PPT-Performance of Recommender Algorithms on Top-N Recommendation Tasks

Author : debby-jeon | Published Date : 2020-01-06

Performance of Recommender Algorithms on TopN Recommendation Tasks Gabriel Vargas Carmona 220612 Agenda Introduction General Overview Recommender system Evaluation

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Performance of Recommender Algorithms on Top-N Recommendation Tasks: Transcript

Performance of Recommender Algorithms on TopN Recommendation Tasks Gabriel Vargas Carmona 220612 Agenda Introduction General Overview Recommender system Evaluation RMSE amp MAE Recall and precision. e-Commerce and Life Style Informatics: . Recommender Systems I. February 4 2013. Geoffrey Fox. gcf@indiana.edu. . . http://. www.infomall.org/X-InformaticsSpring2013/index.html. . Associate Dean for Research and Graduate Studies, School of Informatics and Computing. www.kdd.uncc.edu. CCI, UNC-Charlotte. Research sponsored . by:. p. resented by. Zbigniew. W. Ras. CONSULTING COMPANY in Charlotte. Client 1. Client 2. Client 3. Client 4. Build . Recommender System. Interaction . Effectively, yet . Infrequently, Enables . Programmers to Discover New Tools. Emerson Murphy-Hill. North Carolina State University. Gail Murphy. University of British Columbia. 1. Background. Describing what you know. Contents. What are they and were do we find them?. Why show the algorithm?. What formalisms are used for presenting algorithms?. Notes on notation. Algorithmic performance. Where do we find them. Dietmar. . Jannach. , Markus . Zanker. , Alexander . Felfernig. , Gerhard Friedrich. Cambridge University Press. Which digital camera should I buy. ?. What is the best holiday for me and. my family. Agenda. Online consumer decision making. Introduction. Context effects. Primacy/. recency. effects. Further effects. Personality and social psychology. Discussion and . summary. Literature. Introduction. Hybrid recommender systems. Hybrid: combinations of various inputs and/or composition of different mechanism. Knowledge-based: "Tell me what fits based on my needs". Content-based: "Show me more of the same what I've liked. Danielle Lee . April 20, 2011. Three basic recommendations . Collaborative Filtering. : exploiting other likely-minded community data to derive recommendations. Effective, Novel and Serendipitous recommendations . ManetS. Adeela Huma. 02/02/2017. Introduction - MANETs. MANETs- Mobile ad hoc networks . lacks infrastructure and . central . authority to . establish and . facilitate communication . in the . network. CCI, UNC-Charlotte. Research sponsored by. presented by. Zbigniew. W. Ras. WI’17, Leipzig, Germany. Project Team. Kasia. . Tarnowska. (Warsaw Univ. of . Tech., . Poland. ). Pauline Brunet. (Paris Tech.,. S. OCIAL. N. ETWORKS. Modified from . R. . . Zafarani. , M. A. . Abbasi. , and H. Liu, . Social Networks . Mining: An Introduction. , Cambridge University Press, 2014. . Difficulties of Decision Making. Evaluation. Tokenization and properties of text . Web crawling. Query models. Vector methods. Measures of similarity. Indexing. Inverted files. Basics of internet and web. Spam and SEO. Search engine design. 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. Dr. Sonalika's Eye Clinic in Pune is a top choice for individuals in need of exceptional ophthalmologists and eye clinics. They have multiple convenient locations throughout the city, including Hadapsar, Amanora,

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