Graph Mining: Link Prediction. Learn by finding answers to the following questions.<\/p>\n
What is Link Prediction in Graph Mining?<\/p>\n
How can Link Prediction help? and where? can it help in social network, research co-authorship, or spread of disease<\/p>\n
Give uses of Link Prediction in epidemiology or any medical\/biology application?<\/p>\n
Give uses of Link Prediction in Social Network?<\/p>\n
Give uses of Link Prediction in co-authorship?<\/p>\n
What are the steps in Link Prediction? i.e. define link prediction problem.<\/p>\n
Define Link Prediction Problem formally i.e. with Notations i.e. with Graph notations i.e. Graph Representations.<\/p>\n
How is node similarity related in Link Prediction?<\/p>\n
What are possible Node Similarity algorithms that can be used for the purpose?<\/p>\n
Which nodes are the most possible new links? think in terms of Node Similarity Index (Highest, Lowest)<\/p>\n
What are the types of Node Similarity? Node proximity?<\/p>\n
What is Node Similarity based upon? i.e. Network Topology<\/p>\n
What is Local Structure for Node Similarity?<\/p>\n
What is Global Structure for Node Similarity?<\/p>\n
What are examples of Local Structure for Node Similarity?<\/p>\n
What are examples of Global Structure for Node Similarity?<\/p>\n
Define Node Neighborhoods. Is it local or global structure?<\/p>\n
What is Preferential Attachment Index? Is it LocaL or global structure<\/p>\n
What are the types of Node Neighborhoods?<\/p>\n
If two nodes do not have any common node — what is the probable similarity (Node Neigh. aspect)?<\/p>\n
What is Common Neighbors ? Is it local or global structure? is it Node Neighbor or Preferential Attachment? and why?<\/p>\n
What is Jaccard Coefficient ? Is it local or global structure? is it Node Neighbor or Preferential Attachment? and why?<\/p>\n
What is Adamic-Adar? Is it local or global structure? is it Node Neighbor or Preferential Attachment? and why?<\/p>\n
What is the name of the Node Similarity approach where Sum of the inverse logarithmic degree centrality of the neighbors shared by the two nodes are counted?<\/p>\n
What is the name of the Node Similarity approach where the ratio of seize of set intersection to the set union is counted?<\/p>\n
What is the name of the Node Similarity approach where the count of common nodes are used?<\/p>\n
If node similarity score is counted as multiplication of the number\/count of outgoing edges for a node pair. And then the higher results are assumed to create new links. What is this approach called?<\/p>\n
When similarity scores are calculated based on global link structure of graph – what is this called local structure or global structure?<\/p>\n
What is an example of Global Structure?<\/p>\n
What are the examples of Global Structure?<\/p>\n
What is Kartz Index for Global Structure?<\/p>\n
What is Simrank for Global Structure?<\/p>\n
When Node Similarity is calculated as: Sum of count of all paths between node pairs – what is this approach called? Then how is the link prediction made?<\/p>\n
When Node Similarity is calculated as: two nodes are similar if they are referred by similar nodes. What is the name?<\/p>\n
How can you measure if your implemented link prediction algorithm is great or not?<\/p>\n
Can you use train and test concept for the measurement? Can you define the steps\/problems formally? with Graph Notations?<\/p>\n
What are some measures to calculate in the train\/test approach?<\/p>\n
Answers:<\/strong> What is the name of the Node Similarity approach where the ratio of seize of set intersection to the set union is counted? What is the name of the Node Similarity approach where the count of common nodes are used? If node similarity score is counted as multiplication of the number\/count of outgoing edges for a node pair. And then the higher results are assumed to create new links. What is this approach called? What is an example of Global Structure? What are the examples of Global Structure? What are some measures to calculate in the train\/test approach? Resources<\/strong> Similarity Index based Link. Prediction Algorithms in Social Networks: A Survey Proximity-based Methods for Link Prediction Evaluating Link Prediction Methods Link Prediction Algorithm Evaluating link prediction methods By<\/strong><\/p>\n Sayed Ahmed<\/strong><\/p>\n Linkedin<\/strong>: https:\/\/ca.linkedin.com\/in\/sayedjustetc<\/a><\/p>\n Blog<\/strong>: http:\/\/Bangla.SaLearningSchool.com<\/a>, http:\/\/SitesTree.com<\/a> Affiliate Links:<\/strong> Hottest Deals on Amazon CA: http:\/\/tiny.cc\/bgnddz<\/a><\/p>\n
\nWhat is the name of the Node Similarity approach where Sum of the inverse logarithmic degree centrality of the neighbors shared by the two nodes are counted?
\nAns: Adamic-Adar<\/p>\n
\nAns: Jaccard Coefficient<\/p>\n
\nAns: Common Neighbors<\/p>\n
\nAns: Preferential Attachment Index<\/p>\n
\nAns: Path Length > 2<\/p>\n
\nShortest Paths \u2013 use inverse of distance as similarity, Kartz Index, SimRank<\/p>\n
\nAccuracy, F1-score, Sensitivity, Most metrics that would work for classification<\/p>\n
\nLink Prediction
\nhttps:\/\/paperswithcode.com\/task\/link-prediction<\/a><\/p>\n
\nhttps:\/\/pdfs.semanticscholar.org\/8e72\/fa77f3d788f3c67da1e1c6347c3aaf280723.pdf<\/a><\/p>\n
\nhttps:\/\/cran.r-project.org\/web\/packages\/linkprediction\/vignettes\/proxfun.html<\/a><\/p>\n
\nhttps:\/\/arxiv.org\/pdf\/1505.04094.pdf<\/a><\/p>\n
\nhttp:\/\/be.amazd.com\/link-prediction\/<\/a><\/p>\n
\nhttps:\/\/www3.nd.edu\/~dial\/publications\/yang2015evaluating.pdf<\/a><\/p>\n
\nOnline and Offline Training<\/strong>: http:\/\/Training.SitesTree.com<\/a><\/p>\n
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