Embedding-based Detection and Extraction of Research Topics from Academic Documents Using Deep Clustering.
Sahand VahidniaAlireza AbbasiHussein A. AbbassPublished in: J. Data Inf. Sci. (2021)
Keyphrases
- document clustering
- topic detection
- topic discovery
- information retrieval
- document clusters
- text documents
- document collections
- clustering algorithm
- topic extraction
- topic models
- covering a wide range
- document set
- keywords
- text clustering
- vector space
- newspaper articles
- clustering method
- related topics
- anomaly detection
- latent topics
- information extraction
- topic modeling
- web documents
- cluster analysis
- latent dirichlet allocation
- metadata
- k means
- cosine similarity
- information retrieval systems
- key concepts
- text data
- document corpus
- text classification
- relevant documents
- xml documents
- document retrieval
- document representation
- vector space model
- text collections
- document classification
- relevance assessments
- topic specific
- detection algorithm
- highly relevant
- statistical topic models
- google scholar
- related documents
- scientific literature
- user interests
- spectral clustering
- test collection
- text mining
- data points