June 25, 2008
What is it?
You probably noticed the ‘G’ button on the right hand side of the field for adding new tags, and of the ‘tags’ field in the search. That is the Google search button that we wrote about on our Help page here. However, we thought that this feature deserves its own post on the blog, because it helped us with finding tags many, many times.
How does it work?
With Google search button, you can search for tags as you would search Wikipedia pages on Google. For instance, if you type in ‘apple’, and click on the Google button, the system will automatically add ‘wikipedia’, so your query will actually be ‘apple wikipedia’, and search result will be retrieved from the domain en.wikipedia.org only.
Experience showed us that this way of finding tags can be quite helpful and time saving. Sometimes it is hard to find the most appropriate tag with autocomplete list, and Google is pretty clever when it comes to finding the most popular/representative tag for an acronym or ambiguous term, for instance. So, it is often the case that the tag that you are looking for is at the top of the list. To add it just click on the ‘copy’ link.
Cases in which it beats the autocomplete list
- Acronyms and their disambiguation:
- EU = European Union
- RHCP = Red Hot Chili Peppers
- CSS = Cascading Style Sheets, Content Scramble System, Cansei de Ser Sexy
- LCD = Liquid crystal display, Lacida, Lowest common denominator
- SEO = Search engine optimization, Seasoned equity offering
- RDF = Resource Description Framework, Robotech Defense Force, Radical Dance Faction
- REST = Representational State Transfer
- Ambiguous terms:
- apple (fruit, digital technology corporation, Fiona Apple, bank…)
- keyboard (computers, music, magazine…)
- office (software, place where you work, series, film…)
- flash (software, superhero, photography, song…)
- Searching for the right term for the concept:
- programming = Computer programming;
- baby = Infant;
- tiredness = Fatigue (medical);
- moonlight sonata = Piano Sonata No. 14 (Beethoven);
- rachmaninov = Sergei Rachmaninoff. (Note that in this case the term is not even spelled correctly)
- When you know what you think of, but you don’t know/can’t remember how to name it:
- belarus capital = Minsk
- eu lead body = European Council
- kaiser chiefs singer = Ricky Wilson (British musician)
- If you wish to search for related tags or tags concerning a broad topic:
- online social (Social network, Social software, Online identity, OpenSocial, Virtual community, Social bookmarking, Social computing)
- vegetarian (Vegetarianism, Vegetarian cuisine, Vegetarian Society, World Vegetarian Day, Veganism)
- olympic games (Olympic Games, Summer Olympic Games, Winter Olympic Games, Ancient Olympic Games, Youth Olympic Games)
- If the tag contains non-English characters, and you don’t want to deal with them:
- roisin murphy = Róisín Murphy
- motorhead = Motörhead
- It is slightly different than autocomplete list, e.g. you have to click on the ‘copy’ link instead of on the tag name (which is a link to a Wikipedia page)
- Search results list will also contain some Wikipedia pages which are not tags, like pages whose names start with ‘Special:’, ‘Template:’, ‘User:’, ‘Wikipedia:’, ‘Help:’, ‘User talk:’, ‘Wikipedia talk:’, ‘Category:’. These are special Wikipedia pages and obviously cannot be used for tags, so you cannot add them.
We hope we’ll be able to fix these issues soon.
Inserting correct tags is essential for Faviki in order to use its potentials to the maximum. But finding the right tag is sometimes a bit tricky. We hope that Google search API can make your tagging easier and more accurate.
June 17, 2008
Good news everybody! The Faviki team is proud to announce that we have started the Help section on http://faviki.wikia.com/wiki/Help. If you have had any questions about using Faviki, saving bookmarks or any other topic, we hope it will give you the answers you need.
We tried hard to cover all the aspects of using Faviki and to pay special attention to the details that might be new or confusing to some or all of our users. If you think that there is more that should be said, we welcome you to take an active part and contribute to Faviki Help. If you think that the section needs some additional information, or believe that you can explain some of the more tricky aspects of social bookmarking to others, don’t hesitate to have a part in developing Faviki.
As Faviki keeps on growing and developing so will the Help section change too. We will keep it up to date with all of the new features and changes that we are planning as soon as they happen. Again, don’t hesitate to take part in it. Any help with help is welcomed :-).
June 4, 2008
It started great…
When you put a lot of time and energy into something it sure is great to see that it was not in vain. Well, last week was exactly that way for us. From May 23rd Faviki is a featured project on Google code homepage, as a tool that uses Google AJAX search API.
Google API helps Faviki users with adding tags and searching. Sometimes it is hard to find the most appropriate tag with autocomplete list, especially in the cases of abbreviations and ambiguous terms. That is where Google search comes in handy. We’ll have more about this feature very soon.
This was a great nod to us and we were very excited and proud especially considering that we are a long time users of Google tools and services. Since then we’ve had a huge increase in visitors and Faviki started getting the attention we honestly believe it deserves.
But that was just the beginning. On May 26th an excellent article about Faviki was posted on ReadWriteWeb. The article is a great description of what Faviki is, how it is used and what problems it solves. Among other things the article concludes:
If that turns out to be true [that tags will play an increasingly important role in the structure of the web,] then Faviki represents a big step in that direction by offering a transitional service between social bookmarking and a purely semantic-based bookmarking service that would automatically know how to tag any content saved by discovering the semantic aspects already associated with that web page.
…and then got even better!
They say that when it rains it pours, but when it’s shining… well it can be really bright! Here’s more of the “sunshine” we had during last week.
Also, Faviki is officially a killer! A killer startup, that is. Here is a part of what Killer startups had to say about us:
Why it might be a killer
Faviki is the next generation in social bookmarking. There are a lot of implications for semantic search and semantic tagging. It makes this a lot more efficient and easier for the user.
A Rotorblog post by Arnold Zafra entitled Faviki Offers Social Bookmarking with Semantic Tagging stated the following:
Faviki has the making of a killer application. The only problem it faces right now is how to get into the social bookmarking niche with the presence of already popular del.ici.ous, magnolia and others. But sometimes, we users tend to look for something else. So, Faviki is a good alternative, if not worthy of at least a try.
There is also a very good post Faviki uses Wikipedia and DBpedia for semantic tagging. Author’s question was:
One interesting research question is whether it’s possible to combine the ease of using user-generated tags with the power of mapping them into tags in a structured or semi-structured knowledge base.
And his conclusion is:
Deriving knowledge bases from Wikipedia and using them in innovative is a very exciting topic that is sure to receive a lot of work in the coming years.
Dennis D. McDonald’s question was How Important Are Tags to You?. He notices the following:
While controlled indexing vocabularies and classifications schemes have existed for as long as indexes, catalogs, and information retrieval systems have existed, the benefits of such controlled vocabularies have been somewhat limited to professional and specialized communities or other organizations that already have a vested interest in standard ways of referring to concepts and ideas.
Once authorship and usage extend beyond such communities – which happens very easily online – it’s possible that the advantages of standardization, specialization, and specificity of tags might start to break down as profession- and knowledge-based borders are crossed.
We are really excited that Faviki has broken the language barrier. A detailed description of Faviki in Japanese can be found at http://mojix.org/2008/05/27/faviki. Two more posts about Faviki in Japanese can be found here and here. There are also posts in Chinese and Italian.
In addition, the first printed article is published in the Italian magazine Digital life. Check out the online version. Thanks, Donatella!
We are so modern we belong to the museum
But a very special type of museum it is. Faviki is now a member of Museum of Modern Betas. Even if you are not exactly a museum type you can get your dose of cutting edge bookmarking!
The word about Faviki has also spread on Twitter. We found two of the tweets especially cute:
Finally, we would especially like to mention the very first post about Faviki. Matt was among the first Faviki users and his support has meant so much to us.
So, as you can see, last week was really great. We extend our thanks to all of the websites and people mentioned above. Also, we send thanks and best regards to all of our users. You Favikings give us the energy and drive to continue our quest of developing Faviki. Your feedback is always welcome, as we are trying to make our website better for you (and for us, because we use it too :)).