InDegree Analysis: Difference between revisions

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== Parameters ==  
== Parameters ==  


No parameters found.
$n$: number of pages
 
$m$: number of hyperlinks
 
$z$: # of topics/categories


== Table of Algorithms ==  
== Table of Algorithms ==  
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| [[The INDEGREE Algorithm (InDegree Analysis Link Analysis)|The INDEGREE Algorithm]] || 1997 || $O(m^{2} n )$ || $O(n)$ || Exact || Deterministic || [https://www.w3.org/People/Massimo/papers/quest_hypersearch.pdf Time]
| [[The INDEGREE Algorithm (InDegree Analysis Link Analysis)|The INDEGREE Algorithm]] || 1997 || $O(mn)$ || $O(n)$ || Exact || Deterministic || [https://www.w3.org/People/Massimo/papers/quest_hypersearch.pdf Time]
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Revision as of 09:24, 10 April 2023

Description

A simple heuristic that can be viewed as the predecessor of all Link Analysis Ranking algorithms is to rank the pages according to their popularity (also referred to as visibility (Marchiori 1997)). The popularity of a page is measured by the number of pages that link to this page. We refer to this algorithm as the InDegree algorithm, since it ranks pages according to their in-degree in the graph $G$. That is, for every node $i$, $a_i = |B(i)|$.

Related Problems

Related: Link Analysis

Parameters

$n$: number of pages

$m$: number of hyperlinks

$z$: # of topics/categories

Table of Algorithms

Name Year Time Space Approximation Factor Model Reference
The INDEGREE Algorithm 1997 $O(mn)$ $O(n)$ Exact Deterministic Time

Time Complexity Graph

Link Analysis - InDegree Analysis - Time.png

Space Complexity Graph

Link Analysis - InDegree Analysis - Space.png

Time-Space Tradeoff

Link Analysis - InDegree Analysis - Pareto Frontier.png