Homework 1

Document Clustering

• Download docs.trn.tsv.

• Each line in the file represents a document, where the format is as follows:

  line ::= <label><tab><document>
  document ::= <token>(<space><token>)*
  

• Create a vector for each document using bag-of-words and TF-IDF. A sample python code for the vector creation can be found here: hw1.py.

• Implement and run the k-means clustering algorithm on all documents using both bag-of-words and TF-IDF, where k = 7.

• Experiment with different sets of randomly selected centroids. Measure the purity score of each trial.

• Implement and experiment with the k-means++ clustering algorithm and compare its results to the ones achieved by the k-means clustering algorithm.

• Write a report describing your approach, results, and analysis. Use the ACL latex template.

Submission

• Compress your code and report into hw1.zip and submit it to: https://canvas.emory.edu/courses/29596/assignments/30886