| 000 | 05373cam a2200337 i 4500 | ||
|---|---|---|---|
| 999 |
_c382182 _d382182 |
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| 001 | 18593251 | ||
| 003 | APU | ||
| 005 | 20190219065546.0 | ||
| 008 | 190212s2015 enka 001 0 eng | ||
| 010 | _a 2015016005 | ||
| 020 | _a9780749474010 (pbk.) | ||
| 040 |
_aDLC _beng _cDLC _dWAN |
||
| 042 | _apcc | ||
| 050 | 0 | 0 |
_aHF5415.125 _b.S77 2015 |
| 082 | 0 | 0 |
_a658.4/72 _223 |
| 100 | 1 |
_aStruhl, Steven M. _941837 |
|
| 245 | 1 | 0 |
_aPractical text analytics : _binterpreting text and unstructured data for business intelligence / _cSteven Struhl. |
| 260 |
_aLondon ; _aPhiladelphia : _bKogan Page, _c2015. |
||
| 300 |
_axiii, 257 p. : _bill. ; _c23 cm. |
||
| 490 | 0 | _aMarketing science | |
| 500 | _aIncludes index. | ||
| 505 | 8 | _aMachine generated contents note: Preface01 Who should read this book? -- Who should read this book -- Where we find text -- Sense and sensibility in thinking about text -- A few places we will not be going -- Where we will be going from here -- Summary -- References02 Getting ready: capturing, sorting, sifting, stemming and matching -- What we need to do with text -- Ways of corralling words -- Summary -- References03 In pictures: word clouds, wordles and beyond -- Getting words into a picture -- The many types of pictures and their uses -- Clustering words -- Applications, uses and cautions -- Summary -- References04 Putting text together: clustering documents using words -- Where we have been and moving on to documents -- Clustering and classifying documents -- Clustering documents -- Document classification -- Summary -- References05 In the mood for sentiment (and counting) -- Basics of sentiment and counting -- Counting words -- Understanding sentiment -- Summary -- References06 Predictive models 1: having words with regressions -- Understanding predictive models -- Starting from the basics with regression -- Rules of the road for regression -- Divergent roads: regression aims and regression uses -- Practical examples -- Summary -- References07 Predictive models 2: classifications that grow on trees -- Classification trees: understanding an amazing analytical method -- Seeing how trees work, step by step -- CHAID and CART (and CRT, C&RT, QUEST, J48 and others) -- Summary: applications and cautions -- References08 Predictive models 3: all in the family with Bayes Nets -- What are Bayes Nets and how do they compare with other methods? -- Our first example: Bayes Nets linking survey questions and behaviour -- Using a Bayes Net with text -- Bayes Net software: welcome to the thicket -- Summary, conclusions and cautions -- References09 Looking forward and back -- Where we may be going -- What role does text analytics play? -- Summing up: where we have been -- Software and you -- In conclusion -- References Glossary -- Index . | |
| 520 | _a"Bridging the gap between the marketer who must put text analytics to use and data analysis experts, Practical Text Analytics is an accessible guide to the many advances in text analytics. It explains the different approaches and methods, their uses, strengths, and weaknesses, in a way that is relevant to marketing professionals. Each chapter includes illustrations and charts, hints and tips, pointers on the tools and techniques, definitions, and case studies/examples. Consultant and researcher Steven Struhl presents the process of text analysis in ways that will help marketers clarify and organize the confusing array of methods, frame the right questions, and apply the results successfully to find meaning in any unstructured data and develop effective new marketing strategies"-- | ||
| 520 | _a"Bridging the gap between the marketer who must put text analytics to use and the increasingly rarefied community of data analysis experts, Practical Text Analytics is an accessible guide to the many remarkable advances in text analytics that specialists are discussing among themselves. Instead of being a resource for programmers, a book on theory or an introduction on how to use advanced statistical programs, this daily reference resource cuts through the profusion of jargon, evaluating the strengths and weaknesses of various methods and serving as a guide to what is credible in this fast-moving and often confusing field. Practical Text Analytics provides guidance on the application of text analytics for marketing professionals who must interpret the results and apply them in their campaigns. It presents the process of analysis in ways that people who use the data need to see them, helping marketers to clarify and organize confidently the confusing array of methods, frame the right questions and apply the results successfully to find meaning in any unstructured data and develop powerful new marketing strategies. About the series: The Marketing Science series makes difficult topics accessible to marketing students and practitioners by grounding them in business reality. Each book is written by an expert in the field and includes case studies and illustrations so marketers can gain confidence in applying the tools and techniques and commission external research"-- | ||
| 650 | 0 |
_aMarketing _xData processing. _941838 |
|
| 650 | 0 |
_aBig data. _941839 |
|
| 650 | 0 |
_aBusiness intelligence. _941840 |
|
| 650 | 0 |
_aMarketing research. _941841 |
|
| 906 |
_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg |
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| 942 |
_2lcc _cBook |
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