NDLI: User Perception of Next-Track Music Recommendations

Please wait, while we are loading the content...

After Twenty-Five Years of User Modeling and Adaptation...What Makes us UMAP?

Nudge your Workforce: A Study on the Effectiveness of Task Notification Strategies in Enterprise Mobile Crowdsourcing

Interactive Prior Elicitation of Feature Similarities for Small Sample Size Prediction

Towards Improving E-commerce Users Experience Using Personalization & Persuasive Technology

Recommender Systems as Multistakeholder Environments

I'll be Watching You: Policing the Line between Personalization and Privacy

Long and Short-Term Recommendations with Recurrent Neural Networks

An Analysis on Time- and Session-aware Diversification in Recommender Systems

Analyzing the Impact of Social Connections on Rating Behavior in Social Recommender Systems

Towards Understanding Users' Motivation in a Q&A Social Network Using Social Influence and the Moderation by Culture

Emotion Analysis in Natural Language

Using Learning Analytics to Devise Interactive Personalised Nudges for Active Video Watching

Deriving Item Features Relevance from Past User Interactions

Personalized Research Paper Recommendation using Deep Learning

Harvesting Entity-relation Social Networks from the Web: Potential and Challenges

A Multi-Armed Bandit Model Selection for Cold-Start User Recommendation

A Clustering Approach for Personalizing Diversity in Collaborative Recommender Systems

Conversational Group Recommender Systems

Enhancing Collaborative Filtering with Friendship Information

Fine-Grained Open Learner Models: Complexity Versus Support

Personality Traits and Music Genres: What Do People Prefer to Listen To?

Smart Technology for Supporting Dance Education

Combining Supervised and Unsupervised Learning to Discover Emotional Classes

Where To Go Next?: Exploiting Behavioral User Models in Smart Environments

Improving Cold Start Recommendation by Mapping Feature-Based Preferences to Item Comparisons

Harnessing Virtual Reality Exergames and Physical Fitness Sensing to Create a Personalised Game and Dashboard

The Adaptation of an Individual's Satisfaction to Group Context: the Role of Ties Strength and Conflicts

A New Statistical Density Clustering Algorithm based on Mutual Vote and Subjective Logic Applied to Recommender Systems

The Force Within: Recommendations Via Gravitational Attraction Between Items

Modelling User Behaviour based on Process

The Influence of City Size on Dietary Choices and Food Recommendation

RouteMe: A Mobile Recommender System for Personalized, Multi-Modal Route Planning

Encoding User as More Than the Sum of Their Parts: Recurrent Neural Networks and Word Embedding for People-to-people Recommendation

Behavioral Patterns Mining for Online Time Personalization

Stereotype Modeling for Problem-Solving Performance Predictions in MOOCs and Traditional Courses

Multilingual Search User Behaviors -- Exploring Multilingual Querying and Result Selection Through Crowdsourcing

Modeling the Dynamics of Online News Reading Interests

Learner Modeling for Integration Skills

Modelling Embodied Mobility Teamwork Strategies in a Simulation-Based Healthcare Classroom

User Verification on Mobile Devices Using Sequences of Touch Gestures

"Out of the Fr-Eye-ing Pan": Towards Gaze-Based Models of Attention during Learning with Technology in the Classroom

Providing Control and Transparency in a Social Recommender System for Academic Conferences

User Modeling for the Internet of Things

Probabilistic Perspectives on Collecting Human Uncertainty in Predictive Data Mining

Impact of Individual Differences on User Experience with a Real-World Visualization Interface for Public Engagement

User Perception of Next-Track Music Recommendations

Are Item Attributes a Good Alternative to Context Elicitation in Recommender Systems?

"Personal Social Dashboard": A Tool for Measuring Your Social Engagement Effectiveness in the Enterprise

Item Contents Good, User Tags Better: Empirical Evaluation of a Food Recommender System

Adaptive City Characteristics: How Location Familiarity Changes What Is Regionally Descriptive

A Hybrid Recommendation Framework Exploiting Linked Open Data and Graph-based Features

Investigating the Impact of Personality and Cognitive Efficiency on the Selection of Exercises for Learners

Combining Long-term and Discussion-generated Preferences in Group Recommendations

Imputing KCs with Representations of Problem Content and Context

Evaluation of Learners' Adjustment of Question Difficulty in Adaptive Practice of Facts

Experimental Analysis of Mastery Learning Criteria

An Evaluation of Learning-to-Rank Methods for Lurking Behavior Analysis

Using Eye Gaze Data and Visual Activities to Infer Human Cognitive Styles: Method and Feasibility Studies

Learning Inclination to Empathy from Social Media Footprints

Group Recommendations by Learning Rating Behavior

Using System Dynamics to Model Student Performance in an Intelligent Tutoring System

Let's Dance: How to Build a User Model for Dance Students Using Wearable Technology

Measuring Bias in News Websites, Towards a Model for Personalization

Enhancing Student Models in Game-based Learning with Facial Expression Recognition

A Unified Latent Factor Model for Effective Category-Aware Recommendation

A Deep Architecture for Content-based Recommendations Exploiting Recurrent Neural Networks

Sequences of Diverse Song Recommendations: An Exploratory Study in a Commercial System

Measuring Student Behaviour Dynamics in a Large Interactive Classroom Setting

A Personalized Global Filter To Predict Retweets

Inferring Contextual Preferences Using Deep Auto-Encoding

User Expertise Inference on Twitter: Learning from Multiple Types of User Data

Weighted Random Walk Sampling for Multi-Relational Recommendation

A Neural Time Series Forecasting Model for User Interests Prediction On Twitter

Inferring Students' Sense of Community from Their Communication Behavior in Online Courses

Indirect Context Suggestion

Towards a Long Term Model of Virtual Reality Exergame Exertion

Get to the Bottom: Causal Analysis for User Modeling

User Perception of Next-Track Music Recommendations

Content Provider	ACM Digital Library
Author	Kamehkhosh, Iman Jannach, Dietmar
Abstract	Many of today's music streaming websites and apps provide personalized next-track listening recommendations based on the user's current and past listening behavior. In the research literature, various algorithmic approaches to determine suitable next tracks can be found. However, almost all of them were evaluated in offline experiments using, for example, manually created playlists as a gold standard. In this work, we aim to check the external validity of insights that are obtained through such offline experiments on historical datasets. We conducted an online user study involving 277 subjects in which the participants evaluated the suitability of four different alternatives of continuing a given set of playlists. Our results indicate that manually created playlists can in fact represent a reasonable gold standard, an insight for which no evidence existed in the literature before. Furthermore, our work was able to confirm that considering playlist homogeneity aspects does not only lead to performance improvements in offline experiments -- as indicated by past research -- but also to a better quality perception by users. However, the observations also revealed that user studies of this type can be easily distorted by item familiarity biases, because the participants tend to evaluate continuation alternatives better when they know the track or the artist.
Starting Page	113
Ending Page	121
Page Count	9
File Format	PDF
ISBN	9781450346351
DOI	10.1145/3079628.3079668
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2017-07-09
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Music recommendation Offline-online comparison User study Perceived quality Recommender systems
Content Type	Text
Resource Type	Article

Central Library (ISO-9001:2015 Certified)
Indian Institute of Technology Kharagpur
Kharagpur, West Bengal, India | PIN - 721302

See location in the Map
03222 282435
Mail: support@ndl.gov.in

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in