| 000 | 03393cam a2200577 i 4500 | ||
|---|---|---|---|
| 001 | on1152356623 | ||
| 003 | OCoLC | ||
| 005 | 20220711203626.0 | ||
| 006 | m o d | ||
| 007 | cr ||||||||||| | ||
| 008 | 200331t20212021njua ob 001 0 eng | ||
| 010 | _a 2020015367 | ||
| 040 |
_aDLC _beng _erda _cDLC _dOCLCO _dOCLCQ _dOCLCF _dOCLCA _dYDX _dUKMGB _dDG1 _dOCLCO _dN$T _dYDX _dDG1 |
||
| 015 |
_aGBC0D9722 _2bnb |
||
| 016 | 7 |
_a019938838 _2Uk |
|
| 020 |
_a9781119625384 _qelectronic book |
||
| 020 |
_a1119625386 _qelectronic book |
||
| 020 |
_a9781119625377 _qelectronic book |
||
| 020 |
_a1119625378 _qelectronic book |
||
| 020 |
_a9781119625360 _qelectronic book |
||
| 020 |
_a111962536X _qelectronic book |
||
| 020 |
_z9781119625278 _qhardcover |
||
| 029 | 1 |
_aUKMGB _b019938838 |
|
| 035 | _a(OCoLC)1152356623 | ||
| 037 |
_a9781119625377 _bWiley |
||
| 042 | _apcc | ||
| 050 | 0 | 4 |
_aP98 _b.D35 2021 |
| 082 | 0 | 0 |
_a410.1/5195 _223 |
| 049 | _aMAIN | ||
| 100 | 1 |
_aDębowski, Łukasz Jerzy, _d1975- _eauthor. _99413 |
|
| 245 | 1 | 0 |
_aInformation theory meets power laws : _bstochastic processes and language models / _cŁukasz Dębowski, Polish Academy of Sciences. |
| 264 | 1 |
_aHoboken, NJ : _bJohn Wiley & Sons, Inc., _c2021. |
|
| 264 | 4 | _c©2021 | |
| 300 |
_a1 online resource (xvi, 368 pages) : _billustrations |
||
| 336 |
_atext _btxt _2rdacontent |
||
| 337 |
_acomputer _bn _2rdamedia |
||
| 338 |
_aonline resource _bnc _2rdacarrier |
||
| 504 | _aIncludes bibliographical references and index. | ||
| 520 |
_a"This book introduces mathematical foundations of statistical modeling of natural language. The author attempts to explain a few statistical power laws satisfied by texts in natural language in terms of non-Markovian and non-hidden Markovian discrete stochastic processes with some sort of long-range dependence. To achieve this, he uses various concepts and technical tools from information theory and probability measures. This book begins with an introduction. The first half of the book is an introduction to probability measures, information theory, ergodic decomposition, and Kolmogorov complexity, which is provided to make the book relatively self-contained. This section also covers less standard concepts and results, such as excess entropy and generalization of conditional mutual information to fields. The second part of the book discusses the results concerning power laws for mutual information and maximal repetition, such as theorems about facts and words. There is also a separate chapter discussing toy examples of stochastic processes, which should inspire future work in statistical language modeling"-- _cProvided by publisher. |
||
| 588 | _aDescription based on online resource; title from digital title page (viewed on January 27, 2021). | ||
| 590 | _bWiley Frontlist Obook All English 2020 | ||
| 650 | 0 |
_aComputational linguistics. _96146 |
|
| 650 | 0 |
_aStochastic processes. _93246 |
|
| 650 | 7 |
_aComputational linguistics. _2fast _0(OCoLC)fst00871998 _96146 |
|
| 650 | 7 |
_aStochastic processes. _2fast _0(OCoLC)fst01133519 _93246 |
|
| 655 | 4 |
_aElectronic books. _93294 |
|
| 776 | 0 | 8 |
_iPrint version: _aDębowski, Łukasz Jerzy, 1975- _tInformation theory meets power laws _dHoboken : Wiley, 2020. _z9781119625278 _w(DLC) 2020015366 |
| 856 | 4 | 0 |
_uhttps://doi.org/10.1002/9781119625384 _zWiley Online Library |
| 942 | _cEBK | ||
| 994 |
_a92 _bDG1 |
||
| 999 |
_c69388 _d69388 |
||