GitHub - JFriel/honours_project: Honours project 2016/17 :- Timelining events in news articles

James Friel Honours Project 2016/17 "Event Ordering In News Articles" Supervisor: Shay Cohen

How to Run: Due to the large size of data retrieved from Wikipedia, it is unable to be stored on GitHub. To Gather Data yourself

getArticles.py will print to sdout a large set of event titles, their associated year and the article itself.
getDoubleSets.py will generate features of the form [[feature vector],[event1,event2], correct classification]

If you already have double set data

Run one of the available graph generating scripts (MLP.py is reccomended) this will generate an accuracy and will print a dictionary where the value of each key are events that have edges pointing to them from the key.
Save the dictionary
Run pathFinder.py to generate optimal pathing and Tau measurment (Warning, this is fragile)

Name		Name	Last commit message	Last commit date
Latest commit History 163 Commits
app		app
data		data
latex		latex
networkx		networkx
poster		poster
venv		venv
#structured-perceptron.py#		#structured-perceptron.py#
.gitignore		.gitignore
DT.results.title		DT.results.title
LICENSE		LICENSE
LR.results.title		LR.results.title
MLP.py		MLP.py
MLP.py.1		MLP.py.1
MLP.py.1~		MLP.py.1~
MLP.py~		MLP.py~
MLP.results		MLP.results
MLP.results.title		MLP.results.title
MLP.results.title~		MLP.results.title~
README.md		README.md
ShortNoDate.txt		ShortNoDate.txt
__init__.py		__init__.py
class.py		class.py
classifier-title.py		classifier-title.py
classifier-triple.py		classifier-triple.py
classifier-tripple-title.py		classifier-tripple-title.py
classifier.py		classifier.py
decisiontree.results		decisiontree.results
dt.results.title.triple		dt.results.title.triple
dt.results.triple		dt.results.triple
dt.results.triple.title		dt.results.triple.title
getArticle.py		getArticle.py
getArticle.py~		getArticle.py~
getDoubleSets.py		getDoubleSets.py
getDoubleSets.py~		getDoubleSets.py~
getPath.py		getPath.py
getarticles.py		getarticles.py
index.py		index.py
logirsticregression.results		logirsticregression.results
logistic-regression.py		logistic-regression.py
lr.results.title.triple		lr.results.title.triple
lr.results.triple		lr.results.triple
mlp.results.title		mlp.results.title
mlp.results.title.triple		mlp.results.title.triple
mlp.results.triple		mlp.results.triple
mlp.results.triple.title		mlp.results.triple.title
nn.py		nn.py
pathFinder.py		pathFinder.py
pathFinder.py.1		pathFinder.py.1
pathFinder.py.1~		pathFinder.py.1~
perceptron-output.txt		perceptron-output.txt
perceptron.py		perceptron.py
perceptron.results		perceptron.results
perceptron.results.title		perceptron.results.title
perceptron.results.title.triple		perceptron.results.title.triple
perceptron.results.triple		perceptron.results.triple
perceptron.results.triple.title		perceptron.results.triple.title
probs.csv		probs.csv
randomForest.py		randomForest.py
regression.py		regression.py
requirements.txt		requirements.txt
run		run
setup1.py		setup1.py
setup2.py		setup2.py
singleSetTest.txt		singleSetTest.txt
singleSets.txt		singleSets.txt
structured-perceptron.py		structured-perceptron.py
svc.result		svc.result
svm.restuts.title		svm.restuts.title
svm.results.py		svm.results.py
svm.results.py~		svm.results.py~
svm.results.title		svm.results.title
svm.results.title.triple		svm.results.title.triple
svm.results.triple		svm.results.triple
svm.results.triple.title		svm.results.triple.title
svm.results.triple.title~		svm.results.triple.title~
testDoubleSet		testDoubleSet
testing.py		testing.py
texput.log		texput.log
tmp.py		tmp.py
tmp.txt		tmp.txt
trainDoubleSet		trainDoubleSet

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JFriel/honours_project

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