Wednesday, July 9, 2014

Some new and fresh PAPERS from The 37th Annual ACM SIGIR 2014 CONFERENCE

http://sigir.org/sigir2014/finalfullpapers.php

A tag-based personalized item recommendation system using tensor modeling and topic model approaches  Full text: PDFPDF
Gaussian process factorization machines for context-aware recommendations Full text: PDFPDF
Addressing cold start in recommender systems: a semi-supervised co-training algorithm Full text: PDFPDF
Explicit factor models for explainable recommendation based on phrase-level sentiment analysis Full text: PDFPDF
Preference preserving hashing for efficient recommendation Full text: PDFPDF
Load balancing for partition-based similarity search Full text: PDFPDF
Recommending social media content to community owners    Full text: PDFPDF
On measuring social friend interest similarities in recommender systems   Full text: PDFPDF
New and improved: modeling versions to improve app recommendation  Full text: PDFPDF
Detection of abnormal profiles on group attacks in recommender systems    Full text: PDFPDF
Modeling dual role preferences for trust-aware recommendation   Full text: PDFPDF
Group latent factor model for recommendation with multiple user behaviors   Full text: PDFPDF
A revisit to social network-based recommender systems    Full text: PDFPDF
Just-for-me: an adaptive personalization system for location-aware social music recommendation     Full text: PDFPDF
Novelty and diversity enhancement and evaluation in recommender systems and information retrieval   Full text: PDFPDF


What comes after the Social Networking wave?
The Next Big Investment Opportunity on the Internet will be .... Personalization!
Personality Based Recommender Systems and Strict Personality Based Compatibility Matching Engines for serious Online Dating with the normative 16PF5 personality test.



If you want to be first in the "personalization arena" == Personality Based Recommender Systems, you should understand HOW TO INNOVATE in the ............ Online Dating Industry first of all! 

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