This article looks at ontology’s and compares traditional predefined fixed expert ontology’s with the current web trend of individually defined organically growing tagging of web content post-publishing that is becoming every more popular on the web.
It reviews the traditional methods and looks at how they are based on library’s who’s systems where designed to find a book on a shelf so a thus it had to have only one place in the catalog system.
The essence of a book isn’t the ideas it contains. The essence of a book is “book.” Thinking that library catelogs exist to organize concepts confuses the container for the thing contained.
The article basically compares hierarchical systems with a flat unstructured one. The realisation that:
One of the biggest problems with categorizing things in advance is that it forces the categorizers to take on two jobs that have historically been quite hard: mind reading, and fortune telling. It forces categorizers to guess what their users are thinking, and to make predictions about the future.
It ends with an analysis of del.icio.us tagging and provides some statistical views of it.
My ideas from this
- Perhaps you can get the users on a community driven site to classify the content on that site. If uses are offered a system to mark articles (items) as ‘favourites/bookmarks’ they could be also offered a option to tag add tags so they can find it again. These tags could be globally pooled and a dynamic thesaurus could be generated between like terms/tags.
- Music managers, such as iTunes or Winamp, should allow a tag type labelling for genre. Disocogs handles this well but having ‘Genre’ with a top level type label and then ‘Style’ which can be a list of styles an album falls into. Better would be to have this per song as often tracks on the same album will be in different styles.
the semantics here are in the users, not in the system. This is not a way to get computers to understand things…The tag overlap is in the system, but the tag semantics are in the users. This is not a way to inject linguistic meaning into the machine.
I disagree here. I believe that ‘meaning’ of words is individual to everyone and is based on the examples of our own experience. del.icio.us is providing individual opinions of word meanings/groupings and giving an example (the URL). I think together this is closer to how our brains work than anything else. It might be argued that del.icio.us doesn’t understand this information, but what is understanding it? Because del.icio.us doesn’t have a mean to express its ‘understanding’ how can we say it doesn’t?
Within its domain and only mode of expression (i.e. recommending tags based on a given one) then it does understand because it can equate tags that are similar. If this is not understanding then what is? I mean isn’t this what we do when we are asked what a ‘dog’ is? Don’t we recall our experiences of ‘dog’ to create an ‘understanding’ in our minds which is converted to words to relate this. Words that come together to form related meaning, as a dictionary uses words to describe words.
I think in this way Google is in fact intelligent as it is like a concept dictionary of all the information online. ‘Intelligent’ within its domain and mode of communication.