Web advertising recommender system based on estimating users' latent interests.
Yuriko YamaguchiMimpei MorishitaYoichi InagakiReyn Y. NakamotoJianwei ZhangJunichi AoiShinsuke NakajimaPublished in: iiWAS (2016)
Keyphrases
- recommender systems
- user interests
- user profiles
- information overload
- user generated content
- collaborative filtering
- user profiling
- web content
- user model
- recommendation systems
- information sources
- user preferences
- individual user
- personalized recommendation
- web mining
- web portal
- personalized search
- website
- end users
- recommendation quality
- web applications
- web resources
- information filtering
- cold start problem
- internet users
- product recommendation
- user behavior
- personal interests
- web information
- user ratings
- browsing behavior
- active user
- user centric
- social media
- implicit feedback
- personalized services
- online dating
- web logs
- user experience
- web documents
- personal preferences
- semantic web
- user interface
- social awareness
- web browsing
- advertising campaigns
- internet advertising
- content based filtering
- viral marketing
- matrix factorization
- social networking sites
- social networks
- data sparsity
- social relationships
- user communities