Setting up WordPress on a GoDaddy hosting account is really not difficult (this blog is an example that it can be done!).  Below are my notes on the process.  If you glance at these steps, and don’t want to mess around with this, consider using one of the following hosting services which come with WordPress pre-installed (fairly rare): An Hosting, Lunarpages, BlueHost, Yahoo

Steps for installing WordPress on a GoDaddy Hosting Account

1. Get an account.  If you haven’t already, purchase a hosting account.  I chose the Deluxe plan, which really isn’t very expensive.  You’ll be emailed directions after you purchase the account.  The email will say it takes 24-48 hrs to activate, but it actually only takes 20 minutes or so.

2. Login to the “my account”.  The login is on the GoDaddy homepage.  On the my account screen, click “Hosting Account List”.  Then click “open” under control panel.  You should be at the “Hosting Manager” seen below.

3. Create a MySql Database.  WordPress stores its data on MySql.

• Click the MySql icon.  Then click “Create New Database”. Name the db “WordPress”. 
• Create a db login.
• Confirm.
• Submit.  Wait a minute. Then refresh. The status should change to “setup”. 
• Click the db name.
• Highlight the hostname and copy it (ctrl-c).  You’ll need it for the WordPress config file.

4.  Download WordPress.  Unzip the files.

5.  Configure the file wp-config.php.  Change the following lines using your information.

define(‘DB_NAME’, ‘wordpress’);
define(‘DB_USER’, ‘username’);
define(‘DB_PASSWORD’, ‘password’);
define(‘DB_HOST’, ‘localhost’);

6.  Upload the WordPress directory to your GoDaddy account.  You’ll need an ftp client to upload files to your account (I use Smart Ftp) and you’ll need the ftp address for your site.  Your address is ftp.yourdomain.com.  Put the files in you top level directory, that way when you go to www.yourdomain.com it will load WordPress.

7. Test WordPress.  There are detailed directions for configuring WordPress here.

Around the Web

• Here is another good tutorial.

Flash remoting is a big improvement over forms/cgi for communication between flash and server.  There’s a great little project called amfphp for using php with flash remoting.  There’s a whole lot less great (but appreciated!) version called amf::perl for perl and python. There is little documentation, so I thought I’d post an example. 

Here’s my remoting notes dealing with amf::perl.  For context, I was working on a movie recommendation system.

Steps:

(1) On the Server side, in the cgi-bin, create a perl file, and call it, say “recommendation.pl”.   Your version of this file will look the same, except replace “/recommendation” with an appropriate subdirectory where you will put the code in step 2. 

#!perl  -w
use strict;
use AMF::Perl;

my $gateway = AMF::Perl->new;
$gateway->setBaseClassPath("./recommendation/");
$gateway->service();

(2) In a subdirectory, in this case “/recommendation”, create a perl module, in this case called “rec.pm”.  This module contains the “methodTable” which will be accessed by the flash code.  The example below has both get and set calls. 

#!perl  -w

use AMF::Perl;
use lib 'Filesystem\\Active Projects\\'; ## directory where my server side code is
use SimMan::TitleLookup; ## my own server side perl modulesuse SimMan::Recommendation;

package rec;

## must have this constructorsub new 
{
    my ($proto)=@_;
    my $self={};
    bless $self, $proto;
    return $self;
}

sub methodTable
{
    return {
        "getFeatureWeights" => {
            "description" => "Returns the current feature weights",
            "access" => "remote",
        },
        "setFeatureWeights" => {
            "description" => "Sets the current feature weights",
            "access" => "remote",
        },

        "disambiguateQuery" => {
            "description" => "Returns possible titles and their ids",
            "access" => "remote",
        },
    };
}

sub getFeatureWeights
{
    my ($self) = @_;
    my $hash = SimMan::Readers::readFeatureWeights();
    my @array;
    push @array, $hash;
    return \@array;
}

sub setFeatureWeights
{
    my ($self, $featureWeights) = @_;
    SimMan::Readers::setFeatureWeights($featureWeights);}

sub disambiguateQuery
{
    my ($self, $usertext) = @_;
    return $titles = SimMan::TitleLookup::getCandidateTitles($usertext);
}

1;

(3) On the client side, first include the necessary files and give the location of the perl files we just created.  

Then you can directly call the methods listed in the methodTable.  Notice that the results sent back by the perl module will be returned to a function called “method_result”, where method is the name of the method.

import mx.remoting.NetServices;
NetDebug.initialize();
NetServices.setDefaultGatewayUrl("http://localhost/cgi-bin/recommendation.pl");
var connection = NetServices.createGatewayConnection();
var recommender = connection.getService("rec", this);

function disambiguateQuery_Result(result){
    if (result.length == 0){
        Results.htmlText = "<b>No movies found</b>";
    }
    else{
        Results.htmlText = "<b>Are you looking for...</b><br><br>";
        for (i=0; i< result.length; i++) {
            Results.htmlText += "result[i].id + " " + result[i].title + "<br>";
        }
    }
}

searchText.enter = function(){
    recommender.disambiguateQuery(searchText.text, 10);
};

Hope this helps someone!

In my daily work I tend to manipulate fairly large datasets, such as Wikipedia, U.S. Patents, Netflix Ratings, and Imdb.  Here’s a few tricks I’ve come across so that you don’t lose time waiting for your programs to finish. 

1. Use Storable
   • If you need to a save a hash, array, or more complex data structure to use in its entirety at a later time, it is around 4 times faster to use storable than to read/write it from a text file.  Its simple to use, just two calls…
   • store(\%hash, $filename);
   • $hashref = retrieve($filename);
2. Use a Berkeley Db for random access
   • Berkeley Db’s are associative databases (as opposed to relational databases like MySql, Postgresql, etc).  And they are quite useful.
   • Whereas we want to use Storable when we will be later loading the entire data structure back into memory, we want to use BDBs when we will only be performing random access at a later time.  So, for example, lets say I have all the IMDB movie titles in a hash, and I want to save it to disk.  But I know that later on I am only going to want to look up one or two titles at a time, so that’s a case where I want to use a BDB.
   • There’s two modules for BDBs to choose: DB_File or BerkeleyDB.  I usually use DB_File.
3. Use Unix Grep
   • This might sound a bit off the wall, but when you have your data in a file, rather than reading it in and parsing it using Perl regular expressions, it can be up to 100 times faster to call Grep or AWK.  Grep is particularly useful when your task is simply to lookup something in a text file.  In general, when trying to speed up code, don’t be afraid to take advantage of the operating system.
   • system(“command”, $input, @files);
4. Patterns for Storing Hash Structures
   • This tip is somewhat domain dependent.  I often find myself using 2d hashes, primarily because I work with data represented as graphs (i.e. a set of edges represented as node-node-weight).  So these 2d hashes look like {id1}->{id2}=value.
   • When writing such a hash out to text I’ll use the command chr(1) to generate a delimiter, and directly write “id1 id2 value\n” (with chr(1) instead of spaces) per entry.
   • When using Storable, I don’t need to do anything special.
   • When using a BDB, there is no such thing as a 2d hash.  Either one has to create multiple BDBs, or, usually the better option, is to convert the hash to {id}=id2a|value|id2b|value… and use split when accessing the data.  Again, I like to use chr(1) instead of | as a delimiter. 

Over the past year and a half I’ve been hooked on the language Processing. I’ve even contributed a early version library for visualizing social network data. 

For those unfamiliar with Processing, it’s a variant of Java.  Its distinguished by its emphasis on interactive media. The fundamental unit in Processing is a sketch, which is entirely and continuously redrawn at some given rate.  Sketches may be compiled into either standalone apps or Java applets.

Many creative types work with Processing–here’s some cool examples: The Dumpster, Thinking Machines 4 (pictured left), and Relations Environment. More can be seen on exhibition.  Its not hard to see why I was excited by the language. 

I’m still excited by the Processing community and all the cool apps and exhibits they are turning out.  However, today I am much less excited by the technology. 

1. As an Internet content delivery mechanism, Java Applets are a poor choice.  They have a large memory footprint and so are slow to load, and they provide few options for communicating between client and server.
2. Sketches are redrawn in their entirety with each tick of the clock.  There are no layers.  Why is this a problem?  This limits the number of graphical objects one can involve in a sketch without the sketch slowing down.
3. There are no user interface components of any quality.  And Java Swing is not compatible with Processing.  While this is a real limitation, this is a somewhat hollow complaint, as I realize it is only a matter of time before quality UI widgets are created within Processing for Processing. 
4. Java 1.5 is not supported.  My concern here deals with the fact that one of Processing’s greatest strengths is that a developer may use Java.  I am wondering whether the Processing community will be able to maintain this integration over time. 

Recently I’ve been looking into Flash (e.g., the chart in Google Finance is Flash) and have begun to believe that Flash is a better alternative.  It is great at content delivery, has convenient UI components and support, and the fundamental unit of Flash, the “movie”, can be redrawn using separate layers.

I am still learning ActionScript, the object-oriented language used for Flash.  My early impressions of it are that recent versions 2.0 and 3.0 are of a pretty high quality, but a far cry from Java.

I’ll post a follow-up to this in a few months after I have more experience with Flash and Actionscript under my belt.

Around the web

• Processing (Wikipedia)
• Processing
• Processing Blogs
• Processing Hacks
• Flash (Wikipedia)
• Flash Kit
• Flash / JavaScript Integration Kit
• Flash Remoting with PHP
• Flash Remoting with Perl

This post is a bit off topic for this blog.  However, I recently decided I really needed an off-site backup service (er, I lost some files).  And, as usual, I spent way too much time looking around the web for such a service.  Anyways, I thought I’d share my homework.   To give you an idea of my situation, I have about 30GB of data (code, datasets, visualizations) that I need constantly backed up. 

Backup Services vs. Online Storage

There are a ton of options.  I just wanted an automatic backup service–one that works flawlessly.  Many services I looked at emphasize that the files can be accessed anywhere.  These services often refer to themselves as online storage rather that online backup.  The pure backup services usually offer unlimited space and focus on the software for backing up changes on demand or when your computer is idle, and on the software for restoring files.  The tradeoff is usually that files are stored compressed, and are only meant to be accessed for somewhat rare restores.  Online storage services, by comparision, limit the storage space, and although they almost always advertise the backup aspect, files usually need to be manually transfered.  The advantage is that the files on such services can be accessed over the web. 

I’m happy to keep files on my usb flash drive which I need access to wherever I go, and so I just need the automatic backup services. 

I’ve ranked the services based on my impressions of their offerings and personal experience…

Best Deals

1. Mozy–I ended up going with Mozy as my backup service, and an very happy so far.  I go to lunch or a meeting, and come back to a message that my files were backed up while my computer was idle.  The software for selecting which files and folders to backup is quite easy to use.  However, Mozy is purely a backup service, all files are stored compressed on their servers.  So if you’re interested in remote access to your files, look elsewhere.  2GB free, or unlimited space for 4.95/month.
2. Carbonite–Their software for automatic backup is really pretty slick.  I was torn between Carbonite and Mozy.  Like Mozy this is strictly a backup service.  There is no free version; unlimited space for 49.95/yr. 

Runners Up

1. StreamLoad (MediaMax)–StreamLoad is rebranded across a number of sites including MediaMax.com and the AMD Media Vault.  Initially, at least on paper, this seemed liked the best deal to me.  They have a free service of 25GB (they throttle downloading though), which may be enough space for many folks.  It both supports automatic backup and provides anywhere access to your files.  Its 4.95/month for the larger 100GB.  I said initially it looked good.  I downloaded the software, and it kept crashing on both my laptop and desktop.  Unacceptable   Maybe others will have a better experience.
2. Files Anywhere–Provides both online access and automatic backup.  11.95/month for 10gb. 
3. Box.net–Looks nice, but only 5GB for 4.95/month is too small for my needs.
4. FlipDrive–Does not provide automatic backup.  4.95/month for 20 gb. 
5. Iomega IStorage–5GB for 19.99/month.  Yikes!  Too small a space, and too expensive.
6. IBackup.com–5GB for 9.95/month, 50GB for 49.95/month.  Too little for too much. 
7. ShareFile.com–Pay by bandwidth.  23.95/month for 2gb of bandwidth.

Foolish

1. XDrive–Owned by AOL.  Provides for automatic backup and online access.  Strictly a free service which provides 5gb of space.  Reviews are mixed on its software, but mainly I decided to stay away because if I needed more than 5gb, there is no means of upgrading.
2. GoDaddy I’m a big GoDaddy fan.  This blog runs on a GoDaddy Hosting accont. But their online storage service just does not look like a bargain.  Called “Online File Folder”, its 2gb for $20/yr.  No automatic backup software.
3. True Share–Overpriced.  “As little as 30/month for 3gb”.
4. Amazon S3–A web service.  This is strictly for developers only.  Might be a good deal for a small or medium sized business.   
5. Yahoo Briefcase–A pathetic 25mb of storage.  Might as well just use Gmail for storage.

If you just need online storage and remote access, consider a regular hosting account…

1. An Hosting
2. Lunarpages
3. BlueHost
4. Yahoo

Around the Web

1. TechCrunch: The Online Storage Gang
2. PC World: Online Storage 

All Google Tech Talks are here (Google EngEDU is the actual name of the talk series). Thought I’d compile a top ten list…

1. Python and Python 3000. Two talks about the Python language given by its inventor Guido van Rossum. The first is about the language’s origins and the second is about its future.
2. How Open Source Projects Survive Poisonous People (And You Can Too). Really liked this talk. Really liked it! Given by the lead developers of SubVersion (and other large projects), this talk provides a guide to working as a team. Next time I lead a project, I am going to ask everyone to watch this before starting work.
3. Winning the DARPA Grand Challenge. The story of the robot race thru the mojave desert. Having been on a Grand Challenge team, I appreciate just how hard it was to win.
4. Scrum, et al. An excellent talk about the Scrum agile software development methodology.
5. Wikipedia and MediaWiki. A talk about the implementation of Wikipedia given by it original, and for a long time, only paid staff developer. Not a very dynamic talk, but the insider perspective is interesting.
6. Computers versus Common Sense. Doug Lenet gives a talk about the famous AI project Cyc. I thought this project was put to rest a long time ago. Guess I was wrong. Anyways, if you like symbolic Artifical Intelligence, its a really interesting talk.
7. Scholarly Data, Network Science, and (Google) Maps. A very good information visualization talk.
8. 15 Views of a Node Link Graph: An Information Visualization Portfolio. A bunch of visualization techniques. I think Tamara Munzner leads some of the most interesting visualization work anywhere.
9. Human Computation. A talk about harnessing human knowledge for tasks such as spam filtering and image recognition.
10. Scrum Tuning: Lessons learned from Scrum implementation at Google. A talk about the experience of using Scrum given by one of its inventors.

I recently posted an efficient algorithm for computing the similarity of two Wikipedia pages (or any two nodes in a network) using cocitation similarity. Another type of similarity which may be worth considering is bibliometric coupling, in which two pages are similar if the pages they link to are similar. What is interesting is that it is only a few minor tweaks to the cocitation algorithm to compute bibliometricc coupling. Here’s the bibliometric coupling psuedocode (Perl style):

%nodes, %links //the wikipedia pages and pagelinks
%reverse = reverse(%links) //flipping the pagelinks around
%biblioCounts //2d hash for temporarily storing counts
%scores //2d hash storing the final similarity scores

foreach node (keys %nodes){ 

   foreach linkedNode (keys %links->{node}) //count cocitations for node (wiki page)
      foreach node2 (keys %reverse->{linkedNode})
         $biblioCounts{node}->{node2} ++;

  citationCount = keys(%linked->{node})
  foreach node2 ( keys %biblioCounts{node}) //similarities scores for node
      citationCount2 = keys(%linked->{node2})
      scores{node}->{node2} =
		2 * biblioCounts{node}->{node2} / (citationCount + citationCount2)
}

I’m working on a visualization, a ‘map’ if you will, of Wikipedia pages. The map will layout pages close to one another if they are similar. So, in order to create such a map I need to compute the similarity of any two Wikipedia pages.

For my first attempt at this, I decided to go with a cocitation measure of similarity. So, two Wikipedia pages will be said to be similar if other Wikipedia pages that link to one usually link to the other.

However, the naive way to compute this, looking at every pair of pages, is far too inefficient given that there are 650,000 pages in the English Wikipedia, and 14.5 million pagelinks. So I’ve worked up a much more efficient algorithm. Here’s the psuedocode…I hope someone, somewhere out in cyberspace will find this useful. (It can, in fact, be used to compute co-citation similarities for any data represented as nodes and links)

%nodes, %links //the wikipedia pages and pagelinks
%reverse = reverse(%links) //flipping the pagelinks around
%cocitations //2d hash for temporarily storing cocitation counts
%scores //2d hash storing the final similarity scores

foreach node (keys %nodes){ 

   foreach sourceNode (keys %reverse->{node}) //count cocitations for node (wiki page)
      foreach cocited (keys %links->{sourceNode})
         $cocitations{node}->{cocited} ++;

  citationCount = keys(%reverse->{node})
  foreach node2 ( keys %cocitations{node}) //similarities scores for node 
      citationCount2 = keys(%reverse->{node2})
      scores{node}->{node2} =
		2 * cocitations{node}->{node2} / (citationCount + citationCount2)
}

15 Views of a Node Link Graph: An Information Visualization Portfolio by Tamara Munzner

Scholarly Data, Network Science, and (Google) Maps by Katy Borner

Geographical & Historical

WorldProcessor. Globes overlaid with information. Beautiful…must see!
Wikisky Google maps for the stars.
Flight Patterns Visualizations of FAA data.
TextArc: History of Science Beautiful.
2007 Calender. Brad Paley design.
31 days in Iraq. Visualization of deaths in Iraq. Depressing.
Tracing the Visitor’s Eye Flickr tags on a geospatial basemap.
Schreiner International Cables Map. Old world map of cables.
Napolean’s March. Made famous by Edward Tufte.

Government

The State of the Union in Words. From the NYTimes.
Death and Taxes. Where taxes go to.
U.S. Frequency Allocations Chart. Radio frequency allocations.
2006 Election Results. Interesting maps.
Taxonomy Visualization of Patent Data. Patent viz.

Internet

IRC Arcs IRC viz.
Welkin RDF visualizer.
History Flow Visualization of the Wikipedia. Wikipedia viz.
Who owns the Internet? Map of the net backbones.
Amaznode. Amazon product visualization.
Java Technology Concept Map. Relationships among Java technologies.
The Dumpster. Romance and Blogs.

Pop Culture

Radio Protector Music recommendation visualizer.
Movie and Actors. Visualization of imdb data.

Geneology

rhnav Geneology visualization.
20 Generations Family Tree. One particular family tree viz.
Swarm. Networks of website.

Science

Tree of Life. Species visualization.
Map of Science. From the journal Nature.

Literature

TextArc Visualizations of books, other writings
Visual Poetry. Visualizations of poems.
The Voice. One of the better tag clouds I’ve seen.

Other

Thinking Machine 4. A chess match viz.
Ph.D. Thesis Map. Dissertation outline in the style of a subway map.
Newspaper Map. Very unusual.
Visual Elements Periodic Table.