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In preparation for upgrading the cloud computing tool at Tag Cloud Generator and Service I decided to review tag cloud resources on the web to understand current state and features used.

Below will be brief summary of what was found. First of all here is very useful link to 5 Online Tools To Create Tag Clouds And here is one more review of Word Cloud Generators on the web 12 Cool Word Cloud Generators Some description of tag cloud algorithm and PHP source code can be found at Font variation in tag clouds The usage of tag cloud is now more extended. Many online tag generators now have also text box where any text can be submitted. This allow to use the service for idea brainstorming, text visualization, text analysis.

Originally tag clouds were used as another way of navigation on web site. I still sometimes see the web sites that provide tag cloud widgets however from the reading forum discussion at Tag Clouds: A Worthless WordPress Widget? looks like the usage for website navigation is significantly decreased. However in my opinion this does not mean that such visualization of information is worthless for web site navigation. The problem is that it is very hard to create good tag cloud. The current generators do not have all needed features and so people find tag clouds not usable enough. For example I just saw the tag cloud for “Cloud Computing” and the words “Cloud” and “Computing” where at separated positions. Such separated words can lead to wrong conclusions about links. Additionally I saw some noise words that does not mean much. Such features as remove some words from tag cloud based on different criteria, recognizing word phrases, similar words, grouping near each other tags on the same or similar topic instead of locating tags by alphabet order – all this is very important but still hard to find on the web.

In 2006 in the article The Future of Tag Clouds the author is saying about the idea of being able to manipulate the content and the presentation of a tag cloud. Does anyone know such tools?

Google provides many other powerful applications besides search engine. Many people use Google Calendar, Docs, Drive, Gmail, and Sheets. Google Apps Script lets you do even more with Google. All on a JavaScript platform in the cloud.

Here is how you can create the standalone script.

• Open browser at https://script.google.com.
• Select Blank Project.
• Type Logger.log(“Hello World”); inside default myFunction

So you will have the following function:
function myFunction()
{ Logger.log(“Hello World”); }

• Click on Run and then myFunction to run this script

• Click on View and then Logs to view output of this script.

In this case we used Logger object to have script to print to console. Below are few links for resources about Apps Script

https://developers.google.com/apps-script/reference/base/

http://www.acertainblog.com/2012/12/writing-google-apps-script.html

http://gotofritz.net/blog/tutorials/getting-started-part-1/

This was a very simple basic script but it is showing how quickly to start with google scripting.
In the future we will look at more practical scripts.

Featured Article By Wendy Betterini , Freelance Writer

A new year can be an exciting and motivating time to set new goals, but most people tend to bite off more than they can chew by vowing to tackle every dissatisfying area of their lives at once – which inevitably leads to frustration when they realize that old habits aren’t so easy to change.

If the thought of setting traditional “too big to imagine” New Year resolutions overwhelms you, you may be more comfortable with a miniature version to start. If so, read on for a much easier, simpler version of New Year resolutions that practically guarantees your success.

1) Setting Smaller Goals
The first thing to acknowledge is that you can’t take on every area of your life simultaneously and magically transform it into the dream life you desire. Forget trying to quit smoking, lose 50 lbs., meet your soulmate, start a new business, and add $100 a week to your savings account all at once. It’s perfectly acceptable to have such goals in mind for the long-term, but first you have to start taking smaller steps.

Take a few minutes to think about the most important goals you have for the new year (try tackling just one or two at a time), and then consider ways to break them down into smaller goals. For example, a goal to lose 50 lbs. of excess weight can seem like a daunting challenge – but what if you broke it down into a smaller goal of losing 10 lbs. in January, 10 lbs. in February, and so on until you reach your goal weight? It seems much less intense, doesn’t it?

2) Focus on the Action Steps
Rather than basing your perception of success or failure on the RESULTS you achieve each day, instead try focusing on the action steps themselves. If your goal to lose weight involves cutting back on refined and processed foods, drinking more water, and exercising for 20-30 minutes each day, you can tell at a glance whether you are sticking to your plan or not. If you are, you are making progress. If not, you may need to adjust your plan to better fit your lifestyle. Set an appointment with yourself for a weekly review and pay special attention to old habits of self-sabotage that might get in the way of your goal.

3) Expand Over Time
After a few weeks have passed and you are consistently working on your new bite-sized resolutions, you may feel ready to start expanding your original plan. You may decide to increase the length or intensity of your workouts, add in a few daily action steps on other goals, or otherwise shift gears and broaden your horizons. Simply follow the same bite-sized process above and avoid taking on more than you can reasonably handle. A good rule of thumb is to consider what you know for sure you can handle each day, and then make a list of “extra credit” actions you can take if you have time and energy left over.

Resolutions Are Not Just for the New Year As you may have guessed by now, you don’t have to wait for a new year to begin setting goals and improving your life. Try setting new goals every month, or mini-goals every week. Consider what you would like to accomplish during the next week or month, create a plan for doing so, and get moving on it with consistent effort. Before long you’ll be feeling so empowered from all the progress you’re making that transforming every area of your life will seem much more possible – as long as you do it one step at a time.

Web user modeling can be done in many different ways. Below will be described some of them and will be provided the links to the resources.

One of the way of modeling web user behavior is to use Markov chains. This theory allows us to find the probability of clicking available links if we know the transition matrix. Elements of this matrix are the probabilities of moving from page i to page j

Clustering is the assignment of group of objects into subgroups (clusters) based on some metric. This can be also used to cluster users into some subgroups and then we can compare new user path with the cluster which is the most close to this user. More detailed description of clustering is provided at [1]

Vector space models use similarity to compare user data. Each user can be represented by visited pages, by some keywords from visited pages or some other data. With this model the user is represented as the vector in the vector space. Some perl code and examples for vector space modeling can be found at [2]

Soft computing like neural networks, genetic algorithm, swarm intelligence and many other heuristic or AI methods also can be used for web user modeling. [3] provides taxonomy for personalization of web-based systems by CI models. Collaborative filtering is a method of making automatic predictions (filtering) about the interests of a user by collecting taste information from many users (collaborating). [4]

Different types and many algorithms are described on Wikipedia site. Thus there are many ways to do web user modeling. This post provides some ideas and links to resources that can be used as the starting point.

References

1.Cluster Analysis, From Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Cluster_analysis

2. http://www.lwebzem.com/cgi-bin/res/user_modeling_1.cgi Website User Modeling with Perl

3. RECENT ADVANCES in COMPUTER ENGINEERING and APPLICATIONS Personalization of Web-Based Systems based on Computational Intelligence Modeling TRICIA RAMBHAROSE, ALEXANDER NIKOV

4 Collaborative filtering, From Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Collaborative_filtering

Cloud computing is the use of computing resources (hardware and software) that are delivered as a service over a network (typically the Internet). The name comes from the use of a cloud-shaped symbol as an abstraction for the complex infrastructure it contains in system diagrams.

Cloud computing entrusts remote services with a user’s data, software and computation.[1]

Example of cloud service is Google Cloud Storage which allows store, access and manage your data on Google’s storage infrastructure. The good description of the cloud computing is posted on Technology Cloud Blog [2]. It has also a list of some cloud services.

There are also cloud services that provide ability to develop programming applications. For example dotcloud.com allows to build your ideal application stack by combining powerful cloud services. You do need to pay for development. You start to pay only when you deploy your application. Developers can use PHP, PERL, Python, Ruby, MYSQL and other applications. Artificial Intelligence services in the cloud also can be found: Google provides prediction API which is cloud-based set of machine-learning tools that can help you analyze the data.

Another cloud service is Data Applied, a web based data mining environment. As stated on their site “Data Applied revolutionizes data-driven decision making by integrating rich analytics, data mining, and information visualization capabilities”

References

1.Cloud computing From Wikipedia, the free encyclopedia

2.What is in the Cloud ?

3.dotCloud

4.Cloud Computing

5.Turn on Google’s Prediction API for simple, AI in the cloud

6.Data Applied