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User Modeling, Adaption, and Personalization

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

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Opinion-Driven Matrix Factorization for Rating Prediction
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    Chapter 2 Interaction Based Content Recommendation in Online Communities
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    Chapter 3 User Modeling, Adaptation, and Personalization
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    Chapter 4 A Framework for Trust-Based Multidisciplinary Team Recommendation
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    Chapter 5 Semantic Aggregation and Zooming of User Viewpoints in Social Media Content
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    Chapter 6 Learning Likely Locations
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    Chapter 7 User Modeling, Adaptation, and Personalization
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    Chapter 8 Days of Our Lives: Assessing Day Similarity from Location Traces
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    Chapter 9 Studying the Effect of Human Cognition on User Authentication Tasks
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    Chapter 10 Modeling a Graph Viewer’s Effort in Recognizing Messages Conveyed by Grouped Bar Charts
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    Chapter 11 Evaluation of Attention Levels in a Tetris Game Using a Brain Computer Interface
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    Chapter 12 Monitoring Personal Safety by Unobtrusively Detecting Unusual Periods of Inactivity
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    Chapter 13 Recommendation with Differential Context Weighting
  15. Altmetric Badge
    Chapter 14 Exploiting the Semantic Similarity of Contextual Situations for Pre-filtering Recommendation
  16. Altmetric Badge
    Chapter 15 Combining Collaborative Filtering and Text Similarity for Expert Profile Recommendations in Social Websites
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    Chapter 16 Adapting Recommendation Diversity to Openness to Experience: A Study of Human Behaviour
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    Chapter 17 Predicting Successful Inquiry Learning in a Virtual Performance Assessment for Science
  19. Altmetric Badge
    Chapter 18 Comparing and Combining Eye Gaze and Interface Actions for Determining User Learning with an Interactive Simulation
  20. Altmetric Badge
    Chapter 19 Utilizing Dynamic Bayes Nets to Improve Early Prediction Models of Self-regulated Learning
  21. Altmetric Badge
    Chapter 20 Recommending Topics for Web Curation
  22. Altmetric Badge
    Chapter 21 Building Rich User Search Queries Profiles
  23. Altmetric Badge
    Chapter 22 Inform or Flood: Estimating When Retweets Duplicate
  24. Altmetric Badge
    Chapter 23 Predicting Users’ Preference from Tag Relevance
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    Chapter 24 Recommendation for New Users with Partial Preferences by Integrating Product Reviews with Static Specifications
  26. Altmetric Badge
    Chapter 25 User Modeling, Adaptation, and Personalization
  27. Altmetric Badge
    Chapter 26 Personalized Access to Scientific Publications: from Recommendation to Explanation
  28. Altmetric Badge
    Chapter 27 PoliSpell: An Adaptive Spellchecker and Predictor for People with Dyslexia
  29. Altmetric Badge
    Chapter 28 A Framework for Privacy-Aware User Data Trading
  30. Altmetric Badge
    Chapter 29 Understanding Email Writers: Personality Prediction from Email Messages
  31. Altmetric Badge
    Chapter 30 Modeling Emotions with Social Tags
  32. Altmetric Badge
    Chapter 31 Unobtrusive Monitoring of Knowledge Workers for Stress Self-regulation
  33. Altmetric Badge
    Chapter 32 Topolor: A Social Personalized Adaptive E-Learning System
  34. Altmetric Badge
    Chapter 33 RES: A Personalized Filtering Tool for CiteSeerX Queries Based on Keyphrase Extraction
  35. Altmetric Badge
    Chapter 34 Generating a Personalized UI for the Car: A User-Adaptive Rendering Architecture
  36. Altmetric Badge
    Chapter 35 Eliciting Affective Recommendations to Support Distance Learning Students
  37. Altmetric Badge
    Chapter 36 Leveraging Encyclopedic Knowledge for Transparent and Serendipitous User Profiles
  38. Altmetric Badge
    Chapter 37 Modelling Users’ Affect in Job Interviews: Technological Demo
  39. Altmetric Badge
    Chapter 38 Multilingual vs. Monolingual User Models for Personalized Multilingual Information Retrieval
  40. Altmetric Badge
    Chapter 39 A Prismatic Cognitive Layout for Adapting Ontologies
  41. Altmetric Badge
    Chapter 40 Evaluation of Cross-Domain News Article Recommendations
  42. Altmetric Badge
    Chapter 41 Suggesting Query Revisions in Conversational Recommender Systems
  43. Altmetric Badge
    Chapter 42 Mining Semantic Data, User Generated Contents, and Contextual Information for Cross-Domain Recommendation
  44. Altmetric Badge
    Chapter 43 A POV-Based User Model: From Learning Preferences to Learning Personal Ontologies
  45. Altmetric Badge
    Chapter 44 Design and Evaluation of an Affective BCI-Based Adaptive User Application: A Preliminary Case Study
  46. Altmetric Badge
    Chapter 45 Inclusive Personalized e-Learning Based on Affective Adaptive Support
  47. Altmetric Badge
    Chapter 46 Tabbed Browsing Behavior as a Source for User Modeling
  48. Altmetric Badge
    Chapter 47 Grasping the Long Tail: Personalized Search for Cultural Heritage Annotators
  49. Altmetric Badge
    Chapter 48 Enforcing Privacy in Secondary User Information Sharing and Usage
  50. Altmetric Badge
    Chapter 49 Modeling Programming Skills of Students in an Educational Recommender System
  51. Altmetric Badge
    Chapter 50 Socially Adaptive Electronic Partners for Socio-geographical Support
  52. Altmetric Badge
    Chapter 51 An Adaptive Spellchecker and Predictor for People with Dyslexia
Attention for Chapter 28: A Framework for Privacy-Aware User Data Trading
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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 (90th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
2 news outlets

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
16 Mendeley
citeulike
1 CiteULike
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Chapter title
A Framework for Privacy-Aware User Data Trading
Chapter number 28
Book title
User Modeling, Adaptation, and Personalization
Published in
Lecture notes in computer science, June 2013
DOI 10.1007/978-3-642-38844-6_28
Book ISBNs
978-3-64-238843-9, 978-3-64-238844-6
Authors

Johnson Iyilade, Julita Vassileva

Editors

Sandra Carberry, Stephan Weibelzahl, Alessandro Micarelli, Giovanni Semeraro

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 38%
Researcher 3 19%
Professor 2 13%
Student > Bachelor 2 13%
Student > Master 1 6%
Other 1 6%
Unknown 1 6%
Readers by discipline Count As %
Computer Science 9 56%
Engineering 3 19%
Environmental Science 1 6%
Unknown 3 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 15. 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 16 January 2019.
All research outputs
#2,014,883
of 22,947,506 outputs
Outputs from Lecture notes in computer science
#375
of 8,133 outputs
Outputs of similar age
#18,117
of 198,032 outputs
Outputs of similar age from Lecture notes in computer science
#6
of 126 outputs
Altmetric has tracked 22,947,506 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,133 research outputs from this source. They receive a mean Attention Score of 5.0. This one has done particularly well, scoring higher than 95% 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 198,032 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 90% of its contemporaries.
We're also able to compare this research output to 126 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 95% of its contemporaries.