소장자료
LDR | 02762cam a2200373 a 4500 | ||
001 | 0093776137▲ | ||
005 | 20180519090937▲ | ||
008 | 140909s2015 caua b 001 0 eng c▲ | ||
010 | ▼a2014035276▲ | ||
020 | ▼a9780520280977 (cloth : alk. paper)▲ | ||
020 | ▼a0520280970 (cloth : alk. paper)▲ | ||
020 | ▼a9780520280984 (pbk. : alk. paper)▲ | ||
020 | ▼a0520280989 (pbk. : alk. paper)▲ | ||
020 | ▼z9780520960596 (ebk.)▲ | ||
020 | ▼z0520960599 (ebk.)▲ | ||
035 | ▼a(KERIS)REF000017588471▲ | ||
040 | ▼aCU-S/DLC▼beng▼cCU-S▼d221016▲ | ||
042 | ▼apcc▲ | ||
050 | 0 | 0 | ▼aH61.3▼bA88 2015▲ |
082 | 0 | 0 | ▼a006.3/12▼223▲ |
090 | ▼a006.312▼bA884d▲ | ||
100 | 1 | ▼aAttewell, Paul A.,▼d1949-▲ | |
245 | 1 | 0 | ▼aData mining for the social sciences :▼ban introduction /▼cPaul Attewell and David B. Monaghan with Darren Kwong.▲ |
250 | ▼a1st ed.▲ | ||
260 | ▼aOakland :▼bUniversity of California Press,▼c2015.▲ | ||
300 | ▼axi, 252 p. :▼bill. ;▼c26 cm.▲ | ||
504 | ▼aIncludes bibliographical references (p. 239-244) and index.▲ | ||
520 | ▼a"We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher.▲ | ||
650 | 0 | ▼aSocial sciences▼xData processing.▲ | |
650 | 0 | ▼aSocial sciences▼xStatistical methods.▲ | |
650 | 0 | ▼aData mining.▲ | |
700 | 1 | ▼aMonaghan, David B.,▼d1988-▲ | |
700 | 1 | ▼aDarren, Kwong.▲ | |
999 | ▼a정재훈▼c김미선▲ |
Data mining for the social sciences :an introduction
자료유형
국외단행본
서명/책임사항
Data mining for the social sciences : an introduction / Paul Attewell and David B. Monaghan with Darren Kwong.
판사항
1st ed.
발행사항
Oakland : University of California Press , 2015.
형태사항
xi, 252 p. : ill. ; 26 cm.
서지주기
Includes bibliographical references (p. 239-244) and index.
요약주기
"We live, today, in world of big data. The amount of information collected on human behavior every day is staggering, and exponentially greater than at any time in the past. At the same time, we are inundated by stories of powerful algorithms capable of churning through this sea of data and uncovering patterns. These techniques go by many names - data mining, predictive analytics, machine learning - and they are being used by governments as they spy on citizens and by huge corporations are they fine-tune their advertising strategies. And yet social scientists continue mainly to employ a set of analytical tools developed in an earlier era when data was sparse and difficult to come by. In this timely book, Paul Attewell and David Monaghan provide a simple and accessible introduction to Data Mining geared towards social scientists. They discuss how the data mining approach differs substantially, and in some ways radically, from that of conventional statistical modeling familiar to most social scientists. They demystify data mining, describing the diverse set of techniques that the term covers and discussing the strengths and weaknesses of the various approaches. Finally they give practical demonstrations of how to carry out analyses using data mining tools in a number of statistical software packages. It is the hope of the authors that this book will empower social scientists to consider incorporating data mining methodologies in their analytical toolkits"--Provided by publisher.
ISBN
9780520280977 (cloth : alk. paper) 0520280970 (cloth : alk. paper) 9780520280984 (pbk. : alk. paper) 0520280989 (pbk. : alk. paper)
청구기호
006.312 A884d
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