Web Search based on Ranking Lecture
Network theory has very many application areas, where graphs are of primary importance, in e.g.,:
-Communication networks
-Epidemiology
-Systems Biology
-Social networks.
Social Media (e.g., Twitter, Facebook, Instagram, to name a few) has had a tremendous growth in the past 20 years. Social Media Analysis has very many applications, e.g.,:
-Recommendation Systems
-Sentiment Analysis
-Information Diffusion
-Web Search.
This lecture overviews Web Search based on Ranking that has many applications in Web Science and Social Media Analytics. It covers the following topics in detail: Architecture of Web Search Engine: Crawler, Indexer, Query Processor. Timeline of Ranking at Indexed Pages. Ranking Algorithms: Based on Frequency (TF-IDF), Based on Graph-Link Analysis (PageRank, Hits, Salsa, UsersRank, SimRank). Neural Networks-based ranking algorithms: Pointwise (Ranking with Large Margin Principles-SVM), Pairwise (SortNet), Listwise (ListNet). Current Neural Networks for Ranking: GEPS, MatchPyramid, C-DSSM, NeuBase. Deep Learning Metrics: Angular Loss, Nearest Neighbors Gaussian Kernels.