PDF Publication Title:
Text from PDF Page: 031
After investigating the derivative, we develop a new model for PageRank in chapter 4 along with a significant new approach to sensitivity analysis. Instead of using a derivative, which just measures the effect of small change in α, this new model examines an approach based on the variance of the PageRank vector as a function of its parameter over a wide range of values of α. Another interpretation shows that this sensitivity measure corresponds to replacing α in PageRank with a random variable and studying the standard deviation of a set of random PageRank variables. Hence, we call our new method RAPr— Random Alpha Pagerank. Figure 1.3 illustrates how sensitivity works in our new model. Our best-performing algorithm on this problem only involves computing PageRank vectors. 1 1.5 ⋅ contributions 9 x x x 3 x 4 x 5 x 6 0 Figure 1.3 – PageRank with a random variable as the teleportation parame- ter. This plot shows how likely each PageRank value between 0 and 0.5 is when the constant parameter α is replaced with a random variable. Rather than computing the value of PageRank at the circle stem points, we look at the entire range of values it might take. The width of the ma- jor portion of the curves is the new sensitivity parameter. See chapter 4 for more information about this plot and the details of the model. 2 In both of the previous contributions (the derivative and the standard de- viation), the key algorithmic step is a method to compute a PageRank vector. In chapter 2, we review existing algorithms to compute PageRank. For many of the experiments, we used an inner-outer algorithm from Gray et al. [2007]. The performance of this algorithm is excellent and the algorithm is reliable; see figure 1.4. Subsequently, we developed a parallel implementation of this inner-outer iteration for the PageRank problem along with extensions of the idea to other PageRank solvers and new convergence analysis (chapter 5). 0.5PDF Image | Instagram Cheat Sheet
PDF Search Title:
Instagram Cheat SheetOriginal File Name Searched:
pagerank-sensitivity-thesis-online.pdfDIY PDF Search: Google It | Yahoo | Bing
Cruise Ship Reviews | Luxury Resort | Jet | Yacht | and Travel Tech More Info
Cruising Review Topics and Articles More Info
Software based on Filemaker for the travel industry More Info
The Burgenstock Resort: Reviews on CruisingReview website... More Info
Resort Reviews: World Class resorts... More Info
The Riffelalp Resort: Reviews on CruisingReview website... More Info
| CONTACT TEL: 608-238-6001 Email: greg@cruisingreview.com | RSS | AMP |