Automatic Tagging and Recommendation of News Articles using Wikipedia

In today' digital era, it is more important than ever before for the Chronicle Herald to stand by its motto of"Connecting you to what matters". Defining the "what matters" is the key challenge. Are you interested in anynews about Nova Scotia Power, your kid's hockey team, the weather, municipal politics, etc. When is the besttime to offer short news briefs and context of what to expect that day? When and on what device are peoplereading long form journalism? What topics keep you reading longer? If we presented more of what you want,would you now make more time to read it - would you simply get lost in time and stick with the experience?Recommender systems have been around for a long time. Dating services, Amazon.com, Netflix and Applehave all worked on relevancy algorithms to ensure that perfect match. We need to discover and amplify theconnection between reader and content. Profile building and predicting what the person's next move will be iskey to the future of the news industry. Having customers more engaged and deeply entrenched in the contentwill come when we provide them with more content they want to read, hear and view in the form they expecton the particular device or medium they are engaged with at the time.The Chronicle Herald has more and more data being collected on its subscribers and on-line readers. It istime to start using this data to begin recommending what matters to the individual based on the informationthey provide and the behaviours they portray at the same time finding the trends in relevant social space to putcontent in front of folk before anyone else knows.This project aims to build the foundation for connecting readers with news by automatically assigning tagsto news by making use of Wikipedia, the collaboratively built, multilingual, hyperlinked, on-line encyclopedicknowledge base.