QuoraFolloweeRecommendation

• input data → web pages of questions of users
• output → users to follow, ranked
• two process
• personality based recommendation
• topic interest based recommendation
• intermediate data stored as json
• in topic hierarchy, for each node, find base topics at some level
• use networkx library to travel topic hierarchy
• find sort path(s) to root
• and find nodes at level in the ans
• other nodes which have the same nodes in this level
• and are closest means they posses similar interest in topics
• networkx is python library for complex networks
• personality recognizer module
• 5 vector personality test
• 0 to 7 score
• Linguistic Inquiry and Word Count → LIWC
• personality recognizer
• based on words used by user, find his intent or personality
• to do combination → 1st get results based on personality scores
• rank them based on topic hierarchy
• topic hierarchy
• topic tags