Clustering search engine suggests by integrating a topic model and word embeddings.
Tian NieYi DingChen ZhaoYouchao LinTakehito UtsuroYasuhide KawadaPublished in: SNPD (2017)
Keyphrases
- topic models
- latent topics
- search engine
- co occurrence
- latent dirichlet allocation
- topic discovery
- topic modeling
- latent topic models
- word pairs
- probabilistic latent semantic analysis
- clustering algorithm
- text documents
- statistical topic models
- text mining
- generative model
- web search
- latent variables
- document clustering
- keywords
- k means
- high dimensional data
- text corpora
- web pages
- baseline models
- information retrieval
- vector space
- probabilistic model
- low dimensional
- variational inference
- probabilistic topic models
- multi view
- dimensionality reduction
- lda model
- microblog posts
- data points