Our final project will be on page rank. We will be covering topics such as the simplified algorithm for producing page ranks, damping factors, page rank computation methods, and spam detection algorithms.

PageRank is a link analysis algorithm. It has many day to day uses for example, it is utilized in the google toolbar to rank the popularity of sites. The google toolbar picks a whole number between 0 and 10 and ranks the popularity accordingly that is the most popular sites get a rank of 10 and the least popular a lower number. Now what is a Link analysis algorithm? Let us give you an example instead of defining it. Suppose you type in the google search “USA Vacations” the results would be ones that are the most popular and are most likely to give you the correct and the related information to the topic typed into the search. The formal definition for Link analysis algorithm is “is an algorithm that explores associations between related objects”.

Something to note first: PageRank is not that 1-10 number. The 1-10 is actually just the scaling used in the toolbar to make it understandable. Actual PageRank represents something much more intrinsic.

This might will almost certainly involve math that you are not totally familiar with. If this is the case, make sure to ask one of the TAs EARLY to figure out how the key algorithms in PageRank works. Make sure you research real-life applications in PageRank, and how it is modified in practice, and how it can fail or lead to “link spam.”

What type of math does it include(Just Curious)