Sajadmanesh et al., 2019 - Google Patents
Continuous-time relationship prediction in dynamic heterogeneous information networksSajadmanesh et al., 2019
View PDF- Document ID
- 14113588902322880410
- Author
- Sajadmanesh S
- Bazargani S
- Zhang J
- Rabiee H
- Publication year
- Publication venue
- ACM Transactions on Knowledge Discovery from Data (TKDD)
External Links
Snippet
Online social networks, World Wide Web, media, and technological networks, and other types of so-called information networks are ubiquitous nowadays. These information networks are inherently heterogeneous and dynamic. They are heterogeneous as they …
- 238000000605 extraction 0 abstract description 36
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- G06F17/30386—Retrieval requests
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- G06F17/30—Information retrieval; Database structures therefor; File system structures therefor
- G06F17/30861—Retrieval from the Internet, e.g. browsers
- G06F17/30864—Retrieval from the Internet, e.g. browsers by querying, e.g. search engines or meta-search engines, crawling techniques, push systems
- 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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- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
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