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SERF: Stanford Entity Resolution Framework

A modified/updated branch of SERF by trevorprater (May 2015).

Original work done by Stanford InfoLab (April 2006).

Introduction

The SERF project develops a generic infrastructure for Entity Resolution (ER). ER is the task of identifying and combining data records that represent the same real-life entities (e.g., customers, or products).

This release of the SERF software provides an implementation of the R-Swoosh algorithm described in reference [1]. The algorithm takes as input a dataset of records (in CSV) and a "MatcherMerger" class that implements functions to match and merge pairs of records, and returns a dataset of resolved records.

A sample dataset of product records, along with a simple MatcherMerger implementation is provided as an example (in the /example directory). Records are matched based on the similarity of their titles (using a Jaro-Winkler distance) and prices (through a relative difference).

The source code of the SERF package is included (in the /src directory), and is released under the BSD licence (see LICENSE).

Requirements

• JDK6+

• The MatcherMerger class of the example uses the CMU secondstring library (http://secondstring.sourceforge.net/) to measure the similarity of product titles. For convenience, a jar of the library is provided under /lib. The license of the secondstring package is reproduced in the secondstring.LICENSE file, under /libs

Customizing SERF

Let's see now how to use to SERF package to run entity resolution, on your own data, with your own functions to match and merge records.

• Input data should be of CSV format.

• A matcherMerger class should implement the simple serf.data.MatcherMerger interface, which is described in

  [SERF_INSTALL]/doc/javadoc/serf/data/MatcherMerger.html

Where [SERF_INSTALL] is the location of your serf installation.

• A configuration file similar to example.conf should be provided, that points to your input data file and MatcherMerger implementation, and specifies the desired location for the output file.

• The SERF package can then be run as:

  java -cp "[SERF_INSTALL]/serf.jar:[YOURCP]" serf.ER your.conf

Where [YOURCP] represents a user defined classpath.

[YOURCP] should include the path to your MatcherMerger implementation and any libraries it relies on.

Compiling the source code

From the [SERF_INSTALL] directory, create a "classes" directory:

cd [SERF_INSTALL]
mkdir classes

Go to the src directory:

 cd src

Then compile the SERF code:

javac -cp ../libs  -d ../classes @sources

IntelliJ IDEA

This project can also be imported as a Gradle build or directly into IntelliJ. It was rebuilt/repackaged in IntelliJ IDEA 14 CE.

References

[1] Swoosh: A Generic Approach to Entity Resolution Omar Benjelloun, Hector Garcia-Molina, Jeff Jonas, Qi Su, Jennifer Widom. Stanford University Technical Report, 2005. Available at: http://dbpubs.stanford.edu:8090/pub/2005-5