This repository contains the code developed for my master's thesis in Computer Engineering at University of Padova, supervised by Professor Fabio Vandin.
The focus for this work was to find an upper bound on the sample size required for sequential pattern mining, while providing rigorous guarantees on the results obtained from the sample with respect to the results that would be obtained from the whole dataset.
This project is copyright of Andrea Tonon and it licensed under the Apache License 2.0, as also described in the file LICENSE.
The code for this project has been developed using IntelliJ IDE, JAVA, the Apache Spark Framework and the SPMF library.
The classes MainSPMF and MainSpark provide an usage example, respectively of the sequential and parallel/distributed versions, with the MSNBC_SPMF dataset provided in the Data folder.
Required VM options:
- -XmxRG: allows to specify the maximum memory allocation pool for a Java virtual machine (JVM), where R must be replaced with an integer that represents the maximum memory in GB;
- -Dspark.master="local[X]": only for the Spark version, X must be repleaced with the number of cores of your machine.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
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Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
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Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
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Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
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