000 03284nam a22005775i 4500
001 978-0-387-24247-7
003 DE-He213
005 20161121230515.0
007 cr nn 008mamaa
008 100301s2005 xxu| s |||| 0|eng d
020 _a9780387242477
_9978-0-387-24247-7
024 7 _a10.1007/b104937
_2doi
050 4 _aQA76.9.D343
072 7 _aUNF
_2bicssc
072 7 _aUYQE
_2bicssc
072 7 _aCOM021030
_2bisacsh
082 0 4 _a006.312
_223
100 1 _aWang, Wei.
_eauthor.
245 1 0 _aMining Sequential Patterns from Large Data Sets
_h[electronic resource] /
_cby Wei Wang, Jiong Yang.
264 1 _aBoston, MA :
_bSpringer US,
_c2005.
300 _aXV, 163 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Database Systems,
_x1386-2944 ;
_v28
505 0 _aRelated Work -- Periodic Patterns -- Statistically Significant Patterns -- Approximate Patterns -- Conclusion Remark.
520 _aThe focus of Mining Sequential Patterns from Large Data Sets is on sequential pattern mining. In many applications, such as bioinformatics, web access traces, system utilization logs, etc., the data is naturally in the form of sequences. This information has been of great interest for analyzing the sequential data to find its inherent characteristics. Examples of sequential patterns include but are not limited to protein sequence motifs and web page navigation traces. To meet the different needs of various applications, several models of sequential patterns have been proposed. This volume not only studies the mathematical definitions and application domains of these models, but also the algorithms on how to effectively and efficiently find these patterns. Mining Sequential Patterns from Large Data Sets provides a set of tools for analyzing and understanding the nature of various sequences by identifying the specific model(s) of sequential patterns that are most suitable. This book provides an efficient algorithm for mining these patterns. Mining Sequential Patterns from Large Data Sets is designed for a professional audience of researchers and practitioners in industry and also suitable for graduate-level students in computer science. .
650 0 _aComputer science.
650 0 _aComputer communication systems.
650 0 _aData structures (Computer science).
650 0 _aDatabase management.
650 0 _aData mining.
650 0 _aInformation storage and retrieval.
650 0 _aMultimedia information systems.
650 1 4 _aComputer Science.
650 2 4 _aData Mining and Knowledge Discovery.
650 2 4 _aDatabase Management.
650 2 4 _aInformation Storage and Retrieval.
650 2 4 _aData Structures.
650 2 4 _aMultimedia Information Systems.
650 2 4 _aComputer Communication Networks.
700 1 _aYang, Jiong.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387242460
830 0 _aAdvances in Database Systems,
_x1386-2944 ;
_v28
856 4 0 _uhttp://dx.doi.org/10.1007/b104937
912 _aZDB-2-SCS
950 _aComputer Science (Springer-11645)
999 _c499798
_d499798