Archive for Web Development

Javascript Geolocation Google Maps API Tutorial

Geolocation Javascript API Google Maps Tutorial

The Geolocation API allows you to retrieve the latitude and logitude of the devide hosting the request. The API needs third party sources in order to retrive that information such as the Global Positioning System (GPS) and network signals such as an IP Address, RFID, WiFi or others.
Read more

Most Pressed Keys in HTML development

I found a post called Most Pressed Keys and Programming Syntaxes that shared a simples webapp that allowed to heatmap a virtual keyboard highlighting the most used keys.
I was tempted to find out which are the keys I used the mo.st when developing my Conserveira de Lisboa project, and here’s the result:

Keyboard usage in HTML development

The Johny Cash Project

The Johnny Cash Project is a interactive web project where participants from all over the world draw their contribute Johny Cash to be included into a collective wholesome. The drawings are than displayed to the sound of Johny Cash’s song Ain’t No Grave creating an original and unique videoclip. Watch the video for more information about this project.

http://www.thejohnnycashproject.com/

Arcade Fire – The Wilderness Downtown

Here’s something to remember by: The Wilderness Downtown is a single released by Arcade Fire in 2010
This project is the collaboration between Google Creative Lab, Chris Milk and B-Reel and is fully developed using HTML5 video, audio and canvas and interacts with Google Maps API in order to show the location you enter before the video starts.

An amazing project / experiment worth checking out: http://www.thewildernessdowntown.com/.
If you want to know more about this project visit Mr. doob’s blog post about the Making of The Wilderness Downtown

Vertical search on a Semantic web

What is Vertical Search?

Vertical search engines
A vertical search engine differentiates from a regular search engine due to it’s focus on a given subject or content type.

Topic focused vertical search engine
A great example of topic based search is Trip Advisor, a website with great information for people who are looking to travel.

Content focused vertical search engine
Media Type search can be found on sites such as Youtube, Vimeo, Flickr and others, where you search within specific media file types.
For example when I’m looking to fix CSS bugs my basic instinct makes me search on Google but if the first page doesn’t return the best answer for my problem I use Delicious, for books I use Amazon, etc.

The advantage of using a vertical search engine is that it will narrow the amount of information indexed which will result in more relevant search results.

What is Semantic Web

Semantic Web Experience
Semantic web can be interpreted as an intelligent, self-learning web. The future of semantic web will belong to services that will understand the user and deliver them the best answers for it’s need.

While it’s not perfectly clear for users, semantics have been implemented on several websites for a while now. Amazon was, as far as I know, the first site to implement a semantic user experience when it started suggesting further products based on users preferences. When a user bought a book, Amazon’s software would recommend other books based on purchases made by users who have bought that very same book. The result was a massive increase of sales and profit.
Google also is improving it’s search engine by reordering search results based on user navigation history.

So it’s fair to say a semantic web, or Web 3.0 as some call it, is each more a reality and not a trend. This brings me to this posts topic:

Can Vertical Search Engines coexist in a semantic web?

Personally I see vertical search engines as a the first step into the semantic web concept. I believe some people will say there completely separate things and I’d love to hear a different opinion on the subject.
If I want to find a needle inside a huge barn and know the needle is inside a haystack, I’ll search only inside the haystack. The haystack is my vertical search engine.

Using the same metaphor with semantic web once I’m inside the barn I’ll get a suggestion the needle is probably on the haystack, along with a picture of how the needle might look like and also where in the haystack it will probably be.
Eventually, once I find the needle, related subjects such as strings, other kinds of needles, groups, etc would be suggested as a complement to my interest on the needle.

Being the first time I searched for something I would also get suggestions related to hay and the haystack but if I show no interest in that, further similar searches would not retrieve those suggestions.

What do you think about the future of vertical search? How can it grow in order to survive on a Web 3.0 environment?