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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 Social Computers for the Social Animal: State-of-the-Art and Future Perspectives of Social Signal Processing
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    Chapter 2 Thinking Outside the (Search) Box
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    Chapter 3 Challenges for the Multi-dimensional Personalised Web
  5. Altmetric Badge
    Chapter 4 Modeling User Affect from Causes and Effects
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    Chapter 5 Evaluating Web Based Instructional Models Using Association Rule Mining
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    Chapter 6 Sensors Model Student Self Concept in the Classroom
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    Chapter 7 Use and Trust of Simple Independent Open Learner Models to Support Learning within and across Courses
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    Chapter 8 Narcissus: Group and Individual Models to Support Small Group Work
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    Chapter 9 Social Navigation Support for Information Seeking: If You Build It, Will They Come?
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    Chapter 10 Performance Evaluation of a Privacy-Enhancing Framework for Personalized Websites
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    Chapter 11 Creating User Profiles from a Command-Line Interface: A Statistical Approach
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    Chapter 12 Context-Aware Preference Model Based on a Study of Difference between Real and Supposed Situation Data
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    Chapter 13 Modeling the Personality of Participants During Group Interactions
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    Chapter 14 Predicting Customer Models Using Behavior-Based Features in Shops
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    Chapter 15 Investigating the Utility of Eye-Tracking Information on Affect and Reasoning for User Modeling
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    Chapter 16 Describing User Interactions in Adaptive Interactive Systems
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    Chapter 17 PerspectiveSpace: Opinion Modeling with Dimensionality Reduction
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    Chapter 18 Recognition of User Intentions for Interface Agents with Variable Order Markov Models
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    Chapter 19 Tell Me Where You’ve Lived, and I’ll Tell You What You Like: Adapting Interfaces to Cultural Preferences
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    Chapter 20 Non-intrusive Personalisation of the Museum Experience
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    Chapter 21 Assessing the Impact of Measurement Uncertainty on User Models in Spatial Domains
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    Chapter 22 SoNARS: A Social Networks-Based Algorithm for Social Recommender Systems
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    Chapter 23 Grocery Product Recommendations from Natural Language Inputs
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    Chapter 24 I Like It... I Like It Not: Evaluating User Ratings Noise in Recommender Systems
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    Chapter 25 Evaluating Interface Variants on Personality Acquisition for Recommender Systems
  27. Altmetric Badge
    Chapter 26 Context-Dependent Personalised Feedback Prioritisation in Exploratory Learning for Mathematical Generalisation
  28. Altmetric Badge
    Chapter 27 Google Shared. A Case-Study in Social Search
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    Chapter 28 Collaborative Filtering Is Not Enough? Experiments with a Mixed-Model Recommender for Leisure Activities
  30. Altmetric Badge
    Chapter 29 Enhancing Mobile Recommender Systems with Activity Inference
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    Chapter 30 Customer’s Relationship Segmentation Driving the Predictive Modeling for Bad Debt Events
  32. Altmetric Badge
    Chapter 31 Supporting Personalized User Concept Spaces and Recommendations for a Publication Sharing System
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    Chapter 32 Evaluating the Adaptation of a Learning System before the Prototype Is Ready: A Paper-Based Lab Study
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    Chapter 33 Capturing the User’s Reading Context for Tailoring Summaries
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    Chapter 34 History Dependent Recommender Systems Based on Partial Matching
  36. Altmetric Badge
    Chapter 35 Capturing User Intent for Analytic Process
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    Chapter 36 What Have the Neighbours Ever Done for Us? A Collaborative Filtering Perspective
  38. Altmetric Badge
    Chapter 37 Investigating the Possibility of Adaptation and Personalization in Virtual Environments
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    Chapter 38 Detecting Guessed and Random Learners’ Answers through Their Brainwaves
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    Chapter 39 Just-in-Time Adaptivity through Dynamic Items
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    Chapter 40 Collaborative Semantic Tagging of Web Resources on the Basis of Individual Knowledge Networks
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    Chapter 41 Working Memory Differences in E-Learning Environments: Optimization of Learners’ Performance through Personalization
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    Chapter 42 Semantic Web Usage Mining: Using Semantics to Understand User Intentions
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    Chapter 43 Adaptive Tips for Helping Domain Experts
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    Chapter 44 On User Modelling for Personalised News Video Recommendation
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    Chapter 45 A Model of Temporally Changing User Behaviors in a Deployed Spoken Dialogue System
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    Chapter 46 Recognition of Users’ Activities Using Constraint Satisfaction
  48. Altmetric Badge
    Chapter 47 Reinforcing Recommendation Using Implicit Negative Feedback
  49. Altmetric Badge
    Chapter 48 Evaluating Three Scrutability and Three Privacy User Privileges for a Scrutable User Modelling Infrastructure
  50. Altmetric Badge
    Chapter 49 User Modeling of Disabled Persons for Generating Instructions to Medical First Responders
  51. Altmetric Badge
    Chapter 50 Filtering Fitness Trail Content Generated by Mobile Users
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    Chapter 51 Adaptive Clustering of Search Results
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    Chapter 52 What Do Academic Users Really Want from an Adaptive Learning System?
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    Chapter 53 How Users Perceive and Appraise Personalized Recommendations
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    Chapter 54 Towards Web Usability: Providing Web Contents According to the Readers Contexts
  56. Altmetric Badge
    Chapter 55 Plan Recognition of Movement
  57. Altmetric Badge
    Chapter 56 Personalised Web Experiences: Seamless Adaptivity across Web Service Composition and Web Content
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 (80th percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
1 X user
patent
1 patent
facebook
1 Facebook page
wikipedia
1 Wikipedia page

Readers on

mendeley
2676 Mendeley
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Title
User Modeling, Adaptation, and Personalization
Published by
ADS, June 2009
DOI 10.1007/978-3-642-02247-0
ISBNs
978-3-64-202246-3, 978-3-64-202247-0
Editors

Houben, Geert-Jan, McCalla, Gord, Pianesi, Fabio, Zancanaro, Massimo

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 2,676 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2676 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 <1%
Student > Master 1 <1%
Professor 1 <1%
Unknown 2672 100%
Readers by discipline Count As %
Computer Science 3 <1%
Biochemistry, Genetics and Molecular Biology 1 <1%
Unknown 2672 100%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 20 October 2020.
All research outputs
#5,310,838
of 26,017,215 outputs
Outputs from ADS
#3,535
of 27,022 outputs
Outputs of similar age
#23,383
of 130,996 outputs
Outputs of similar age from ADS
#43
of 251 outputs
Altmetric has tracked 26,017,215 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 27,022 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 well, scoring higher than 85% 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 130,996 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 80% of its contemporaries.
We're also able to compare this research output to 251 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 82% of its contemporaries.