Reputation: 812
I am working on a personal project. I worked on some publicly available data sets. I have to build a text recommendation system that suggest users meaning full text(1 -2 lines) based on pre-defined rules.
How do I go about building a text recommendation system and how do I define the rules (The rules are simple checks like AC, then suggest a text if not suggest alternate text). I also need to know how I can make the system learn by itself to update rules
ANy inputs, links to research papers, github links etc will help
Upvotes: 1
Views: 182
Reputation: 416
First of all, you will be encountering a cold start problem.
The simple solution would be to recommend all-time favorites text. More sophisticated solutions are here.
Thereafter you can use collaborative filtering by collecting implicit data like views, clicks, comment , bookmarks of the text. Because users seldom give ratings. So you can use implicit data as: 'VIEW': 1.0, 'LIKE': 2.0, 'BOOKMARK': 3.0, 'FOLLOW': 4.0, 'COMMENT CREATED': 5.0, as ratings.
This kind of reccomender system can be found here
Upvotes: 2