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User Modeling, Adaptation and Personalization

Overview of attention for book
Cover of 'User Modeling, Adaptation and Personalization'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Exploring the Potential of User Modeling Based on Mind Maps
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    Chapter 2 Modeling Motivation in a Social Network Game Using Player-Centric Traits and Personality Traits
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    Chapter 3 Automatic Gaze-Based Detection of Mind Wandering with Metacognitive Awareness
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    Chapter 4 The Value of Social: Comparing Open Student Modeling and Open Social Student Modeling
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    Chapter 5 MENTOR: A Physiologically Controlled Tutoring System
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    Chapter 6 Context-Aware User Modeling Strategies for Journey Plan Recommendation
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    Chapter 7 MOOClm: User Modelling for MOOCs
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    Chapter 8 Dynamic Approaches to Modeling Student Affect and its Changing Role in Learning and Performance
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    Chapter 9 Analyzing and Predicting Privacy Settings in the Social Web
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    Chapter 10 Counteracting Anchoring Effects in Group Decision Making
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    Chapter 11 Gifting as a Novel Mechanism for Personalized Museum and Gallery Interpretation
  13. Altmetric Badge
    Chapter 12 User Modeling, Adaptation and Personalization
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    Chapter 13 A Utility Model for Tailoring Sensor Networks to Users
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    Chapter 14 Towards a Recommender Engine for Personalized Visualizations
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    Chapter 15 Cross-System Transfer of Machine Learned and Knowledge Engineered Models of Gaming the System
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    Chapter 16 MobiScore: Towards Universal Credit Scoring from Mobile Phone Data
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    Chapter 17 Where to Next? A Comparison of Recommendation Strategies for Navigating a Learning Object Repository
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    Chapter 18 Diagrammatic Student Models: Modeling Student Drawing Performance with Deep Learning
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    Chapter 19 Lessons Learned – 15 Years of Delivering Real-World Pedagogically Driven Courses Using Experimental Platforms
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    Chapter 20 Smartphone Based Stress Prediction
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    Chapter 21 Exploiting Implicit Item Relationships for Recommender Systems
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    Chapter 22 The Mars and Venus Effect: The Influence of User Gender on the Effectiveness of Adaptive Task Support
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    Chapter 23 Quiet Eye Affects Action Detection from Gaze More Than Context Length
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    Chapter 24 User Model in a Box: Cross-System User Model Transfer for Resolving Cold Start Problems
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    Chapter 25 Implicit Acquisition of User Personality for Augmenting Movie Recommendations
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    Chapter 26 Harnessing Engagement for Knowledge Creation Acceleration in Collaborative Q&A Systems
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    Chapter 27 News Recommender Based on Rich Feedback
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    Chapter 28 News Recommenders: Real-Time, Real-Life Experiences
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    Chapter 29 On the Use of Cross-Domain User Preferences and Personality Traits in Collaborative Filtering
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    Chapter 30 Understanding Real-Life Website Adaptations by Investigating the Relations Between User Behavior and User Experience
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    Chapter 31 Modelling the User Modelling Community (and Other Communities as Well)
  33. Altmetric Badge
    Chapter 32 Personality Correlates for Digital Concert Program Notes
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    Chapter 33 Integrating Context Similarity with Sparse Linear Recommendation Model
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    Chapter 34 Modeling Motivational States Through Interpreting Physical Activity Data for Adaptive Robot Companions
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    Chapter 35 Privacy-Enhanced Personalisation of Web Search
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    Chapter 36 From Artifact to Content Source: Using Multimodality in Video to Support Personalized Recomposition
  38. Altmetric Badge
    Chapter 37 Exploiting Item and User Relationships for Recommender Systems
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

blogs
1 blog
policy
1 policy source
twitter
7 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
129 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
User Modeling, Adaptation and Personalization
Published by
Lecture notes in computer science, January 2015
DOI 10.1007/978-3-319-20267-9
ISBNs
978-3-31-920266-2, 978-3-31-920267-9
Authors

Francesco Ricci, Kalina Bontcheva, Owen Conlan, Séamus Lawless

Editors

Francesco Ricci, Kalina Bontcheva, Owen Conlan, Séamus Lawless

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 129 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 129 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 33 26%
Student > Master 23 18%
Student > Bachelor 15 12%
Researcher 11 9%
Student > Doctoral Student 8 6%
Other 14 11%
Unknown 25 19%
Readers by discipline Count As %
Computer Science 53 41%
Engineering 13 10%
Psychology 9 7%
Business, Management and Accounting 5 4%
Social Sciences 4 3%
Other 18 14%
Unknown 27 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 April 2023.
All research outputs
#1,719,524
of 23,578,918 outputs
Outputs from Lecture notes in computer science
#283
of 8,153 outputs
Outputs of similar age
#24,739
of 355,973 outputs
Outputs of similar age from Lecture notes in computer science
#21
of 258 outputs
Altmetric has tracked 23,578,918 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,153 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 355,973 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 258 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.