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<title>PDF Finder - New Way To Search Documents</title>
<copyright>Copyright (c) 2007 pdffinder.com. All rights reserved.</copyright>
<link>http://www.pdffinder.com/</link>
<description>PDF Finder Last Listed Documents</description>
<language>en-us</language>
<lastBuildDate>Mon, 10 Jan 2011 04:17:58 CST</lastBuildDate>
<ttl>5</ttl>
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<title>PDF Finder - New Way To Search Documents</title>
<width>187</width>
<height>55</height>
<link>http://www.pdffinder.com/</link>
<url>http://www.pdffinder.com/images/pdffinder-logo.gif</url>
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<item>
<title>Hibernate, Spring, Eclipse, HSQL Database &amp;amp; Maven Tutorial</title>
<link>http://www.pdffinder.com/pdf/hibernate-spring-eclipse-hsql-database-maven-tutorial.html</link>
<guid isPermaLink="yes">/pdf/hibernate-spring-eclipse-hsql-database-maven-tutorial.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Hibernate is a very popular ORM (Object to Relational Mapping) tool and Spring is a very popular IOC (Inversion Of Control) container with support for AOP, Hibernate etc.</description>
</item>
<item>
<title>Overture Maven Eclipse plugin development Guide</title>
<link>http://www.pdffinder.com/pdf/overture-maven-eclipse-plugin-development-guide.html</link>
<guid isPermaLink="yes">/pdf/overture-maven-eclipse-plugin-development-guide.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>In order to compile the eclipse plug-ins of the Overture Tool the environment has to be setup. This includes Java, Maven, Eclipse and Eclipse test framework. ... The Maven user setting le is located in directory /.m2/ be default it contains user settings for Maven which apply for all projects. The settings le is named &quot;settings.xml&quot; a description of how to use this le in this project is described in section ??.</description>
</item>
<item>
<title>Apache Maven User Guide</title>
<link>http://www.pdffinder.com/pdf/apache-maven-user-guide.html</link>
<guid isPermaLink="yes">/pdf/apache-maven-user-guide.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Maven, a Yiddish word meaning accumulator of knowledge, was originally started as an attempt to simplify the build processes in the Jakarta Turbine project. There were several projects each with their own Ant build files that were all slightly different and JARs were checked into CVS. We wanted a standard way to build the projects, a clear definition of what the project consisted of, an easy way to publish project information and a way to share JARs across several projects. The result is a tool that can now be used for building and managing any Java-based project. We hope that we have created something that will make the day-to-day work of Java developers easier and generally help with the comprehension of any Java-based project.</description>
</item>
<item>
<title>A Probabilistic Deduplication, Record Linkage and Geocoding System</title>
<link>http://www.pdffinder.com/pdf/a-probabilistic-deduplication-record-linkage-and-geocoding-system.html</link>
<guid isPermaLink="yes">/pdf/a-probabilistic-deduplication-record-linkage-and-geocoding-system.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>In many data mining projects in the health sector information from multiple
data sources needs to be cleaned, deduplicated and linked in order to allow
more detailed analysis. The aim of such linkages is to merge all records relating
to the same entity, such as a patient. Most of the time the linkage process
is challenged by the lack of a common unique entity identier. Additionally,
personal information, like names and addresses, are frequently recorded
with typographical errors, can be formatted dierently, and parts can even
be missing or swapped, making the duplication or linkage task non-trivial.
A special case of linkage is geocoding, the process of matching user records
with geocoded reference data, allowing spatial data analysis and mining, for
example of disease outbreaks, or correlations with environmental factors.
In this paper we present an overview of the Febrl (Freely extensible biomedical
record linkage) project, which aims at developing improved algorithms
and techniques for large scale data cleaning and standardisation, record linkage,
deduplication and geocoding.</description>
</item>
<item>
<title>A Probabilistic Geocoding System based on a National Address File</title>
<link>http://www.pdffinder.com/pdf/a-probabilistic-geocoding-system-based-on-a-national-address-file.html</link>
<guid isPermaLink="yes">/pdf/a-probabilistic-geocoding-system-based-on-a-national-address-file.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>It is estimated that between 80% and 90% of governmental
and business data collections contain address information. Geocoding {
the process of assigning geographic coordinates to addresses { is becoming
increasingly important in many application areas that involve the
analysis and mining of such data. In many cases, address records are
captured and/or stored in a free-form or inconsistent manner. This fact
complicates the task of robustly matching such addresses to spatiallyannotated
reference data. In this paper we describe a geocoding system
that is based on a comprehensive high-quality geocoded national address
database. It uses a learning address parser based on hidden Markov models
to separate free-form addresses into components, and a rule-based
matching engine to determine the best set of candidate matches to a
reference le. The geocoding software modules are implemented (as part
of the Febrl open source data linkage system) in the object-oriented language
Python, which allows rapid prototype development and testing.</description>
</item>
<item>
<title>Geoprocessing and Scripting</title>
<link>http://www.pdffinder.com/pdf/geoprocessing-and-scripting.html</link>
<guid isPermaLink="yes">/pdf/geoprocessing-and-scripting.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>This exercise is designed to integrate methods in geoprocessing. The assignment begins with processing some data for the San Diego area using the ModelBuilder, includes some ArcToolBox processing, and ends with execution of iterative functions in a script. You are working with data in San Diego County to support habitat analysis for the California Gnatcatcher (Polioptila californica). The Gnatcatcher is a small non-migratory songbird that resides in this area. Habitat loss has lead to declining populations. The objective of this exercise is to provide an understanding of the range of geoprocessing options available in ArcGIS. Upon completion of the exercise you should be able to differentiate between processing using the ModelBuilder, the ToolBox, and automated processing using a script.</description>
</item>
<item>
<title>The 10 Commandments of Guerrilla Marketing Design</title>
<link>http://www.pdffinder.com/pdf/the-10-commandments-of-guerrilla-marketing-design.html</link>
<guid isPermaLink="yes">/pdf/the-10-commandments-of-guerrilla-marketing-design.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Guerrilla Marketing Design is more an  attitude  than a system of do’s and
don’ts. It’s an attitude that emphasizes the efficient and memorable delivery
of information.
First Commandment: Purposeful - 
Guerrilla Marketers view design not as a matter of subjective likes and dislikes but as a strategic tool intended to achieve specific goals.
Guerrillas avoid unnecessary decoration. Every mark on the page must serve
a purpose. Guerrillas make design decisions based on how efficiently their
designs communicate a desired message to a specific audience.
Guerrilla Marketing design begins with a plan, based on a careful analysis of
message, audience and competition.</description>
</item>
<item>
<title>Guerrilla Marketing in 30 Days</title>
<link>http://www.pdffinder.com/pdf/guerrilla-marketing-in-30-days.html</link>
<guid isPermaLink="yes">/pdf/guerrilla-marketing-in-30-days.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Distilled from the bestselling &quot;marketing&quot; book series in history (with more than 14 million copies 
sold worldwide in 39 languages), Guerrilla Marketing In 30 Days encourages busy business 
professionals and CEO’s to hurdle the excuses of time, money, or motivation, and take dynamic 
strides toward new client acquisition and increased sales by following a 30-day marketing 
blueprint.</description>
</item>
<item>
<title>Open Source and Viral Marketing</title>
<link>http://www.pdffinder.com/pdf/open-source-and-viral-marketing.html</link>
<guid isPermaLink="yes">/pdf/open-source-and-viral-marketing.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Internet marketing has evolved into a major marketing branch for many existing companies. Many new 
enterprises see the effectiveness and advantages of  electronic business by not being limited by time and 
distance when engaging in business activity. The opportunities to do business world wide with the click of 
mouse are enormous and enticing. The skyrocketing success of Hotmail.com has shaken the Internet 
marketing world encouraging entrepreneur to develop marketing concepts and to convince capital venture 
companies to finance them. Despite promising innovative products, many start-ups disappeared as quickly as 
they had appeared. Something fundamentally had gone wrong. 
Viral marketing has been the buzz word for businesses for the last ten years. Customers act as advertisers by 
promoting a product through word of mouse. It is synonymous with word of mouth where a high degree of 
trust is given to a personal recommendation. The communication networks of the customers are used to 
transmit promotional material thereby drastically lowering the costs of customer acquisition.</description>
</item>
<item>
<title>Manfred, A Dramatic Poem</title>
<link>http://www.pdffinder.com/pdf/manfred-a-dramatic-poem.html</link>
<guid isPermaLink="yes">/pdf/manfred-a-dramatic-poem.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Manfred, A Dramatic Poem by Lord Byron is a publication of the Pennsylvania State
University. This Portable Document file is furnished free and without any charge of any
kind. Any person using this document file, for any purpose, and in any way
does so at his or her own risk. Neither the Pennsylvania State University nor Jim
Manis, Faculty Editor, nor anyone associated with the Pennsylvania State University
assumes any responsibility for the material contained within the document or for the
file as an electronic transmission, in any way.
Manfred, A Dramatic Poem by Lord Byron, the Pennsylvania State University, Electronic Classics Series, Jim Manis, Faculty Editor, Hazleton, PA 18201-1291 is a Portable Document File produced as part of an ongoing student publication project to bring
classical works of literature, in English, to free and easy access of those wishing to
make use of them.</description>
</item>
<item>
<title>Writing a Riddle Poem</title>
<link>http://www.pdffinder.com/pdf/writing-a-riddle-poem.html</link>
<guid isPermaLink="yes">/pdf/writing-a-riddle-poem.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>-When writing a riddle poem, begin with the answer. Concrete objects, such as a desk or 
car, are easier to write poems about than abstract ideas such as happiness or peace.  
-Think about how difficult the riddle will be and use that to determine the level of 
specificity you want with your answer. Very specific answers like “Tonya’s white cat” 
are likely to be very hard, even for those who know Tonya’s cat. Specific answers such as 
“blue cheese” aren’t as difficult as very specific ones, but they are still challenging. 
General answers such as “cars” are the easiest type of solution, but that doesn’t mean the 
riddle can’t be hard!</description>
</item>
<item>
<title>Mining Knowledge-Sharing Sites for Viral Marketing</title>
<link>http://www.pdffinder.com/pdf/mining-knowledge-sharing-sites-for-viral-marketing.html</link>
<guid isPermaLink="yes">/pdf/mining-knowledge-sharing-sites-for-viral-marketing.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Viral marketing takes advantage of networks of influence among
customers to inexpensively achieve large changes in behavior.
Our research seeks to put it on a firmer footing by mining these
networks from data, building probabilistic models of them, and
using these models to choose the best viral marketing plan.
Knowledge-sharing sites, where customers review products and
advise each other, are a fertile source for this type of data mining.
In this paper we extend our previous techniques, achieving a large
reduction in computational cost, and apply them to data from a
knowledge-sharing site. We optimize the amount of marketing
funds spent on each customer, rather than just making a binary
decision on whether to market to him. We take into account the
fact that knowledge of the network is partial, and that gathering
that knowledge can itself have a cost. Our results show the robustness and utility of our approach.</description>
</item>
<item>
<title>The New Rules of Viral Marketing</title>
<link>http://www.pdffinder.com/pdf/the-new-rules-of-viral-marketing.html</link>
<guid isPermaLink="yes">/pdf/the-new-rules-of-viral-marketing.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Imagine you’re the head of marketing at a theme park, and you’re charged with
announcing a major new attraction. What would you do? 
Well, the old rules of marketing suggest that you pull out your wallet. You’d probably spend
millions to buy your way into people’s minds, interrupting them with TV spots, billboards 
by the side of the highway, and other “creative” Madison Avenue advertising techniques.
You’d also hire a big PR agency, who would beg the media to write about your attraction. 
The traditional PR approach requires a self-congratulatory press release replete with company
muckety-mucks claiming that the new attraction will bring about world peace by bringing
families closer together. 
That’s not what Cindy Gordon, vice president of new media and marketing partnerships at
Universal Orlando Resort, did when she launched The Wizarding World of Harry Potter.
Other large entertainment companies would have spent millions of dollars to interrupt
everyone in the country with old-rules approaches: Super Bowl TV ads, blimps, direct mail,
and magazine ads. Instead, Gordon told just seven people about the new attraction.</description>
</item>
<item>
<title>Mining Social Networks for Viral Marketing</title>
<link>http://www.pdffinder.com/pdf/mining-social-networks-for-viral-marketing.html</link>
<guid isPermaLink="yes">/pdf/mining-social-networks-for-viral-marketing.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Traditionally, social network models have been descriptive, rather than predictive: they are
built at a very coarse level, typically with only a few global parameters, and are not useful for
making actual predictions of the future behavior of the network. In the past, this was largely due
to lack of data: the networks available for experimental study were small and few, and contained
only minimal information about each node. Fortunately, the rise of the Internet has changed this
dramatically. Massive quantities of data on very large social networks are now available from
blogs, knowledge-sharing sites, collaborative ltering systems, online gaming, social networking
sites, newsgroups, chat rooms, etc. These networks typically number in the tens of thousands to
millions of nodes, and often contain substantial quantities of information at the level of individual
nodes, sucient to build models of those individuals. Assembling these models into models of the
larger network they are part of gives us an unprecedented level of detail in social network analysis,
with the corresponding potential for new understanding, useful predictions, and their productive
use in decision-making.</description>
</item>
<item>
<title>The Dynamics of Viral Marketing</title>
<link>http://www.pdffinder.com/pdf/the-dynamics-of-viral-marketing.html</link>
<guid isPermaLink="yes">/pdf/the-dynamics-of-viral-marketing.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>We present an analysis of a person-to-person recommendation network, consisting of 4 million people who made 16 million recommendations on half a
million products. We observe the propagation of recommendations and the cascade sizes, which we explain by a simple stochastic model. We analyze how user
behavior varies within user communities de&amp;#64257;ned by a recommendation network.
Product purchases follow a ’long tail’ where a signi&amp;#64257;cant share of purchases
belongs to rarely sold items. We establish how the recommendation network
grows over time and how e&amp;#64256;ective it is from the viewpoint of the sender and
receiver of the recommendations. While on average recommendations are not
very e&amp;#64256;ective at inducing purchases and do not spread very far, we present a
model that successfully identi&amp;#64257;es communities, product and pricing categories
for which viral marketing seems to be very e&amp;#64256;ective.</description>
</item>
<item>
<title>Correlation and Simple Linear Regression</title>
<link>http://www.pdffinder.com/pdf/correlation-and-simple-linear-regression.html</link>
<guid isPermaLink="yes">/pdf/correlation-and-simple-linear-regression.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>In this tutorial article, the concepts of correlation and regression are reviewed and
demonstrated. The authors review and compare two correlation coef&amp;#64257;cients, the
Pearson correlation coef&amp;#64257;cient and the Spearman , for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the
linear relationship between a predictor and an outcome variable, simple linear
regression analysis is conducted. These statistical concepts are illustrated by using a
data set from published literature to assess a computed tomography–guided interventional technique. These statistical methods are important for exploring the
relationships between variables and can be applied to many radiologic studies.</description>
</item>
<item>
<title>Applied Correlation and Regression Analysis</title>
<link>http://www.pdffinder.com/pdf/applied-correlation-and-regression-analysis.html</link>
<guid isPermaLink="yes">/pdf/applied-correlation-and-regression-analysis.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>The readings for the course come from a single textbook, a revised and updated edition of a 
classic that can be found among the reference books owned by many social and behavioral 
science researchers.  We will cover all of the material in six of the 16 chapters and much of the 
information in two others.  It is essential that you spend significant time reading in the textbook 
before each class meeting.  Most of the time, reading through the assigned material once will not 
be sufficient.  Read it; read it again; take notes on it; discuss it with fellow class members; 
prepare questions about it to raise in class or lab meeting.  In short, to succeed in this course you 
must commit yourself to significant preparation time for each class meeting.</description>
</item>
<item>
<title>Simple Regression and Correlation</title>
<link>http://www.pdffinder.com/pdf/simple-regression-and-correlation.html</link>
<guid isPermaLink="yes">/pdf/simple-regression-and-correlation.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Today, we are going to discuss a powerful statistical technique for
examining whether or not two variables are related. Specifically, we
are going to talk about the ideas of simple regression and correlation.
One reason why regression is powerful is that we can use it to
demonstrate causality; that is, we can show that an independent
variable causes a change in a dependent variable.</description>
</item>
<item>
<title>OrangeHRM Free Open Source HRM Software: Review</title>
<link>http://www.pdffinder.com/pdf/orangehrm-free-open-source-hrm-software-review.html</link>
<guid isPermaLink="yes">/pdf/orangehrm-free-open-source-hrm-software-review.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>Human Resource Management software are high on demand as companies are
looking for more feasible solutions to streamline their most important assets - the
employees. The HRM software have redefined the ambit of talent management
assisting businesses in time-saving and effective HR management. Having done with
my Top 10 HRM software, I need to add that there are efficient open source HRM
software with upgraded features that are free to download. OrangeHRM one of the
most feasible solutions that I could see.
OrangeHRM is a free and open source human resource management business
solution for the Small and Medium sized Enterprise(SME). This modular HRM system
automates HR processes. It is developed fromPHP, MySQL and Apache HTTP
Server. The software can be used on both Microsoft Windows and Linux operating
system. For more insight I delved into the features of OrangeHRM.
OrangeHRM includes 7modules lets how each of them function.</description>
</item>
<item>
<title>OrangeHRM Tutorial</title>
<link>http://www.pdffinder.com/pdf/orangehrm-tutorial.html</link>
<guid isPermaLink="yes">/pdf/orangehrm-tutorial.html</guid>
<pubDate>Mon, 10 Jan 2011 04:17:58 CST</pubDate>
<description>OrangeHRM is a comprehensive solution for the efficient management and
development of your Human Resources functions. OrangeHRM assists you in
the complex and strategic process of managing this crucial enterprise
function. Based on modular architecture, OrangeHRM enables a vast range of
HR activities, with features that reflect the primary HR management
activities. OrangeHRM is a perfect platform for reengineering your HR
processes and achieving a new level of HR Management.</description>
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