'User based' diaporamas de présentation

Data Mining Algorithms for Recommendation Systems

1.95k views • 136 slides

Recommender System

993 views • 77 slides

Intro to RecSys and CCF

Intro to RecSys and CCF. Brian Ackerman. Roadmap. Introduction to Recommender Systems & Collaborative Filtering Collaborative Competitive Filtering. Introduction to Recommender Systems & Collaborative Filtering. Motivation.

631 views • 41 slides

Cisco Unified Communications Licensing Enhancements

Cisco Unified Communications Licensing Enhancements. John Sunzeri, Product Manager June 3, 2010. Agenda. Cisco User Connect Licensing What is it Benefits to you & customers Pricing for Specific Applications Migrating to User Connect Licensing 3 & 3 Upgrade Offer

526 views • 39 slides

Evaluation

Evaluation. The benefits of testing Testing: Expert-based vs user-based Proper technique for conducting a user-based test Effective means of communicating test results. The benefits of testing. User almost always has a choice: Usability sells ,

511 views • 33 slides

Improving Recommendation Lists Through Topic Diversification

Improving Recommendation Lists Through Topic Diversification. CaiNicolas Ziegler, Sean M. McNee, Joseph A. Konstan, Georg Lausen WWW '05 ??? : ???. Outline. Introduction On collaborative filtering Evaluation metrics Topic diversification Empirical analysis Related work Conclusion.

398 views • 29 slides

Recommendations via Collaborative Filtering

377 views • 28 slides

Artificial Intelligence with Web Applications

Artificial Intelligence with Web Applications. Dell Zhang Birkbeck, University of London 2010/11. CI Chapter 2. Making Recommendations. Recommendation Systems. State of the Art. An Ensemble The Neighbourhood Approach User-based Collaborative Filtering

428 views • 27 slides

Majestic MRSS Usability Engineering

Majestic Market Research MRSS firms based in India provides market research services in Automotive Industry, HealthCare & Eye Tracking. We are a member of the European Association of Opinion and Marketing Research Professionals ESOMAR.

663 views • 25 slides

Alliance Solutions Group (ASG)

432 views • 25 slides

Collaborative Filtering

466 views • 21 slides

Designing for Business and Users: Finding the Perfect Blend

Designing for Business and Users: Finding the Perfect Blend. Erin Smith Convergys Corporation Erin.e.smith@convergys.com. Convergys at a Glance. Enabling organizations to enhance the value of their relationships with customers and employees. Solutions and Service Offerings.

348 views • 21 slides

Oct 14, 2013

Recommender systems. acknowledgment: Li Zhang, UCSC. Lirong Xia. Oct 14, 2013. Last time: Judgment aggregation. Doctrinal paradox Axiomatic properties of JA procedures Impossibility theorem Premise-based approaches Distance-based approaches. Today: recommender systems.

315 views • 20 slides

Political Economy and the Choice of Fishery Management Strategies

Political Economy and the Choice of Fishery Management Strategies. Robert T. Deacon University of California, Santa Barbara Resources for the Future World Bank Workshop on Fishery Reform Dhaka, Bangladesh July 2011. Introduction. Trends in world fisheries Widespread biological decline

272 views • 20 slides

???????? ?????? Data availability in China On Physical supply and use tables

???????? ?????? Data availability in China On Physical supply and use tables. Gan H ong China Institute of Water Resources and Hydropower Research. Outline. General. Supply Table. Use Table. Issues. Water statistics related with PSUT in China. General. Annual. Water statistics

277 views • 19 slides

Prediction Modeling for Personalization & Recommender Systems

Prediction Modeling for Personalization & Recommender Systems. Bamshad Mobasher DePaul University. What Is Prediction?. Prediction is similar to classification First, construct a model Second, use model to predict unknown value Prediction is different from classification

295 views • 17 slides

?????? ????? / Collaborative Filtering

?????? ????? / Collaborative Filtering. ?"? ??? ???????. ????? ?? ?????? ??? ?????. Supervised ?? Unsupervised. ????? Unsupervised ?? ???? ?? ? " Objective truth " (??? ??????????) ???? ??? ?????? ??? ??? ?????? ????? ????? ( Click-through ) ??? ????? Correlation

275 views • 14 slides

Workstation-Based Traffic Shaping

Presentation by Mark Meiss ( mmeiss@iu.edu ) January 2002. Workstation-Based Traffic Shaping. Motivation. New peer-to-peer file sharing applications emerge regularly The need for traffic shaping is greater than ever How can we limit peer-to-peer traffic without starving out other traffic?.

265 views • 13 slides

October, 2004

October, 2004. IBM Workplace Services Express Delivering a Collaborative, Team based Portal Capability to Small & Medium Business. Installation and Configuration made Simple Up and Running in a couple of hours Increase End User Productivity

209 views • 10 slides

The 5 Characteristics of Social Networks

151 views • 7 slides