContextMDSequence.txt
  
  in a folder containing spmf.jar and the file ContextMDSequence.txt which is included with SPMF.

What is displayed?

After running the example, the content of the file will be displayed by the tool. The picture below shows the user interface of this viewer.

The window A) show in the picture below is the main window. It displays the multi-dimensional time sequence database using a table. The table has four rows in this example. Each row is a multi-dimensional sequence that contains two parts: dimension values (called an MD-pattern) and a sequence.

Take the first row as example. It represents a multi-dimensional sequence
The cell in the first column indicates that the values for the three dimensions of this multi-dimensional sequence are 1, 1 and 1, respectively.
The cell in the second column indicates that the sequence is defined as follows. First, two items 2 and 4 were observed at time 0, followed by the item 3 at time 1, followed by the item 2 at time 2, and finally followed by the item 1 at time 3.

The other multi-dimensional sequences follow the same format.

Besides, there are buttons that provides additional features:

• By clicking on the button "View sequence length distribution ", a new window is opened, presented as window B) in the picture below. This window displays the frequency histogram of the different sequence lengths in the current file. The number of sequences is the Y axis and the different sequence lengths are the X axis. There are some buttons in this window to export the data from the frequency histogram as a CSV file so that it can be imported in other software (e.g. Excel), or as a picture. Besides some options are provided to adjust the bar width and the order in which the X axis is sorted.
• By clicking on the button "View item frequency distribution ", a new window is opened, presented as window C) in the picture below. This window displays the frequency histogram for the frequency of the different items in the current file. The number of occurrences (or support) is the Y axis and the different items are displayed on the X axis. There are some buttons in this window to export the data from the frequency histogram as a CSV file so that it can be imported in other software (e.g. Excel), or as a picture. Besides some options are provided to adjust the bar width and the order in which the X axis is sorted.

What is the input?

The algorithm takes as input a multi-dimensional time sequence database, as used by algorithm such SEQ-DIM and DIM-SEQ .

The database used in this example is provided in the text file "ContextMDSequence.txt" in the package ca.pfv.spmf.tests of the SPMF distribution.

The input file format is defined as follows. It is a text file where each line represents a multi-dimensional time-extended sequence from a multi-dimensional time-extended sequence database. Each line consists of two parts.

• The first part is a list of dimension values separated by single spaces. A dimension value is a positive integer or the symbol "*" meaning "any values". Finally, the value "-3" indicates the end of the first part. Note that each line should have the same number of dimension values.
• The second part is a list of itemsets, where each itemset has a timestamp represented by a positive integer and each item is represented by a positive integer. Each itemset is first represented by its timestamp between the "<" and "> symbols. Then, the items of the itemset appear separated by single spaces. Finally, the end of an itemset is indicated by "-1". After all the itemsets, the end of a sequence (line) is indicated by the symbol "-2". Note that it is assumed that items are sorted according to a total order in each itemset and that no item appears twice in the same itemset.

For example, this is the content of the example file "ContextMDSequence.txt":

1 1 1 -3 <0> 2 4 -1 <1> 3 -1 <2> 2 -1 <3> 1 -1 -2
1 2 2 -3 <0> 2 6 -1 <1> 3 5 -1 <2> 6 7 -1 -2
1 2 1 -3 <0> 1 8 -1 <1> 1 -1 <2> 2 -1 <3> 6 -1 -2
* 3 3 -3 <0> 2 5 -1 <1> 3 5 -1 -2

Consider the second line. It indicates that the second multi-dimensional time-extended sequence of this database has the dimension values 1, 2 and 2. Furthermore, the first itemset is {2, 4} with a timestamp of 0. Then, the item 3 appears with a timestamp of 1. Then the item 2 appears with a timestamp of 2. Finally, the item 1 appears with a timestamp of 3. The other sequence follows the same format. Note that timestamps do not need to be consecutive integers. But they should increase for each succesive itemset within a same sequence.