Are Topics Interesting or Not? An LDA-based Topic-graph Probabilistic Model for Web Search Personalization.
Jiashu ZhaoJimmy Xiangji HuangHongbo DengYi ChangLong XiaPublished in: ACM Trans. Inf. Syst. (2022)
Keyphrases
- probabilistic model
- topic models
- web search
- latent dirichlet allocation
- personalized web search
- topic modeling
- topic drift
- related topics
- topic discovery
- search engine
- generative model
- personalized search
- user interests
- latent topics
- hot topics
- topic specific
- topic detection
- trend analysis
- web search engines
- emerging topics
- user profiles
- random walk
- language model
- search experience
- link information
- search result
- directed graph
- text documents
- bayesian networks
- improving web search
- statistical topic models
- anchor text
- structured data
- citation networks
- text streams
- web queries
- document set
- weighted graph
- news topics
- topic hierarchy
- recommender systems
- social tagging
- web search queries
- result lists
- graph structure
- web pages