RecSys 2021 15th ACM Conference on Recommender Systems

 

Amsterdam, Netherlands, 27th September-1st October 2021
https://recsys.acm.org/recsys21/accepted-contributions/#content-tab-1-5-tab

PAPER: RecSys Challenge 2018
https://onlinedatingsoundbarrier.blogspot.com/2018/10/paper-recsys-challenge-2018-playlist.html

best paper RecSys 2011 Conference
https://onlinedatingsoundbarrier.blogspot.com/2011/09/best-paper-recsys-2011-conference.html

 

Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences)
https://onlinedatingsoundbarrier.blogspot.com/2019/05/paper-beyond-personalization-research.html
 
That is the only way to improve recommender systems, to include the personality traits of their users.
http://onlinedatingsoundbarrier.blogspot.com.ar/2017/01/paper-comparative-study-of-people-to_14.html  

They need to calculate personality similarity between users but there are different formulas to calculate similarity.

In case you did not notice: Recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry for years, with low success rates until now because they mostly use the Big Five model to assess personality and the Pearson correlation coefficient to calculate similarity.
Please remember: Personality traits are highly stable in persons over 25 years old to 45 years old. 

The key to long-lasting romance: COMPATIBILITY is exactly STRICT PERSONALITY SIMILARITY and not "meet other people with similar interests or political views".  

Which is the RIGHT approach to innovate in the Personality Based Recommender Systems Arena? 
The same approach to innovate in the Online Dating Industry == 16PF6 test or similar to assess personality traits and a new method to calculate similarity between quantized patterns.
 
Online Dating sites have very big databases, in the range of 20,000,000 (twenty million) profiles, so the Big Five model or the HEXACO model are not enough for predictive purposes. That is why I suggest the 16PF6 test instead and another method to calculate similarity.

Breaking "the online dating sound barrier" is to achieve at least:
3 most compatible persons in a 100,000 persons database.
12 most compatible persons in a 1,000,000 persons database.
48 most compatible persons in a 10,000,000 persons database.
100 times better than Compatibility Matching Algorithms used by actual online dating sites!
High precision in matching algorithms is precisely the key to open the door and leave the infancy of compatibility testing.

Without offering the NORMATIVE 16PF6 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry.   

PAPER: RecSys Challenge 2018: playlist continuation based on

shared neighborhood-methods, matrix factorization and audio-feature classification
https://asciico.de/assets/archive/papers/blauensteiner-metz-advanced-data-challenge-report.pdf
Please see also "about 12th ACM Conference on Recommender Systems"
https://onlinedatingsoundbarrier.blogspot.com/2018/10/about-12th-acm-conference-on.html

and notice Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences)

That is the only way to improve recommender systems, to include the personality traits of their users.
http://onlinedatingsoundbarrier.blogspot.com.ar/2017/01/paper-comparative-study-of-people-to_14.html  

They need to calculate personality similarity between users but there are different formulas to calculate similarity.

In case you did not see, recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry for years, with low success rates until now because they mostly use the Big Five model to assess personality and the Pearson correlation coefficient to calculate similarity.
Please remember: Personality traits are highly stable in persons over 25 years old to 45 years old. 

The key to long-lasting romance: COMPATIBILITY is exactly STRICT PERSONALITY SIMILARITY and not "meet other people with similar interests or political views".  

Which is the RIGHT approach to innovate in the Personality Based Recommender Systems Arena? 
The same approach to innovate in the Online Dating Industry == 16PF5 test or similar to assess personality traits and a new method to calculate similarity between quantized patterns.
Online Dating sites have very big databases, in the range of 20,000,000 (twenty million) profiles, so the Big Five model or the HEXACO model are not enough for predictive purposes. That is why I suggest the 16PF5 test instead and another method to calculate similarity.

High precision in matching algorithms is precisely the key to open the door and leave the infancy of compatibility testing.
Without offering the NORMATIVE 16PF5 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry.
 
WorldWide, there are over 5,000 (five thousand) online dating sites:

- but no one is using the 16PF5 (or similar) to assess personality of its members!

- but no one calculates similarity with a quantized pattern comparison method!

- but no one can show Compatibility Distribution Curves to each and every of its members!!! i.e. if you are a man seeking women, to show how compatible you are with a 20,000,000 women database, and to select a bunch of 100 women from 20,000,000 women database.

- but no one is scientifically proven!  No actual online dating site  is "scientifically proven" because no one can prove its matching algorithm can match prospective partners who will have more stable and satisfying relationships (and very low divorce rates) than couples matched by chance, astrological destiny, personal preferences, searching on one's own, or other technique as the control group in a peer reviewed Scientific Paper for the majority (over 90%) of its members.

The 8 tips to innovate in the Online Dating Industry!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/12/the-8-tips-to-innovate-in-online-dating.html

PAPER Spatial Cascaded Model for Personalized Recommender System

[PDF] PAPER  Spatial Cascaded Model for Personalized Recommender System

Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences)

That is the only way to improve recommender systems, to include the personality traits of their users. They need to calculate personality similarity between users.
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/02/paper-alleviating-new-user-problem-in.html
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/01/paper-using-personality-enhanced-item.html

 

In case you had not noticed, recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry.

Similarity is a word that has different meanings for different persons or companies, it exactly depends on how mathematically is defined.
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/04/paper-hybrid-personalized-recommender.html 

Which is the RIGHT approach to innovate in the Personality Based Recommender Systems Arena?
The same approach to innovate in the Online Dating Industry == 16PF5 test or similar to assess personality traits and a new method to calculate similarity between quantized patterns. 
But that is exactly ............ guess ............. yes ........ LIFEPROJECT METHOD, ready since 2001!
All other proposals are NOISE and perform as placebo.

PAPER: Using Personality Enhanced Item-Based Recommender System for Cold Start

PAPER:[PDF] using personality Enhanced item-based recommender system for cold start

Please see:
PAPER: Birds of a feather ......
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/01/paper-birds-of-feather-locate-together.html

PAPER User Similarity Adjustment for Improved Recommendations http://onlinedatingsoundbarrier.blogspot.com.ar/2016/01/paper-user-similarity-adjustment-for.html

Please remember:
Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences)
That is the only way to improve recommender systems, to include the personality traits of their users. They need to calculate personality similarity between users but there are different formulas to calculate similarity.
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/01/paper-diversity-enhancement-in.html
In case you did not notice, recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry for years, with low success rates!!! because they mostly use the Big 5 to assess personality and the Pearson correlation coefficient to calculate similarity.
Please remember: Personality traits are highly stable in persons over 25 years old to 45 years old.

Online Dating sites OFFERING COMPATIBILITY MATCHING METHODS BASED ON PERSONALITY SIMILARITY have very big databases, in the range of 20,000,000 (twenty million) profiles, so the Big Five model or the HEXACO model are not enough for predictive purposes. That is why I suggest the 16PF5 normative personality test instead.
The same applies for Personality Based Recommender Systems.

Similarity is a word that has different meanings for different persons or companies, it exactly depends on how mathematically is defined.
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/04/paper-hybrid-personalized-recommender.html

Please see: "How to calculate personality similarity between users"
Short answer: the key is the ENSEMBLE!
(the whole set of different valid possibilities)
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/03/how-to-calculate-personality-similarity.html

 
The 8 tips to innovate in the Online Dating Industry!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/12/the-8-tips-to-innovate-in-online-dating.html  

The next wave of innovation!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/06/the-next-wave-of-innovation.html

PAPER CS224W Final Report

Please see:
PAPER User Similarity Adjustment for Improved Recommendations http://onlinedatingsoundbarrier.blogspot.com.ar/2016/01/paper-user-similarity-adjustment-for.html

Please remember:
Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences)
That is the only way to improve recommender systems, to include the personality traits of their users. They need to calculate personality similarity between users but there are different formulas to calculate similarity.
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/01/paper-diversity-enhancement-in.html
In case you did not notice, recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry for years, with low success rates!!! because they mostly use the Big 5 to assess personality and the Pearson correlation coefficient to calculate similarity.
Please remember: Personality traits are highly stable in persons over 25 years old to 45 years old.

Online Dating sites OFFERING COMPATIBILITY MATCHING METHODS BASED ON PERSONALITY SIMILARITY have very big databases, in the range of 20,000,000 (twenty million) profiles, so the Big Five model or the HEXACO model are not enough for predictive purposes. That is why I suggest the 16PF5 normative personality test instead.
The same applies for Personality Based Recommender Systems.

Similarity is a word that has different meanings for different persons or companies, it exactly depends on how mathematically is defined.
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/04/paper-hybrid-personalized-recommender.html

Please see: "How to calculate personality similarity between users"
Short answer: the key is the ENSEMBLE!
(the whole set of different valid possibilities)
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/03/how-to-calculate-personality-similarity.html

 
The 8 tips to innovate in the Online Dating Industry!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/12/the-8-tips-to-innovate-in-online-dating.html  

The next wave of innovation!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/06/the-next-wave-of-innovation.html

PAPER User Similarity Adjustment for Improved Recommendations

http://link.springer.com/chapter/10.1007/978-3-319-26832-3_48

Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences)
That is the only way to improve recommender systems, to include the personality traits of their users. They need to calculate personality similarity between users but there are different formulas to calculate similarity.
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/01/paper-diversity-enhancement-in.html
In case you did not notice, recommender systems are morphing to compatibility matching engines, as the same used in the Online Dating Industry for years, with low success rates!!! because they mostly use the Big 5 to assess personality and the Pearson correlation coefficient to calculate similarity.
Please remember: Personality traits are highly stable in persons over 25 years old to 45 years old.

Online Dating sites OFFERING COMPATIBILITY MATCHING METHODS BASED ON PERSONALITY SIMILARITY have very big databases, in the range of 20,000,000 (twenty million) profiles, so the Big Five model or the HEXACO model are not enough for predictive purposes. That is why I suggest the 16PF5 normative personality test instead.
The same applies for Personality Based Recommender Systems.


Similarity is a word that has different meanings for different persons or companies, it exactly depends on how mathematically is defined.
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/04/paper-hybrid-personalized-recommender.html

Please see: "How to calculate personality similarity between users"
Short answer: the key is the ENSEMBLE!
(the whole set of different valid possibilities)
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/03/how-to-calculate-personality-similarity.html

 Please read also
PAPER Evaluation of Similarity Functions 
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/04/paper-evaluation-of-similarity-functions.html
An exercise of similarity.
How LIFEPROJECT METHOD calculates similarity.
STRICT PERSONALITY SIMILARITY by LIFEPROJECT METHOD.
Personality Distribution Curves using the NORMATIVE 16PF5.
ALGORITHMS & POWER CALCULATION.
Innovations: to take the 16PF5 test 3 times.
Why your brain distorts!
Matching Algorithms for the Online Dating Industry (serious daters)  
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/01/matching-algorithms-for-online-dating.html 
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/02/article-how-dating-companies-are-having.html

paper: DIVERSITY ENHANCEMENT IN COMMUNITY RECOMMENDATION USING TENSOR DECOMPOSITION AND CO-CLUSTERING

DIVERSITY ENHANCEMENT IN COMMUNITY RECOMMENDATION USING TENSOR DECOMPOSITION AND CO-CLUSTERING

Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences).
Please see.

The Netflix Recommender System: Algorithms, Business Value, and Innovation
http://onlinedatingsoundbarrier.blogspot.com.ar/2016/01/the-netflix-recommender-system.html

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

http://onlinedatingsoundbarrier.blogspot.com.ar/2015/12/paper-similarity-scores-evaluation-in.html


 
The 8 tips to innovate in the Online Dating Industry!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/12/the-8-tips-to-innovate-in-online-dating.html  

The next wave of innovation!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/06/the-next-wave-of-innovation.html

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.
Without offering the NORMATIVE16PF5 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry.  

The Netflix Recommender System: Algorithms, Business Value, and Innovation

http://dl.acm.org/citation.cfm?id=2843948


PAPER "Evaluating User's Personality and Social Interactions for Groups Recommendations"
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/12/paper-evaluating-users-personality-and.html


Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences).

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

http://onlinedatingsoundbarrier.blogspot.com.ar/2015/12/paper-similarity-scores-evaluation-in.html


 
The 8 tips to innovate in the Online Dating Industry!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/12/the-8-tips-to-innovate-in-online-dating.html  

The next wave of innovation!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/06/the-next-wave-of-innovation.html

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.
Without offering the NORMATIVE16PF5 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry.  

PAPER "Evaluating User's Personality and Social Interactions for Groups Recommendations"

http://ceur-ws.org/Vol-1533/paper4.pdf

Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences).

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

http://onlinedatingsoundbarrier.blogspot.com.ar/2015/12/paper-similarity-scores-evaluation-in.html


 
The 8 tips to innovate in the Online Dating Industry!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/12/the-8-tips-to-innovate-in-online-dating.html  

The next wave of innovation!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/06/the-next-wave-of-innovation.html
 
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.
Without offering the NORMATIVE16PF5 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry. 

PAPER Similarity Scores Evaluation in Social Networking Sites

Abstract

In today's world, social networking sites are becoming increasingly popular. Often we find suggestions for friends, from such social networking sites. These friend suggestions help us identify friends that we may have lost touch with or new friends that we may want to make. At the same time, these friend suggestions may not be that accurate. To recommend a friend, social networking sites collect information about user's social circle and then build a social network based on this information. This network is then used to recommend to a user, the people he might want to befriend. FoF algorithm is one of the traditional techniques used to recommend friends in a social network. Delta-SimRank is an algorithm used to compute the similarity between objects in a network. This algorithm is also applied on a social network to determine the similarity between users. Here, we evaluate Delta-SimRank and FoF algorithm in terms of the friend suggestion provided by them, when applied on a Facebook dataset. It is observed that Delta-SimRank provides a higher precise similarity score because it considers the entire network around a user.


http://link.springer.com/chapter/10.1007/978-81-322-2674-1_57


See also the paper
User Recommendation Based on Network Structure in Social Networks

Abstract

Advances in Web 2.0 technology has led to the popularity of social networking sites. One fundamental task for social networking sites is to recommend appropriate new friends for users. In recent years, network structure has been used for user recommendation. Most existing network structure-based recommendation methods either need to pre-specify the group number and structure type or fail to improve performance. In this paper, we propose a novel network structure-based user recommendation method, called Bayesian nonparametric mixture matrix factorization (BNPM-MF). The BNPM-MF model first employs a Bayesian nonparametric model to automatically determine the group number and the network structure in networks and then applies a matrix factorization method on each structure to user recommendation for improvement. Experiments conducted on a number of real networks demonstrate that the BNPM-MF model is competitive with other state-of-the-art methods.

http://link.springer.com/chapter/10.1007/978-3-319-26555-1_55

Personality Based Recommender Systems are the next generation of recommender systems because they perform far better than Behavioural ones (past actions and pattern of personal preferences).

If you want to be first in the "personalization arena" == Personality Based Recommender Systems, you should understand the ............ Online Dating Industry first of all!  
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/11/paper-new-similarity-measure-for-user.html
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/10/paper-recommender-systems-supporting.html http://onlinedatingsoundbarrier.blogspot.com.ar/2015/04/paper-evaluation-of-similarity-functions.html

Similarity is a word that has different meanings for different persons or companies, it exactly depends on how mathematically is defined.
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/04/paper-hybrid-personalized-recommender.html

Please see: "How to calculate personality similarity between users"
Short answer: the key is the ENSEMBLE!
(the whole set of different valid possibilities)
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/03/how-to-calculate-personality-similarity.html

 Please read also
PAPER Evaluation of Similarity Functions 
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/04/paper-evaluation-of-similarity-functions.html
An exercise of similarity.
How LIFEPROJECT METHOD calculates similarity.
STRICT PERSONALITY SIMILARITY by LIFEPROJECT METHOD.
Personality Distribution Curves using the NORMATIVE 16PF5.
ALGORITHMS & POWER CALCULATION.
Innovations: to take the 16PF5 test 3 times.
Why your brain distorts!
Matching Algorithms for the Online Dating Industry (serious daters)  
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/01/matching-algorithms-for-online-dating.html 
http://onlinedatingsoundbarrier.blogspot.com.ar/2015/02/article-how-dating-companies-are-having.html
 
The key to long-lasting romance is STRICT PERSONALITY SIMILARITY, but ...
the only way to revolutionize the Online Dating Industry is using the 16PF5 normative personality test, available in different languages to assess personality of members, or a proprietary test with exactly the same traits of the 16PF5 and expressing compatibility with eight decimals (needs a quantized pattern comparison method, part of pattern recognition by cross-correlation, to calculate similarity between prospective mates.)
High precision in matching algorithms is precisely the key to open the door and leave the infancy of compatibility testing.
 
The 8 tips to innovate in the Online Dating Industry!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/12/the-8-tips-to-innovate-in-online-dating.html  

The next wave of innovation!
http://onlinedatingsoundbarrier.blogspot.com.ar/2013/06/the-next-wave-of-innovation.html
 
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.
Without offering the NORMATIVE16PF5 (or similar test measuring exactly the 16 personality factors) for serious dating, it will be impossible to innovate and revolutionize the Online Dating Industry.