Feature/adding relevance scores

This PR adds a feature to dbpedia-spotlight, namely, weights associated with the annotations extracted.To do so, all you need to do is add a line containing `relevance_scoring=default` to your `model.properties` file in the model folder. If that line is not present, spotlight behaves as usual.

We use:
 - the context vector overlap
 - number a times a topic is spotted in the text
 - the overlap among context words for the topics. For example "Microsoft" being a context words for the topics.
 - We normalize the output score using min-max normalization (0-1) ( this step could be improved)

Given some toy data that we had manually annotated, we realized that this method gives results close to human judgements than those given by other topic extractors such as Zemanta or Alchemy. If you think this is a good idea, we could manually annotate some establish dataset, like the milne witten, and write a paper as an attempt to reproduce the results in a more formal way.