Partition-based Similarity Search (PSS)

A Partition-based Similarity Search as described in [1][2]. The package takes an input of the format <DocID: word1 word2..> as bag of words and output the pair of document IDs that have a Cosine-based similarity value >= threshold. The framework used is the Java-based MapReduce framework provided by Apache Hadoop.

Installation:

1. clone the repository as:

2. make sure 'ant','java','javac' are installed by typing them into the command line.

3. make sure you have hadoop setup following[ http://hadoop.apache.org/docs/r0.19.0/quickstart.html#Download ]

Package overview:

README src/: build/: conf/: target/: conf/lib:

Quick start:

1. Copy the project: git clone git@github.com:mahaucsb/pss.git
2. Setup the following environment variables:

   • HADOOP_HOME: to the location of your hadoop directory. Eg.$ export HADOOP_HOME=/home/maha/hadoop-1.0.1

   • JAVA_HOME:

     For Linux: export JAVA_HOME=/usr/lib/jvm/java-openjdk //this is just an example

     For MAC: export JAVA_HOME=/System/Library/Frameworks/JavaVM.framework/Versions/1.6/Home

   • JAVA_VERSION:

     For MAC: export JAVA_VERSION=java -version 2>&1 | head -n 1 | cut -d\" -f 2 | cut -f1 -f2 -d"."

     In linux: export JAVA_VERSION=java -version 2>&1| head -n 1 | cut -d \" -f 2 | cut -d . -f1,2

     Else: export JAVA_VERSION=1.6 //depending on your java version

Configurations:

Dataset:

Solutions to common errors:

References:

[1] "Optimizing Parallel Algorithms for All Pairs Similarity Search".M.Alabduljalil,X.Tang,T.Yang.WSDM'13.

[2] "Cache-Conscious Performance Optimization for Similarity Search".M.Alabduljalil,X.Tang,T.Yang.SIGIR'13.