HITs Implementation Presented by the Amazingly Brilliant John Yankowski and the slightly less brilliant Larry Phillips

Eigen Values and Vectors Av = λv (λ is the Eigenvalue) Each λ corresponds to one Eigenvector v I don’t know what this means, but Google seems to think its related to Eigen somehow.

The POWER Method!!!! x(k+1) = Ax(k) xk -> Dominant Eigenvector Hey John, What about other methods??

Computing the ultimate authority and hub scores x and y

Steps Step 1 Initialize y(0) = e; e is a column vector of all ones Step 2 take x(k) = Lt y(k-1) , y(k) = Lx(k) and simplify to get…

x(k) = Lt L x(k-1) y(k) = L Lt y(k-1) Computes the dominant eigenvector for the matrices LT L (Authority matrix) and L LT (Hub Matrix)

Benefits of using the dominant eigenvectors of LTL and LLT Incurs a small cost in comparison with using scores from all documents on Web Only one document eigenvector needs to be computed: (LTL or LLT)

Authoritative and Hub Matrices Authoritative means the links are to the website Hub means the the links shoot out from the website

Mexican Hats? Yes, Mexican hats. We submit a query that results in pages 1 and 6, where 1 happens to point to 6

But Hey, What about Sombreros?? Related nodes can be added to a limited extent to make the search more comprehensive

I need Mexican Hats! The query results in Matrix L

MSPaint Matrices are Awesome! From L, we can find the Authoritative and Hub Matrices.

HITs successfully refines the score by computing Xi(k) = Σ yj(k-1) Can be written as X(k) = LTy(k-1) which is the power method that will give you the dominate eigenvector

Dangerously close to a Mexican hat, so we’ll count it We have vectors, weee!!! xT = (0 0 .3660 .1340 .5 0) yT = (.3660 0 .2113 0 .2113 .2113) Why John, Don’t those add up to 1? Why yes they do, and thank you for asking. These numbers give you the ranking for all your Mexican hat web pages. Auth. Ranking = (6 3 5 1 2 10) Hub Ranking = (1 3 6 10 2 5) Dangerously close to a Mexican hat, so we’ll count it

Bibliometricity Yeah, it’s a big word, and we know it Refers to two documents that are in-laws (related through association).

How does Bibliometricity apply to mexican hats? LTL = Din + Ccit LLT = Dout + Cref Mexican Hat in action

How does this apply to the real world? http://www.teoma.com is a search engine that uses hits technology.