A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law Distribution
In recent years, streaming music platforms have become very popular mainly due to the huge number of songs these systems make available to users. This enormous availability means that recommendation mechanisms that help users to select the music they like need to be incorporated. However, developing...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2020-01-01
|
| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/7309453 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850225822869225472 |
|---|---|
| author | Diego Sánchez-Moreno Vivian F. López Batista M. Dolores Muñoz Vicente Ana B. Gil González María N. Moreno-García |
| author_facet | Diego Sánchez-Moreno Vivian F. López Batista M. Dolores Muñoz Vicente Ana B. Gil González María N. Moreno-García |
| author_sort | Diego Sánchez-Moreno |
| collection | DOAJ |
| description | In recent years, streaming music platforms have become very popular mainly due to the huge number of songs these systems make available to users. This enormous availability means that recommendation mechanisms that help users to select the music they like need to be incorporated. However, developing reliable recommender systems in the music field involves dealing with many problems, some of which are generic and widely studied in the literature while others are specific to this application domain and are therefore less well-known. This work is focused on two important issues that have not received much attention: managing gray-sheep users and obtaining implicit ratings. The first one is usually addressed by resorting to content information that is often difficult to obtain. The other drawback is related to the sparsity problem that arises when there are obstacles to gather explicit ratings. In this work, the referred shortcomings are addressed by means of a recommendation approach based on the users’ streaming sessions. The method is aimed at managing the well-known power-law probability distribution representing the listening behavior of users. This proposal improves the recommendation reliability of collaborative filtering methods while reducing the complexity of the procedures used so far to deal with the gray-sheep problem. |
| format | Article |
| id | doaj-art-5b8fc8152a3945918499df816d092cc0 |
| institution | OA Journals |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-5b8fc8152a3945918499df816d092cc02025-08-20T02:05:13ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/73094537309453A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law DistributionDiego Sánchez-Moreno0Vivian F. López Batista1M. Dolores Muñoz Vicente2Ana B. Gil González3María N. Moreno-García4Department of Computing and Automation, University of Salamanca, Salamanca 37008, SpainDepartment of Computing and Automation, University of Salamanca, Salamanca 37008, SpainDepartment of Computing and Automation, University of Salamanca, Salamanca 37008, SpainDepartment of Computing and Automation, University of Salamanca, Salamanca 37008, SpainDepartment of Computing and Automation, University of Salamanca, Salamanca 37008, SpainIn recent years, streaming music platforms have become very popular mainly due to the huge number of songs these systems make available to users. This enormous availability means that recommendation mechanisms that help users to select the music they like need to be incorporated. However, developing reliable recommender systems in the music field involves dealing with many problems, some of which are generic and widely studied in the literature while others are specific to this application domain and are therefore less well-known. This work is focused on two important issues that have not received much attention: managing gray-sheep users and obtaining implicit ratings. The first one is usually addressed by resorting to content information that is often difficult to obtain. The other drawback is related to the sparsity problem that arises when there are obstacles to gather explicit ratings. In this work, the referred shortcomings are addressed by means of a recommendation approach based on the users’ streaming sessions. The method is aimed at managing the well-known power-law probability distribution representing the listening behavior of users. This proposal improves the recommendation reliability of collaborative filtering methods while reducing the complexity of the procedures used so far to deal with the gray-sheep problem.http://dx.doi.org/10.1155/2020/7309453 |
| spellingShingle | Diego Sánchez-Moreno Vivian F. López Batista M. Dolores Muñoz Vicente Ana B. Gil González María N. Moreno-García A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law Distribution Complexity |
| title | A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law Distribution |
| title_full | A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law Distribution |
| title_fullStr | A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law Distribution |
| title_full_unstemmed | A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law Distribution |
| title_short | A Session-Based Song Recommendation Approach Involving User Characterization along the Play Power-Law Distribution |
| title_sort | session based song recommendation approach involving user characterization along the play power law distribution |
| url | http://dx.doi.org/10.1155/2020/7309453 |
| work_keys_str_mv | AT diegosanchezmoreno asessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution AT vivianflopezbatista asessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution AT mdoloresmunozvicente asessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution AT anabgilgonzalez asessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution AT marianmorenogarcia asessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution AT diegosanchezmoreno sessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution AT vivianflopezbatista sessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution AT mdoloresmunozvicente sessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution AT anabgilgonzalez sessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution AT marianmorenogarcia sessionbasedsongrecommendationapproachinvolvingusercharacterizationalongtheplaypowerlawdistribution |