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Complete real-world examples of gathering feedback from users and
web environments; Fundamentals of text analysis using JavaScript
and PHP; Harnessing JavaScript data visualisation tools; Business
focused application to feedback gathering, analysis and reporting;
Integration of new and existing data sources into a single bespoke
web-based analysis environment
Text Mining and Visualization: Case Studies Using Open-Source Tools
provides an introduction to text mining using some of the most
popular and powerful open-source tools: KNIME, RapidMiner, Weka, R,
and Python. The contributors-all highly experienced with text
mining and open-source software-explain how text data are gathered
and processed from a wide variety of sources, including books,
server access logs, websites, social media sites, and message
boards. Each chapter presents a case study that you can follow as
part of a step-by-step, reproducible example. You can also easily
apply and extend the techniques to other problems. All the examples
are available on a supplementary website. The book shows you how to
exploit your text data, offering successful application examples
and blueprints for you to tackle your text mining tasks and benefit
from open and freely available tools. It gets you up to date on the
latest and most powerful tools, the data mining process, and
specific text mining activities.
Powerful, Flexible Tools for a Data-Driven WorldAs the data deluge
continues in today's world, the need to master data mining,
predictive analytics, and business analytics has never been
greater. These techniques and tools provide unprecedented insights
into data, enabling better decision making and forecasting, and
ultimately the solution of increasingly complex problems. Learn
from the Creators of the RapidMiner Software Written by leaders in
the data mining community, including the developers of the
RapidMiner software, RapidMiner: Data Mining Use Cases and Business
Analytics Applications provides an in-depth introduction to the
application of data mining and business analytics techniques and
tools in scientific research, medicine, industry, commerce, and
diverse other sectors. It presents the most powerful and flexible
open source software solutions: RapidMiner and RapidAnalytics. The
software and their extensions can be freely downloaded at
www.RapidMiner.com. Understand Each Stage of the Data Mining
ProcessThe book and software tools cover all relevant steps of the
data mining process, from data loading, transformation,
integration, aggregation, and visualization to automated feature
selection, automated parameter and process optimization, and
integration with other tools, such as R packages or your IT
infrastructure via web services. The book and software also
extensively discuss the analysis of unstructured data, including
text and image mining. Easily Implement Analytics Approaches Using
RapidMiner and RapidAnalytics Each chapter describes an
application, how to approach it with data mining methods, and how
to implement it with RapidMiner and RapidAnalytics. These
application-oriented chapters give you not only the necessary
analytics to solve problems and tasks, but also reproducible,
step-by-step descriptions of using RapidMiner and RapidAnalytics.
The case studies serve as blueprints for your own data mining
applications, enabling you to effectively solve similar problems.
Complete real-world examples of gathering feedback from users and
web environments; Fundamentals of text analysis using JavaScript
and PHP; Harnessing JavaScript data visualisation tools; Business
focused application to feedback gathering, analysis and reporting;
Integration of new and existing data sources into a single bespoke
web-based analysis environment
This book constitutes the refereed proceedings of the Third International COST264 Workshop on Networked Group Communication, NGC 2001, held in London, UK, in November 2001.The 14 revised full papers presented were carefully reviewed and selected from 40 submissions. All current issues in the area are addressed. The papers are organized in topical sections on application-level aspects, group management, performance topics, security, and topology.
Text Mining and Visualization: Case Studies Using Open-Source Tools
provides an introduction to text mining using some of the most
popular and powerful open-source tools: KNIME, RapidMiner, Weka, R,
and Python. The contributors-all highly experienced with text
mining and open-source software-explain how text data are gathered
and processed from a wide variety of sources, including books,
server access logs, websites, social media sites, and message
boards. Each chapter presents a case study that you can follow as
part of a step-by-step, reproducible example. You can also easily
apply and extend the techniques to other problems. All the examples
are available on a supplementary website. The book shows you how to
exploit your text data, offering successful application examples
and blueprints for you to tackle your text mining tasks and benefit
from open and freely available tools. It gets you up to date on the
latest and most powerful tools, the data mining process, and
specific text mining activities.
As the Internet has grown, so have the challenges associated with
delivering static, streaming, and dynamic content to end-users.
This book is unique in that it addresses the topic of content
networking exclusively and comprehensively, tracing the evolution
from traditional web caching to today's open and vastly more
flexible architecture. With this evolutionary approach, the authors
emphasize the field's most persistent concepts, principles, and
mechanisms--the core information that will help you understand why
and how content delivery works today, and apply that knowledge in
the future.
+ Focuses on the principles that will give you a deep and timely
understanding of content networking.
+ Offers dozens of protocol-specific examples showing how real-life
Content Networks are currently designed and implemented.
+ Provides extensive consideration of Content Services, including
both the Internet Content Adaptation Protocol (ICAP) and Open
Pluggable Edge Services (OPES).
+ Examines methods for supporting time-constrained media such as
streaming audio and video and real-time media such as instant
messages.
+ Combines the vision and rigor of a prominent researcher with the
practical experience of a seasoned development engineer to provide
a unique combination of theoretical depth and practical
application.
Immer mehr Unternehmen entdecken die Bedeutung von
Customer-Relationship-Management (CRM). Hofmann legt das erste Buch
vor, das CRM mit dem gleichfalls immer bedeutender werdenden Aspekt
der wertsteigernden Unternehmensfuhrung zum
Customer-Lifetime-Value-Management (CLV-M) verknupft.
"
Diplomarbeit aus dem Jahr 2004 im Fachbereich BWL - Marketing,
Unternehmenskommunikation, CRM, Marktforschung, Social Media, Note:
1,7, Hochschule fur Angewandte Wissenschaften Hamburg, Sprache:
Deutsch, Abstract: Schwerpunkte der Arbeit sind: B2B,
Investitionsguter, Investitionsgutermarketing, Definition von
Innovation und Innovationsgrade, Unternehmen im technologischen
Wandel, Kauferverhalten, Adoption und Diffusion bei
B2B-Innovationen, Innovationsstrategien und Innovationserfolg,
Innovationswiderstande und deren Uberwindung, Innovationsmarketing,
Markenpolitik fur Innovationen Eine Idee und harte Arbeit sind die
Grundlagen fur eine erfolgreiche Innovation, sie alleine sichern
allerdings nicht den Innovationserfolg. Auch Misserfolge und
Ruckschlage gehoren zum nnovationsprozess(vgl. Cooper, 2003, S.
166ff.). Deswegen ist ein wesentliches Ziel dieser Arbeit die
Darstellung einer erfolgreichen Vermarktung von B2B-Innovationen.
Um dies zu erreichen, muss zuerst die Frage nach einer Innovation
im betriebswirtschaftlichen Sinne geklart werden, und welche Formen
von Innovationen es gibt. Ausserdem soll gezeigt werden, wie eine
sinnvolle Abgrenzung zwischen den technologischen Sprungen von
Entwicklungen gemacht, und woran diese erkannt werden konnen. Neben
der Frage, welche Erfolgsgrossen es fur Unternehmen in Bezug auf
Innovationen gibt und durch welche Instrumente ein Unternehmen
uberhaupt einen Innovationsbedarf erkennen kann, sollen Fragen nach
den Turbulenzen bzw. Gefahren eines innovierenden Unternehmens und
eines potenziellen Abnehmers dieser Innovationen in der Branche
beantwortetet werden.Ein elementarer Teil dieser Arbeit wird sich
mit dem industriellen Beschaffungsverhalten und dessen
Beeinflussbarkeit in Bezug auf Innovationen beschaftigen, aber
ebenso mit der Annahme und Verbreitung sowie evtl. Widerstanden
gegenuber von Innovationen und deren Auflosung.Im weiteren Verlauf
der Arbeit ist dann der Frage nachzugehen, welche Strategien
innovierende Unterneh
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