e Freitas et al., 2019 - Google Patents
Parallel rule‐based selective sampling and on‐demand learning to ranke Freitas et al., 2019
- Document ID
- 12219029701930080084
- Author
- e Freitas M
- Sousa D
- Martins W
- Rosa T
- Silva R
- Gonçalves M
- Publication year
- Publication venue
- Concurrency and Computation: Practice and Experience
External Links
Snippet
Learning to rank (L2R) works by constructing a ranking model from training data so that, given a new query, the model is able to generate an effective rank of the objects for the query. Almost all work in L2R focus on ranking accuracy leaving performance and scalability …
- 238000005070 sampling 0 title abstract description 17
Classifications
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- G06F17/30286—Information retrieval; Database structures therefor; File system structures therefor in structured data stores
- G06F17/30386—Retrieval requests
- G06F17/30424—Query processing
- G06F17/30533—Other types of queries
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- G06F17/30867—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems with filtering and personalisation
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