popular this month

recent comments

recent articles

  • The Avengers

    Almer S. Tigelaar 11 / 05 / 2012

    Marvel teased us with the release of this film near the end of various previously released super hero flicks like Captain America and Iron Man 2. This would be the movie that unites all the super heroes from the Marvel universe. Well actually, only those that had not been previously licensed to other studios. Hence, you will not find characters from X-Men, Spiderman, or the Fantastic Four in this movie. Director Joss Whedon brings back fond memories of creative television series like Firefly and Dollhouse, but what does he make of a 220 million blockbuster production?

    read more 0 comments

  • Hugo

    Almer S. Tigelaar 06 / 03 / 2012

    Hugo is based on a relatively recently released (2007) award winning book by Brian Selznick. It is not surprising that the film rights to the books were quickly sold, and certainly not by the least of directors either: Martin Scorsese. He has a career spanning decades and has directed a string of movies in recent years which I liked, among which are Shutter Island, The Departed and Gangs of New York. However, those were admittedly all in different, less family friendly, genres. So, I went to Hugo hoping to be pleasantly surprised.

    read more 0 comments

  • How long would it take to read Wikipedia?

    Almer S. Tigelaar 21 / 02 / 2012

    Wikipedia has become the de facto encyclopedia on the Internet. A traditional encyclopedia spans many textbook volumes which would take any normal person ages to read. Few people would likely engage in such an endeavor. However, since Wikipedia is readily accessible: should you take up the challenge?

    read more 0 comments

Almer S. Tigelaar » Graduation Committees

Kien Tjin-Kam-Jet: Result Merging for Efficient Distributed Information Retrieval

Almer S. Tigelaar 03 / 04 / 2009, 16:00

Result Merging for Efficient Distributed Information Retrieval
by Kien T.E. Tjin-Kam-Jet

View in Repository

Abstract
Centralized Web search has difficulties with crawling and indexing the Visible Web. The Invisible Web is estimated to contain much more content, and this content is even more difficult to crawl.
Metasearch, a form of distributed search, is a possible solution. However, a major problem is how to merge the results from several search engines into a single result list. We train two types of Support Vector Machines (SVMs): a regression model and preference classification model. Round Robin (RR) is used as our merging baseline. We varied the number of search engines being merged, the selection policy, and the document collection size of the engines. Our findings show that RR is the fastest method and that, in a few cases, it performs as well as regression-SVM. Both SVM methods are much slower and, judging by performance, regression-SVM is the best of all three methods. The choice of which method to use depends strongly on the usage scenario. In most cases, we recommend using regression-SVM.

More in Graduation Committees: