| 000 | 03931nam a22005655i 4500 | ||
|---|---|---|---|
| 001 | 978-3-031-37291-9 | ||
| 003 | DE-He213 | ||
| 005 | 20251030110810.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 230804s2024 sz | s |||| 0|eng d | ||
| 020 |
_a9783031372919 _9978-3-031-37291-9 |
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| 024 | 7 |
_a10.1007/978-3-031-37291-9 _2doi |
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| 050 | 4 | _aQA75.5-76.95 | |
| 072 | 7 |
_aUNH _2bicssc |
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| 072 | 7 |
_aUND _2bicssc |
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_aCOM030000 _2bisacsh |
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| 072 | 7 |
_aUNH _2thema |
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| 072 | 7 |
_aUND _2thema |
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| 100 | 1 |
_aZhu, Lei. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _965567 |
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| 245 | 1 | 0 |
_aMulti-modal Hash Learning _h[electronic resource] : _bEfficient Multimedia Retrieval and Recommendations / _cby Lei Zhu, Jingjing Li, Weili Guan. |
| 250 | _a1st ed. 2024. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2024. |
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| 300 |
_aXXII, 199 p. 51 illus., 50 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aSynthesis Lectures on Information Concepts, Retrieval, and Services, _x1947-9468 |
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| 505 | 0 | _a1 Introduction -- 2 Context-aware Hashing -- 3 Cross-modal Hashing -- 4 Composite Multi-modal Hashing -- 5 Multi-modal Discrete Collaborative Filtering -- 6 Research Frontiers. . | |
| 520 | _aThis book systemically presents key concepts of multi-modal hashing technology, recent advances on large-scale efficient multimedia search and recommendation, and recent achievements in multimedia indexing technology. With the explosive growth of multimedia contents, multimedia retrieval is currently facing unprecedented challenges in both storage cost and retrieval speed. The multi-modal hashing technique can project high-dimensional data into compact binary hash codes. With it, the most time-consuming semantic similarity computation during the multimedia retrieval process can be significantly accelerated with fast Hamming distance computation, and meanwhile the storage cost can be reduced greatly by the binary embedding. The authors introduce the categorization of existing multi-modal hashing methods according to various metrics and datasets. The authors also collect recent multi-modal hashing techniques and describe the motivation, objective formulations, and optimization steps for context-aware hashing methods based on the tag-semantics transfer. Reveals the key concepts and recent advancements of multi-modal hashing and multimedia indexing technology Introduces standard multimedia retrieval datasets, evaluation metrics for multi-modal hashing, and the unprecedented challenges of both storage cost and retrieval speed Discusses how the multi-modal hashing technique can project high-dimensional data into compact binary hash codes. | ||
| 650 | 0 |
_aInformation storage and retrieval systems. _965568 |
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| 650 | 0 |
_aData mining. _96941 |
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| 650 | 0 |
_aMultimedia systems. _965569 |
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| 650 | 1 | 4 |
_aInformation Storage and Retrieval. _965570 |
| 650 | 2 | 4 |
_aData Mining and Knowledge Discovery. _965571 |
| 650 | 2 | 4 |
_aMultimedia Information Systems. _965572 |
| 700 | 1 |
_aLi, Jingjing. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _965573 |
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| 700 | 1 |
_aGuan, Weili. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _965574 |
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| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer Nature eBook | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031372902 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031372926 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031372933 |
| 830 | 0 |
_aSynthesis Lectures on Information Concepts, Retrieval, and Services, _x1947-9468 _965575 |
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| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-37291-9 |
| 912 | _aZDB-2-SXSC | ||
| 999 |
_c56228 _d56228 |
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