Book Image

Angular Services

By : Sohail Salehi
Book Image

Angular Services

By: Sohail Salehi

Overview of this book

A primary concern with modern day applications is that they need to be dynamic, and for that, data access from the server side, data authentication, and security are very important. Angular leverages its services to create such state-of-the-art dynamic applications. This book will help you create and design customized services, integrate them into your applications, import third-party plugins, and make your apps perform better and faster. This book starts with a basic rundown on how you can create your own Angular development environment compatible with v2 and v4. You will then use Bootstrap and Angular UI components to create pages. You will also understand how to use controllers to collect data and populate them into NG UIs. Later, you will then create a rating service to evaluate entries and assign a score to them. Next, you will create "cron jobs" in NG. We will then create a crawler service to find all relevant resources regarding a selected headline and generate reports on it. Finally, you will create a service to manage accuracy and provide feedback about troubled areas in the app created. This book is up to date for the 2.4 release and is compatible with the 4.0 release as well, and it does not have any code based on the beta or release candidates.
Table of Contents (15 chapters)
Angular Services
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Getting insights via clustering


So far, we got articles, analyzed their words, and measured the value of them, but how can staring at a bunch of words and numbers possibly provide some insight?

We need to create clusters around the keywords that we are interested in. Since we know the value of the words, we can easily navigate through the bags and see which one of them is a close match to our insight. In other words, what we need to do is group similar articles together.

To be more specific, a keyword will be used as a cluster center, and a group of articles which have the highest similarity (value of words) will be considered to be in closer distance with the cluster center and so eligible to be clustered in one group. This group of articles (called a cluster) provides the insight we are looking for.

For example, if we want to get some insight into the practicality of growing food, building houses, transportation, and so on on Mars, we need to look for related keywords in the corpus and find...