PPT-Content Recommendation on Y! sites

Author : min-jolicoeur | Published Date : 2018-11-03

Deepak Agarwal dagarwalyahooinccom Stanford Info Seminar 17 th Feb 2012 Recommend applications Recommend search queries Recommend news article Recommend packages

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Content Recommendation on Y! sites: Transcript

Deepak Agarwal dagarwalyahooinccom Stanford Info Seminar 17 th Feb 2012 Recommend applications Recommend search queries Recommend news article Recommend packages Image Title summary. By Jake Sheehan. Nick Saltzman . What is the invisible web?. All information that cannot be indexed using general web search engines. Also known as the deep internet, deepnet, or the hidden web. Search Engines. Content-based recommendation. While CF – methods do not require any information about the items,. it might be reasonable to exploit such information; and. recommend fantasy novels to people who liked fantasy novels in the past. starT-ups. in the business of journalism. Association for Education in Journalism and Mass Communications,. Chicago, Aug. 11, 2012. Sponsors: . Community Journalism Interest Group. . (ComJIG). a. nd. Content-based recommendation. While CF – methods do not require any information about the items,. it might be reasonable to exploit such information; and. recommend fantasy novels to people who liked fantasy novels in the past. Communicating & Sharing: The Social Web. Visualizing Technology. Copyright © 2014 Pearson Education, Inc. Publishing as Prentice Hall. Objectives. Compare different forms of synchronous online communication.. Kinan Halloum . 1. Presented paper. 2. Deep content-based music recommendation . by van den Oord et al. NIPS 2013. Outline. Music Recommendation. Collaborative filtering. Weighted Matrix Factorization. Ranking by Internet Genre. P2 . Source: VAB analysis . of Media Metrix multi-platform comScore data. , July 2017 (Ranking based on “Total Minutes Viewed”). Genre. Rank:. Top Traffic . TV Sites:. Ranking by Internet Genre. P2 . Source: VAB analysis . of Media Metrix multi-platform comScore data. , March 2017 (Ranking based on “Total Minutes Viewed”). Genre. Rank:. Top Traffic . TV Sites:. Design . for the context of use. Design for the user experience. Design for balancing simplicity and . enrichment. In this presentation – there are purple slides titled “your turn”. Please do those with your team and hand in the team’s report in D2L folder called Sept 20.. and. Content Theft & Malware . Investigative Findings. 30%. 11.8. MILLION. U.S. users exposed to malware each month by sites in the sample content theft group. 1 in 3 content theft sites exposed users to malware . Visualizing Technology. Copyright © 2014 Pearson Education, Inc. Publishing as Prentice Hall. Objectives. Compare different forms of synchronous online communication.. Demonstrate how to use email effectively.. Web 3.0 update eCircle SLC Emerging Entrepreneurs Topics Google Panda Google Push into Social / +1 Keyword Targeted Domain Name Dropping Changes in Google Local Search Linked in Social - New Apps Facebook IN. P2P OSN. By . Keerthi Nelaturu. Challenges with current Social Networks. Personal data left with Service Provider even when Social graph is . removed. Control of the User-generated content with Service Provider . digital business strategy with MagnoliaPERI has built a globalized digital business strategy on Magnolia which powers more than 50 sites in over 30 languagesPeri Case StudyBuilding a solid digital bus

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