Time Granularities in Databases, Data Mining, and Temporal ReasoningSpringer Science & Business Media, 13 июл. 2000 г. - Всего страниц: 230 Calendar units, such as months and days, clock units, such as hours and seconds, and specialized units, such as business days and academic years, play a major role in a wide range of information system applications. System support for reasoning about these units, called granularities in this book, is important for the efficient design, use, and implementation of such applications. The book deals with several aspects of temporal information and provides a unifying model for granularities. It is intended for computer scientists and engineers who are interested in the formal models and technical development of specific issues. Practitioners can learn about critical aspects that must be taken into account when designing and implementing databases supporting temporal information. Lecturers may find this book useful for an advanced course on databases. Moreover, any graduate student working on time representation and reasoning, either in data or knowledge bases, should definitely read it. |
Содержание
II | 3 |
III | 7 |
IV | 8 |
V | 10 |
VI | 11 |
VIII | 12 |
IX | 13 |
X | 17 |
LI | 99 |
LII | 101 |
LIII | 104 |
LIV | 106 |
LV | 110 |
LVI | 112 |
LVII | 117 |
LIX | 120 |
XI | 19 |
XIII | 23 |
XIV | 24 |
XV | 27 |
XVI | 31 |
XVII | 32 |
XVIII | 33 |
XIX | 34 |
XX | 35 |
XXI | 37 |
XXIII | 39 |
XXIV | 42 |
XXV | 47 |
XXVII | 48 |
XXVIII | 50 |
XXIX | 52 |
XXX | 56 |
XXXI | 57 |
XXXII | 63 |
XXXIII | 64 |
XXXIV | 68 |
XXXV | 69 |
XXXVI | 70 |
XXXVII | 73 |
XXXVIII | 77 |
XXXIX | 78 |
XL | 83 |
XLII | 87 |
XLIV | 89 |
XLVI | 90 |
XLVII | 92 |
XLVIII | 94 |
XLIX | 98 |
LX | 123 |
LXI | 124 |
LXII | 125 |
LXIII | 134 |
LXIV | 135 |
LXV | 136 |
LXVI | 141 |
LXVII | 143 |
LXVIII | 146 |
LXIX | 148 |
LXX | 149 |
LXXI | 153 |
LXXIII | 155 |
LXXIV | 156 |
LXXV | 157 |
LXXVI | 158 |
LXXVIII | 159 |
LXXIX | 160 |
LXXX | 162 |
LXXXI | 163 |
LXXXIV | 164 |
LXXXV | 166 |
LXXXVI | 167 |
LXXXVII | 172 |
LXXXIX | 177 |
XC | 185 |
XCII | 188 |
XCIII | 202 |
XCIV | 207 |
XCV | 219 |
223 | |
229 | |
Другие издания - Просмотреть все
Time Granularities in Databases, Data Mining, and Temporal Reasoning Claudio Bettini,Sushil Jajodia,Sean Wang Ограниченный просмотр - 2013 |
Time Granularities in Databases, Data Mining, and Temporal Reasoning Claudio Bettini,Sushil Jajodia,Sean Wang Недоступно для просмотра - 2010 |
Time Granularities in Databases, Data Mining, and Temporal Reasoning Claudio Bettini,Sushil Jajodia,Sean Wang Недоступно для просмотра - 2014 |
Часто встречающиеся слова и выражения
applied Armstrong's axioms assume attributes b-day bottom granularity candidate event types candidate key Chap complex event type compute consider constraint network conversion method corresponding data mining data redundancy defined definition denote derived different granularities domain easily seen event sequence event structure example exists finite set formally formula G₁ G₂ given glb(F granularity G granularity system granule of G H₁ Hence inference axioms input instants integer intersection interval-based assumptions intervals Intuitively logically implied lossless decomposition M₁ MaxSub(G(k minimal closure month MQLF multiple granularities notion obtained operation path-consistency algorithm periodical sets point-based assumptions positive integers Proof Proposition redundancy relationship representation respect restriction result satisfies semantic assumptions set of TFDs solution specific Step subset superkey t₁ T3NF TBCNF decomposition TCGs temporal databases temporal module schema temporal relation Theorem timestamp TSQL2 tuples upper bound user queries values variables week windowing function
Ссылки на эту книгу
Filtering the Web to Feed Data Warehouses Witold Abramowicz,Pawel J. Kalczynski,Krzysztof Węcel Ограниченный просмотр - 2002 |
Theoretical Computer Science: 8th Italian Conference, ICTCS 2003 ..., Том 8 Carlo Blundo,Cosimo Laneve Недоступно для просмотра - 2003 |