Hi,
I'm working on a project at the moment where I need to pick out the most common phrases in a huge body of text. For example say we have three sentences like the following:
- The dog jumped over the woman.
- The dog jumped into the car.
- The dog jumped up the stairs.
From the above example I would want to extract "the dog jumped" as it is the most common phrase in the text. At first I thought, "oh lets use a directed graph [with repeated nodes]":
EDIT: Apologies, I made a mistake while making this diagram "over", "into" and "up" should all link back to "the".
I was going to maintain a count of how many times a word occurred in each node object ("the" would be 6; "dog" and "jumped", 3; etc.) but despite many other problems the main one came up when we add a few more examples like (please ignore the bad grammar :-)):
- Dog jumped up and down.
- Dog jumped like no dog had ever jumped before.
- Dog jumped happily.
We now have a problem since "dog" would start a new root node (at the same level as "the") and we would not identify "dog jumped" as now being the most common phrase. So now I am thinking maybe I could use an undirected graph to map the relationships between all the words and eventually pick out the common phrases but I'm not sure how this is going to work either, as you lose the important relationship of order between the words.
So does anyone have any general ideas on how to identify common phrases in a large body of text and what data structure I would use.
Thanks, Ben