What should we do when encountering a sink in the case of page rank algorithm? Stop the algorithm. Start with the last node. Randomly choose a node from all nodes. Randomly choose a node from neighbor nodes.
Question
What should we do when encountering a sink in the case of page rank algorithm? Stop the algorithm. Start with the last node. Randomly choose a node from all nodes. Randomly choose a node from neighbor nodes.
Solution
In the case of the PageRank algorithm, when encountering a sink (a node with no outgoing links), it can disrupt the ranking process as it "traps" the rank. Here are the steps to handle this situation:
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Identify the sink nodes: These are the nodes in the network that do not have any outgoing links. They are easy to spot as they only have incoming links.
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Implement a damping factor: The damping factor (usually set to 0.85) is a technique used to mitigate the effect of sink nodes. It represents the probability of a user randomly clicking on a link on the page.
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Distribute the sink node's rank: The rank trapped in the sink node is distributed evenly among all other nodes in the network. This is done to simulate the behavior of a user who, when reaching a sink node, jumps to another random node in the network.
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Continue the algorithm: After dealing with the sink nodes, the algorithm can continue with its iterative process of rank calculation.
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Check for other sink nodes: After each iteration, check again for any new sink nodes that may have been created and repeat the process if necessary.
Remember, the goal of the PageRank algorithm is to effectively distribute rank (or importance) across all nodes in the network. Dealing with sink nodes in this way ensures that no rank is lost and the algorithm can converge to a stable state.
Similar Questions
In the page rank algorithm We randomly travel from node to node without any relationship. We randomly travel from node to neighbor node. The maximum visited node will be the leader. B and C A and C
What is a sink? A node with no incoming edges. A node with maximum incoming edges. A node with maximum outgoing edges. A node with no outgoing edges.
In the page rank algorithm the leader is decided by? A node(person) with maximum number of outgoing edges. A node(person) with maximum number of incoming edges. A node(person) which is visited maximum times. Can not decide.
Consider the network in Fig 2 of N = 5 nodes and the iterative pagerank formula. Determine the first iteration of ranks, assuming α = 0.8, R0 = [1/5, 1/5, 1/5, 1/5, 1/5] and E = [1/5, 1/5, 1/5, 1/5, 1/5]
Ranking BooksThere are N books in a shelf which are already arranged in non-increasing order of number of pages in the books. Each book will be given a rank starting from 1 depending on the number of pages. The book with the highest number of pages will be ranked 1. You are writing a new book and it will be completed in M days. Everyday after adding some pages in your book, you want to find the rank of the book in the shelf. Please note that book's with same number of pages will be given same rank. Write an algorithm to find the rank of your book in the shelf for each of the M days.Input FormatFirst line of input contains T - number of test cases. Its followed by 4T lines, the first line contains N - number of books in the shelf and the second line contains N integers, which denotes the number of pages in ith book. The third line contains M - number of days to complete your new book and the fourth line contains M integers, which denotes the number of pages in your new book at the end of ith day.Output FormatFor each testcase, print M integers denoting the rank of your book at the end of each of the M days, separated by a new line.Constraints30 points1 <= T <= 1001 <= N, M <= 1021 <= arr[i] <= 10670 points1 <= T <= 2001 <= N, M <= 1041 <= arr[i] <= 106ExampleInput27100 100 50 40 40 20 1045 25 50 120345 30 1245 12 70 100Output6 4 2 14 3 1 1ExplanationExample 1:When your book has 5 pages, it will be ranked 6: 100 100 50 40 40 20 10 "5"When your book has 25 pages, it will be ranked 4: 100 100 50 40 40 "25" 20 10When your book has 50 pages, it will be ranked 2: 100 100 50 "50" 40 40 20 10When your book has 120 pages, it will be ranked 1: "120" 100 100 50 40 40 20 10
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