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Rescooped by Michelle Robinson from Tracking the Future
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Brainlike Computers, Learning From Experience

Brainlike Computers, Learning From Experience | Search & Discovery | Scoop.it

Computers have entered the age when they are able to learn from their own mistakes, a development that is about to turn the digital world on its head.


Via Szabolcs Kósa
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VendorFit's curator insight, December 31, 2013 3:27 PM

Artificial intelligence is the holy grail of technological achievment, creating an entity that can learn from its own mistakes and can (independently of programmer intervention) develop new routines and programs.  The New York Times claims that the first ever "learning" computer chip is to be released in 2014, an innovation that has profound consequences for the tech market.  When these devices become cheaper, this should allow for robotics and device manufacture that incorporates more detailed sensory input and can parse real objects, like faces, from background noise. 

Laura E. Mirian, PhD's curator insight, January 10, 2014 1:16 PM

The Singularity is not far away

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StyleSpotter Launches Social Discovery Engine for Fashion on iPad - PR Newswire (press release)

StyleSpotter Launches Social Discovery Engine for Fashion on iPad - PR Newswire (press release) | Search & Discovery | Scoop.it
StyleSpotter Launches Social Discovery Engine for Fashion on iPad PR Newswire (press release) The company has developed powerful tagging, filtering and search algorithms designed to make it easier to find, compare and browse fashion items from...
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Demand for Online Content Drives the Market for Multiscreen Content Discovery ... - PR Web (press release)

Demand for Online Content Drives the Market for Multiscreen Content Discovery ... - PR Web (press release) | Search & Discovery | Scoop.it
Demand for Online Content Drives the Market for Multiscreen Content Discovery ...
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recommendationRaccoon

recommendationRaccoon | Search & Discovery | Scoop.it
recommendationRaccoon - A collaborative filtering based recommendation engine and NPM module built on top of Node.js and Redis.
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Rescooped by Michelle Robinson from artificial intelligence for students
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ScienceDirect.com - Knowledge-Based Systems - Improving collaborative filtering recommender system results and performance using genetic algorithms

ScienceDirect.com - Knowledge-Based Systems - Improving collaborative filtering recommender system results and performance using genetic algorithms | Search & Discovery | Scoop.it
Improving collaborative filtering recommender system results and performance using genetic algorithms http://t.co/1RJvdR2eAS
#orj #GAS

Via Scott Turner
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Building Search Driven Solution with SharePoint 2013 Part I

Building Search Driven Solution with SharePoint 2013 Part I This video is the Hands on System demo depending to the blog post under: http://nbsharepointtalk....
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5 Social Media Advertising Trends to Watch for in 2014 - Search Engine Watch

5 Social Media Advertising Trends to Watch for in 2014 - Search Engine Watch | Search & Discovery | Scoop.it
5 Social Media Advertising Trends to Watch for in 2014
Search Engine Watch
Social media advertising is what traditional search engine marketing was 5 years ago: constantly in development with major changes coming every other week.
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Apple Buys Tech Company Co-Founded By Two Indo- Americans For $200 Million - South Asian Link

Apple Buys Tech Company Co-Founded By Two Indo- Americans For $200 Million - South Asian Link | Search & Discovery | Scoop.it
South Asian Link Apple Buys Tech Company Co-Founded By Two Indo- Americans For $200 Million South Asian Link According to Topsy's website,chief technology officerPrakash is a pioneer in the fieldof collaborative filtering.In 2001, Prakash...
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One-class Collaborative Filtering with Random Graphs - arXiv

In this paper we present a novel Bayesian generative model for implicit collaborative filtering. It forms a core component of the Xbox Live architecture, and unlike previous approaches, delineates the odds of a user disliking an ...
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Similarity Functions for User-User Collaborative Filtering | GroupLens

Typically, user-user collaborative filtering has used Pearson correlation to compare users. Early work tried Spearman correlation and (raw) cosine similarity, but found Pearson to work better, and the issue wasn't revisited for ...
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IU X-Informatics Unit 12: Lesson 2: Recommender Systems Introduction

Lesson Overview: We give a general discussion of recommender systems and point out that they are particularly valuable in long tail of tems (to be recommende...
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Rescooped by Michelle Robinson from WooCommerce Extensions Nulled Download
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Woocommerce Recommendation Engine | Download Free Full Scripts

Woocommerce Recommendation Engine | Download Free Full Scripts | Search & Discovery | Scoop.it
Offer Product Recommendations to Customers WooCommerce Recommendation Engine will allow you to configure Netflix and Amazon style product suggestions for your customers.

Via Marvin Doster
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ElasticSearch in Production: lessons learned

Presentation slides available here: http://www.lucenerevolution.org/past_events With Proquest Udini, we have created the worlds largest online article store,...
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Sharepoint 2013 Search Ranking and Relevancy Part 1: Let's compare to FS14

Sharepoint 2013 Search Ranking and Relevancy Part 1:  Let's compare to FS14 | Search & Discovery | Scoop.it
I’m very happy to do some “guest” blogging for my good friend Leo and continue diving into various search-related topics.  In this and upcoming posts, I’d like to jump right into something that int...
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