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• catalog abstract "The collation of large electronic databases of scienti?c and commercial infor- tion has led to a dramatic growth of interest in methods for discovering struc- res in such databases. These methods often go under the general name of data mining. One important subdiscipline within data mining is concerned with the identi?cation and detection of anomalous, interesting, unusual, or valuable - cords or groups of records, which we call patterns. Familiar examples are the detection of fraud in credit-card transactions, of particular coincident purchases in supermarket transactions, of important nucleotide sequences in gene sequence analysis, and of characteristic traces in EEG records. Tools for the detection of such patterns have been developed within the data mining community, but also within other research communities, typically without an awareness that the - sic problem was common to many disciplines. This is not unreasonable: each of these disciplines has a large literature of its own, and a literature which is growing rapidly. Keeping up with any one of these is di?cult enough, let alone keeping up with others as well, which may in any case be couched in an - familiar technical language. But, of course, this means that opportunities are being lost, discoveries relating to the common problem made in one area are not transferred to the other area, and breakthroughs and problem solutions are being rediscovered, or not discovered for a long time, meaning that e?ort is being wasted and opportunities may be lost.".
• catalog contributor b12632604.
• catalog contributor b12632605.
• catalog contributor b12632606.
• catalog contributor b12632607.
• catalog contributor b12632608.
• catalog created "2002.".
• catalog date "2002".
• catalog date "2002.".
• catalog dateCopyrighted "2002.".
• catalog description "Includes bibliographical references and index.".
• catalog description "Pattern detection and discovery / David J. Hand -- Detecting interesting instances / Katharina Morik -- Complex data: mining using patterns / Arno Siebes and Zbyszek Struzik -- Determining hit rate in pattern search / Richard J. Bolton, David J. Hand, and Niall M. Adams -- An unsupervised algorithm for segmenting categorical timeseries into episodes / Paul Cohen, Brent Heeringa, and Niall M. Adams -- If you can't see the pattern, is it there? / Antony Unwin -- Dataset filtering techniques in constraint-based frequent pattern mining / Marek Wojciechowski and Maciej Zakrzewicz -- Concise representations of association rules / Marzena Kryszkiewicz -- Constraint-based discovery and inductive queries / Baptiste Jeudy and Jean-Franȯis Boulicaut -- Relational association rules: getting WARMeR / Bart Goethals and Jan Van den Bussche -- Mining text data: special features and patterns / M. Delgado [and others] -- Modelling and incorporating background knowledge in the web mining process / Myra Spiliopoulou and Carsten Pohle -- Modeling information in textual data combining labeled and unlabeled data / Dunja Mladenic -- Discovery of frequent word sequences in text / Helena Ahonen-Myka -- Pattern detection and discovery / Pierre-Yves Rolland and Jean-Gabriel Ganascia -- Discovery of core episodes from sequences / Frank Hoppner -- Patterns of dependencies in dynamic multivariate data / Ursula Gather [and others].".
• catalog description "The collation of large electronic databases of scienti?c and commercial infor- tion has led to a dramatic growth of interest in methods for discovering struc- res in such databases. These methods often go under the general name of data mining. One important subdiscipline within data mining is concerned with the identi?cation and detection of anomalous, interesting, unusual, or valuable - cords or groups of records, which we call patterns. Familiar examples are the detection of fraud in credit-card transactions, of particular coincident purchases in supermarket transactions, of important nucleotide sequences in gene sequence analysis, and of characteristic traces in EEG records. Tools for the detection of such patterns have been developed within the data mining community, but also within other research communities, typically without an awareness that the - sic problem was common to many disciplines. This is not unreasonable: each of these disciplines has a large literature of its own, and a literature which is growing rapidly. Keeping up with any one of these is di?cult enough, let alone keeping up with others as well, which may in any case be couched in an - familiar technical language. But, of course, this means that opportunities are being lost, discoveries relating to the common problem made in one area are not transferred to the other area, and breakthroughs and problem solutions are being rediscovered, or not discovered for a long time, meaning that e?ort is being wasted and opportunities may be lost.".
• catalog extent "xii, 226 p. :".
• catalog identifier "3540441484 (softcover : alk. paper)".
• catalog isPartOf "Lecture notes in computer science ; 2447. Lecture notes in artificial intelligence".
• catalog isPartOf "Lecture notes in computer science ; 2447.".
• catalog isPartOf "Lecture notes in computer science. Lecture notes in artificial intelligence.".
• catalog issued "2002".
• catalog issued "2002.".
• catalog language "eng".
• catalog publisher "Berlin ; New York : Springer,".
• catalog subject "006.4 21".
• catalog subject "Artificial intelligence.".
• catalog subject "Computer files.".
• catalog subject "Computer science.".
• catalog subject "Computer software.".
• catalog subject "Data mining Congresses.".
• catalog subject "Database management.".
• catalog subject "Information storage and retrieval systems.".
• catalog subject "Pattern recognition systems Congresses.".
• catalog subject "QA76.9.D343 E84 2002".
• catalog tableOfContents "Pattern detection and discovery / David J. Hand -- Detecting interesting instances / Katharina Morik -- Complex data: mining using patterns / Arno Siebes and Zbyszek Struzik -- Determining hit rate in pattern search / Richard J. Bolton, David J. Hand, and Niall M. Adams -- An unsupervised algorithm for segmenting categorical timeseries into episodes / Paul Cohen, Brent Heeringa, and Niall M. Adams -- If you can't see the pattern, is it there? / Antony Unwin -- Dataset filtering techniques in constraint-based frequent pattern mining / Marek Wojciechowski and Maciej Zakrzewicz -- Concise representations of association rules / Marzena Kryszkiewicz -- Constraint-based discovery and inductive queries / Baptiste Jeudy and Jean-Franȯis Boulicaut -- Relational association rules: getting WARMeR / Bart Goethals and Jan Van den Bussche -- Mining text data: special features and patterns / M. Delgado [and others] -- Modelling and incorporating background knowledge in the web mining process / Myra Spiliopoulou and Carsten Pohle -- Modeling information in textual data combining labeled and unlabeled data / Dunja Mladenic -- Discovery of frequent word sequences in text / Helena Ahonen-Myka -- Pattern detection and discovery / Pierre-Yves Rolland and Jean-Gabriel Ganascia -- Discovery of core episodes from sequences / Frank Hoppner -- Patterns of dependencies in dynamic multivariate data / Ursula Gather [and others].".
• catalog title "Pattern detection and discovery : ESF Exploratory Workshop, London, UK, September 16-19, 2002 : proceedings / David J. Hand, Niall M. Adams, Richard J. Bolton (eds.).".
• catalog type "Conference proceedings. fast".
• catalog type "text".