Representing Documents and Queries as Sets of Word Embedded Vectors for Information Retrieval.
Dwaipayan RoyDebasis GangulyMandar MitraGareth J. F. JonesPublished in: CoRR (2016)
Keyphrases
- information retrieval
- query terms
- retrieval systems
- boolean queries
- information retrieval systems
- user queries
- relevant documents
- term weighting
- document collections
- query words
- document space
- structured documents
- distributed information retrieval
- retrieval process
- trec collections
- vector space model
- text queries
- test collection
- ad hoc retrieval
- document retrieval
- related documents
- co occurrence
- retrieval strategies
- retrieval effectiveness
- improve retrieval effectiveness
- retrieval model
- stop words
- text retrieval
- text collections
- language model
- relevance ranking
- compound words
- retrieved documents
- concept space
- query expansion
- search engine
- n gram
- language modeling
- relevance judgements
- relevance judgments
- vector space
- query refinement
- tf idf
- query processing
- keywords
- term frequency
- result set
- relevance model
- web search engines
- web retrieval
- learning to rank
- inverted index
- document representation
- latent semantic indexing
- relevance feedback
- structured queries
- retrieve documents
- spoken document retrieval
- text categorization
- ranking models
- term dependence
- web search
- word pairs
- document clustering
- web documents
- text classification
- ranked list
- information extraction
- probabilistic retrieval models