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https://github.com/thammegowda/autoextractor

A toolkit for clustering web pages based on various similarity measures.
https://github.com/thammegowda/autoextractor

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A toolkit for clustering web pages based on various similarity measures.

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README

        

# Moved to https://github.com/uscdataScience/autoextractor

# Auto Extractor
An intelligent extractor library which learns the structures of the input web pages and then figures out a strategy for scraping the structured content

NOTE : The project is under active development, as a result the README is out of sync with the codebase.

TODO: update this file with the description of all new features.

# Example Usage:
## 1. Structural Similarity Between HTML/XML documents


$ mvn clean compile package
$ java -cp target/autoextractor-0.1-SNAPSHOT-jar-with-dependencies.jar edu.usc.irds.autoext.tree.ZSTEDComputer \
-dir src/test/resources/html/simple/

#Index File Path
0 /home/tg/work/projects/oss/autoextractor/src/test/resources/html/simple/3.html
1 /home/tg/work/projects/oss/autoextractor/src/test/resources/html/simple/2.html
2 /home/tg/work/projects/oss/autoextractor/src/test/resources/html/simple/1.html

#Similarity Matrix
0.000000 13.000000 10.000000
13.000000 0.000000 3.000000
10.000000 3.000000 0.000000

## 2. Clustering based on style and structure


$ mvn clean package
$ java -cp target/autoextractor-0.1-SNAPSHOT-jar-with-dependencies.jar edu.usc.irds.autoext.cluster.FileClusterer
Option "-list" is required
-list FILE : path to a file containing paths to html files that requires
clustering
-workdir FILE : Path to directory to create intermediate files and reports

# Creating input list of htmls
$ find src/test/resources/html/simple/ -type f > list.txt

# Cluster
$ java -cp target/autoextractor-0.1-SNAPSHOT-jar-with-dependencies.jar edu.usc.irds.autoext.cluster.FileClusterer \
-list list.txt -workdir out

# Report
$ cat out/report.txt

# Similarity Matrix
$ cat out/gross-sim.csv

# Clusters
$ cat out/clusters.txt
##Total Clusters:2

#Cluster:0
src/test/resources/html/simple/3.html

#Cluster:1
src/test/resources/html/simple/2.html
src/test/resources/html/simple/1.html


# Developers:
* [Thamme Gowda, USC](mailto:[email protected])
* [Chris Mattmann, USC & NASA JPL]()

# References :
+ K. Zhang and D. Shasha. 1989. "Simple fast algorithms for the editing distance between trees and related problems". SIAM J. Comput. 18, 6 (December 1989), 1245-1262.
+ Jarvis, R.A.; Patrick, Edward A., "Clustering Using a Similarity Measure Based on Shared Near Neighbors," in Computers, IEEE Transactions on , vol.C-22, no.11, pp.1025-1034, Nov. 1973