i am working on my final year project that is a social network. Based on user interest, i have to add him in groups based on area he lives in, age group, interest type, gender and some other features.i have to use machine learning to predict in which group should i place him. I am thinking of using classification but i need data set to train which i don't have at all nor there is any data set related to this problem, so if any one of you guide me in right direction how can i do this ?
As far as I know you shouldn't use ML at this stage. There are two problems:
- You can not get enough data related to your task.
- Even anyhow you manage to get the data it will be either to general or
will be some other domain based so relying on the result would be difficult.
Instead you can write some rule based or weighted value solutions like depending upon the type of group what age-group should be part of the group. Regular expressions to extract some keywords from interest tags and other text features and these can be used to decide the probability of a person falling into a group.
Once if you have enough data and their labels using this method you can start trying ML algorithms and they will give the results.