Originally designed as part of Virginia Tech's Crisis & Tragedy Recovery Network (CTRnet), this project crawls the internet and collects webpages related to a given topic, often for archival purposes.

• Driver class for this project
• Responsible for creating configuration and classifier object and calling crawler

• Crawler class responsible for collecting and exploring new URLs to find relevant pages
• Given a priority queue and a scoring class with a calculate_score(text) method

• Parent class of classifiers (non-VSM) including NaiveBayesClassifier and SVMClassifier

• Contains code for tokenization and vectorization of document text using sklearn

• Child classes only have to assign self.model

• NBClassifier.py

• Subclass of Classifier, representing a Naïve Bayes classifier

• SVMClassifier.py

• Subclass of Classifier, representing an SVM classifier

• Parent class of scorers, which are non-classifier models, typically VSM

• tfidfscorer.py

  • Subclass of Scorer, representing a tf-idf vector space model

• lsiscorer.py

  • Subclass of Scorer representing an LSI vector space model

• Configuration file for focused crawler in INI format

• Class responsible for reading configuration file, using ConfigParser
• Adds all configuration options to its internal dictionary (e.g. config[“seedFile”])

• Contains various utility functions relating to reading files and sanitizing/tokenizing text

• Contains URLs to relevant pages for focused crawler to start
• Default name, but can be modified in config.ini

• Simple implementation of a priority queue using a heap

• Uses BeautifulSoup and nltk to extract webpage text

For the full technical report, please visit: https://docs.google.com/file/d/0B436PtOU57sJZkc5anMyNDZPaHM/edit?usp=sharing