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CRF++ is a simple, customizable, and open source implementation of Conditional Random Fields (CRFs) for segmenting/labeling sequential data. CRF++ is designed for generic purpose and will be applied to a variety of NLP tasks.
GSA Cloud Reporting Framework (CRF) is an open source framework, written in Java, that allows Google Search Appliance administrators to gather and record GSA users activity for reporting purposes. As an example, this version of the framework implements classes for storing the information in two different repositories: App Engine data store and Google Apps Spreadsheet. The project is ready for deployment in Google App Engine for Java.
By applying Natural Language Processing, Machine Learning and some IR techniques, I am working on a research project to build up an automated framework to extract time and events from news articles, with the hope of promoting efficiencies of readers (help readers form a general knowledge about an unfamiliar news topic against a timeline in a relative short of time). Simply put, I implemented four baselines and trained them with TimeBank Corpus: a Dictionary Lookup classifier, variants of Naive B