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| 001 | 387459 | ||
| 003 | ES-MaUEC | ||
| 005 | 20230401130136.0 | ||
| 006 | a||||fo|||| 00| 0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 230401s2015 sz | s |||| 0|eng d | ||
| 020 | _a9783031022968 | ||
| 024 | 7 |
_a10.1007/978-3-031-02296-8 _2doi |
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| 040 |
_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC |
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| 050 | 4 |
_aTK5105.884 _b2015 EB |
|
| 100 | 1 |
_aManasse, Mark S. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9687957 |
|
| 245 | 1 | 0 |
_aOn the Efficient Determination of Most Near Neighbors : _bHorseshoes, Hand Grenades, Web Search and Other Situations When Close Is Close Enough, Second Edition _cby Mark S. Manasse |
| 250 | _a1st edition 2015 | ||
| 264 | 1 |
_aCham _bSpringer International Publishing _c2015 |
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| 300 | _a1 recurso en línea (XIX, 80 páginas) | ||
| 336 |
_atexto _btxt _2rdacontent |
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| 337 |
_aelectrónico _bc _2rdamedia |
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| 338 |
_arecurso electrónico _bcr _2rdacarrier |
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| 347 |
_aarchivo de texto _bPDF |
||
| 490 | 0 |
_aSynthesis Lectures on Information Concepts Retrieval and Services _x1947-9468 |
|
| 505 | 0 | _aForward -- Foreword to the First Edition -- Acknowledgments -- Introduction -- Comparing Web Pages for Similarity: An Overview -- A Personal History of Web Search -- Uniform Sampling after Alta Vista -- Why Weight (and How)? -- A Few Applications -- Forks in the Road: Flajolet and Slightly Biased Sampling -- Author's Biography. | |
| 520 | _aThe time-worn aphorism "close only counts in horseshoes and hand grenades" is clearly inadequate. Close also counts in golf, shuffleboard, archery, darts, curling, and other games of accuracy in which hitting the precise center of the target isn't to be expected every time, or in which we can expect to be driven from the target by skilled opponents. This book is not devoted to sports discussions, but to efficient algorithms for determining pairs of closely related web pages-and a few other situations in which we have found that inexact matching is good enough - where proximity suffices. We will not, however, attempt to be comprehensive in the investigation of probabilistic algorithms, approximation algorithms, or even techniques for organizing the discovery of nearest neighbors. We are more concerned with finding nearby neighbors; if they are not particularly close by, we are not particularly interested. In thinking of when approximation is sufficient, remember the oft-told joke about two campers sitting around after dinner. They hear noises coming towards them. One of them reaches for a pair of running shoes, and starts to don them. The second then notes that even with running shoes, they cannot hope to outrun a bear, to which the first notes that most likely the bear will be satiated after catching the slower of them. We seek problems in which we don't need to be faster than the bear, just faster than the others fleeing the bear. | ||
| 988 | _aSynthesis Collection of Technology_2015 | ||
| 650 | 7 |
_2embne _9156738 _aBúsqueda en Internet |
|
| 776 | 0 | 8 |
_iPrinted edition: _z9783031011689 |
| 776 | 0 | 8 |
_iPrinted edition: _z9783031034244 |
| 856 | 4 | 0 |
_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02296-8 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid) |
| 942 |
_2lcc _cLE |
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| 998 |
_b04/2023 _dz _eIG _zSI |
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