PPT-J. Leskovec, D. Huttenlocher, J. Kleinberg

Paper Review by Rachel Katz Signed Networks in Social Media Network Structures Trust network Signed directed relations among users indicating trust or distrust Social network . stanfordedu dph kleinbercscornelledu jurecsstanfordedu ABSTRACT An increasingly common feature of online communities and social media sites is a mechanism for rewarding user achievements based on a system of badges Badges are given to users for part cornelledu larscscornelledu kleinbercscornelledu ABSTRACT Tracking new topics ideas and memes across the Web has been an issue of considerable interest Recent work has developed meth ods for tracking topic shifts over long time scales as well as abru stanfordedu cristianmpiswsorg Abstract Social media systems rely on user feedback and rating mechanisms for personalization ranking and content 64257ltering However when users evaluate content con tributed by fellow users eg by liking a post or votin The study of complex networks has emerged over the past several years as a theme spanning many disciplines ranging from mathematics and computer science to the social and biological sciences A signi64257cant amount of recent work in this area has fo The resilience of networks to various types of failures is an undercurrent in many parts of graph theory and network algorithms In this paper we study the resilience of networks in the presence of cascading failures failures that spread from one no stanfordedu Biomedical Informatics Stanford University plependu nigamstanfordedu ABSTRACT Event sequences such as patients medical histories or users se quences of product reviews trace how individuals progress over time Identifying common patterns o Seitz Daniel P Huttenlocher Cornell University Ithaca NY 14853 USA yulidph cscornelledu Microsoft Research Redmond WA 98052 USA sbkangneel microsoftcom University of Washington Seattle WA 98195 USA seitzcswashingtonedu Abstract In this paper we show Joint work with . Shai. Ben-David. Measures of Clustering Quality: . A Working Set of Axioms for Clustering. Clustering is one of the most widely used . tools for . exploratory data analysis.. . . Joint work with . Shai. Ben-David. Measures of Clustering Quality: . A Working Set of Axioms for Clustering. Clustering is one of the most widely used . tools for . exploratory data analysis.. . . Languages . to Information. Dan Jurafsky. Stanford University. Recommender Systems & Collaborative Filtering. Slides adapted from Jure . Leskovec. Recommender Systems. Customer X. Buys CD of Mozart. Languages . to Information. Dan Jurafsky. Stanford University. Recommender Systems & Collaborative Filtering. Slides adapted from Jure . Leskovec. Recommender Systems. Customer X. Buys CD of Mozart. Ranking Nodes on the Graph. Web pages are not equally “important”. www.joe-schmoe.com. vs. . www.stanford.edu. . Since there is large diversity . in the connectivity of the . web graph we can . 1 Alpers-Huttenlocher syndrome Description Alpers-Huttenlocher syndrome is one of the most severe of a group of conditions called the POLG -related disorders. The conditions in this group feature a Introduction to Recommender Systems. Recommender systems: The task. Customer W. 2. Slides adapted from Jure Leskovec. Plays an Ella Fitzgerald song. What should we recommend next?. Thomas . Quella. Wikimedia Commons.