Friday, February 16, 2007

Chapter 6

Chapter 6

After reading chapter 6, I feel much more knowledgeable on “global swarming”. The first thing that I found important was the discussion of recommender systems. They are computer programs that attempt to predict items such as movies, music, books, news, and web pages. These are all things that a user might be interested in and they give information about the user’s profile. This is how it is used in Amazon.com because they sell all of these types of items. Recommender systems are very important and useful in this industry of online retail. They are also used in social networking sites such as Facebook. This is done through collaborative filtering. Collaborative filtering is the method of filtering the interests of a user by collecting taste information from many users. This is exactly what Facebook does. In Facebook, a user is able to put down his or her interests and then search for others in their network with similar interests. The chapter also got into how search engines work. They mine the knowledge implicit in multiple trails that structure the web. The first search engines relied on very simple forms of first- order heuristic search. Web search engines work by storing information about a large number of web pages, which they retrieve from the WWW itself. This is done using a Web crawler, also known as a spider. It follows every link it sees. When a user comes to the search engine and makes a query, by using key words, the engine looks up the index and provides a listing of the best matching web pages. Search Engines are only useful if the result given is relevant. This is why most search engines rank their results in order of relevance. The reading also presents a metaphor using the digital world and the biological world. All ants and insects are forced to chose paths. This is very similar to search engines and the world wide web. Search engines take you on a path to where you want to go. Overall, I learned a lot from this reading about the web. There are things I take fro granted and I never think about how they work. This reading helped me to understand these things.

2 comments:

Bharat said...

I agree- its a nice introduction to the intricate details that the WWW has.

--Bharat

Christian Beck said...

I also thought recommendation systems are pretty interesting. I'm not sure how into movies and music you are but I love movies and love finding new music and books on Amazon (you have to be nerd to be in grad school). The problem I find with these recommendation systems is that they can only search for similar things. This is true with the facebook. But sometimes, I like a song or band that I wouldn't expect at all. I'm sure you probably have different kinds of friends. So, I think that recommendation systems still fall short because they can't mimic this aspect of finding things in real-life.