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Visualization of ExplanationsVisualization of Explanations
inin
Recommender SystemsRecommender Systems
Seifedine KadrySeifedine Kadry
American University of The Middle East -American University of The Middle East -
KuwaitKuwait
Mohammed Z. Al-TaieMohammed Z. Al-Taie
AL-Salam University CollegeAL-Salam University College
-- Iraq ---- Iraq --
2
Goal of the studyGoal of the study
 The focus of this study is the visualization of explanations in
recommender systems.
 The study falls in the area of controlling the recommendation
process which gained little attention so far.
 Certain modalities (such as text, graphs, tables, and images)
can better present recommendations and explanations to
users.
3
4
What Are Recommender System (RS)?What Are Recommender System (RS)?
 Also called Recommendation Systems, they are
software tools and techniques providing
suggestions for items to be of use to a user.
BenefitsBenefits
 RS are being well used in various application
domains such as music, videos, queries, news,
friends on social networks etc..
5
Ex: Amazon’s Recommendation SystemEx: Amazon’s Recommendation System
A number of ways have been devised to offer
recommendations to the system users:
6
How Recommendations Are GivenHow Recommendations Are Given
7
Explanations in Recommender SystemExplanations in Recommender System
Now let’s talk about Explanations:
 Important pieces of information that are used by
both selling and buying agents to increase their
performance.
 Another definition … it is a description that makes
users better realize if the recommended item is
relevant to their needs or not.
8
YouTube
Explanation System
A Restaurant
Recommendation Explanation
Explanations - ExamplesExplanations - Examples
9
Amazon
Explanation System
Explanations - ExampleExplanations - Example
10
Why Using Explanations in RSWhy Using Explanations in RS??
11
 More on this artist …
 Try something from similar
artists …
 Someone similar to you also
like this …
 As you listened to that, you
may want this …
 These two go together …
 This is highly rated …
 Try something new …
 Similar or related products
…
 Complementary
accessories ...
 Gift idea ...
 Welcome back (recently
viewed) …
 For you today …
 New for you …
 Hot / Most popular of this
type …
 Other people also do this
…
Phrases Expressing ExplanationsPhrases Expressing Explanations
12
13
Information VisualizationInformation Visualization
 Human eyes can interpret a graph much faster than
plain texts, as it can process many visual cues
simultaneously.
 The design look of the website is what visitors care
much about compared to other website features such
as information structure, information focus and
usefulness of information.
 Visualization has been used in recommender systems
in both offering recommendation to users and
explaining why these recommendations were given.
14
Visualization TechniquesVisualization Techniques
To visualize information, a number of visualization
techniques have been used such as tables, images,
diagrams, text-highlighting, color schemes, rating and
animation. More sophisticated methods include:
Geometrically-transformed displays include techniques such as
scatterplot matrices, projection pursuit techniques, prosection views,
hyperslice and parallel coordinates
Iconic displays include little faces, needle icons, star icons, stick figure
icons, color icons and TileBars.
Dense pixel displays include techniques such as recursive patterns
and circle segments
Stacked displays include dimensional stacking.
In Amazon’s website, there is the use of techniques such
as text-highlighting, five-star rating scales, images,
colors, text size, tables, animation…
15
Example #1:Example #1:
16
a ten-star rating scale: The IMDb.com system uses
Example #2:Example #2:
An example for using different visualization techniques
in some explanations interface
17
Example #3:Example #3:
However, information visualization suffers from the
following common problems:
 Clutter
 Data overload
 Size of the graph
 Time complexity
18
Visualization ProblemsVisualization Problems
19
Correlated DisciplinesCorrelated Disciplines
A. Decision Making
 Decision making is the selection of a course of action from two or more
alternatives in order to solve a problem or to achieve an objective.
 It was found that the format of the information presented can affect
what decisions consumers can make.
 The integration of recommendation technologies with a profound
realization of human decision making can improve the quality of
recommendation for users and the predictability of decision outcomes.
There is strong a relationship between visualization of
information and two other disciplines. Understanding this
relationship is important for a better RS design:
B. Human Computer Interaction
 Human Computer Interaction (HCI) is concerned with how people
interact with computers and how computers can be developed for
successful interaction with human beings.
 The goal of HCI is to design systems that minimize the barrier between
the human's cognitive model of what they want to accomplish and the
computer's understanding of the user's task.
 By designing a good explanation interface, we can better explain
recommendations and can even push users to make further requests.
20
Correlated DisciplinesCorrelated Disciplines
21
There are a number of future research directions we
would like to explore. For example:
Future DirectionsFuture Directions
THANK YOU!
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Visualization of explanations in recommender systems

  • 1. Visualization of ExplanationsVisualization of Explanations inin Recommender SystemsRecommender Systems Seifedine KadrySeifedine Kadry American University of The Middle East -American University of The Middle East - KuwaitKuwait Mohammed Z. Al-TaieMohammed Z. Al-Taie AL-Salam University CollegeAL-Salam University College -- Iraq ---- Iraq --
  • 2. 2 Goal of the studyGoal of the study  The focus of this study is the visualization of explanations in recommender systems.  The study falls in the area of controlling the recommendation process which gained little attention so far.  Certain modalities (such as text, graphs, tables, and images) can better present recommendations and explanations to users.
  • 3. 3
  • 4. 4 What Are Recommender System (RS)?What Are Recommender System (RS)?  Also called Recommendation Systems, they are software tools and techniques providing suggestions for items to be of use to a user. BenefitsBenefits  RS are being well used in various application domains such as music, videos, queries, news, friends on social networks etc..
  • 5. 5 Ex: Amazon’s Recommendation SystemEx: Amazon’s Recommendation System
  • 6. A number of ways have been devised to offer recommendations to the system users: 6 How Recommendations Are GivenHow Recommendations Are Given
  • 7. 7 Explanations in Recommender SystemExplanations in Recommender System Now let’s talk about Explanations:  Important pieces of information that are used by both selling and buying agents to increase their performance.  Another definition … it is a description that makes users better realize if the recommended item is relevant to their needs or not.
  • 8. 8 YouTube Explanation System A Restaurant Recommendation Explanation Explanations - ExamplesExplanations - Examples
  • 9. 9 Amazon Explanation System Explanations - ExampleExplanations - Example
  • 10. 10 Why Using Explanations in RSWhy Using Explanations in RS??
  • 11. 11  More on this artist …  Try something from similar artists …  Someone similar to you also like this …  As you listened to that, you may want this …  These two go together …  This is highly rated …  Try something new …  Similar or related products …  Complementary accessories ...  Gift idea ...  Welcome back (recently viewed) …  For you today …  New for you …  Hot / Most popular of this type …  Other people also do this … Phrases Expressing ExplanationsPhrases Expressing Explanations
  • 12. 12
  • 13. 13 Information VisualizationInformation Visualization  Human eyes can interpret a graph much faster than plain texts, as it can process many visual cues simultaneously.  The design look of the website is what visitors care much about compared to other website features such as information structure, information focus and usefulness of information.  Visualization has been used in recommender systems in both offering recommendation to users and explaining why these recommendations were given.
  • 14. 14 Visualization TechniquesVisualization Techniques To visualize information, a number of visualization techniques have been used such as tables, images, diagrams, text-highlighting, color schemes, rating and animation. More sophisticated methods include: Geometrically-transformed displays include techniques such as scatterplot matrices, projection pursuit techniques, prosection views, hyperslice and parallel coordinates Iconic displays include little faces, needle icons, star icons, stick figure icons, color icons and TileBars. Dense pixel displays include techniques such as recursive patterns and circle segments Stacked displays include dimensional stacking.
  • 15. In Amazon’s website, there is the use of techniques such as text-highlighting, five-star rating scales, images, colors, text size, tables, animation… 15 Example #1:Example #1:
  • 16. 16 a ten-star rating scale: The IMDb.com system uses Example #2:Example #2:
  • 17. An example for using different visualization techniques in some explanations interface 17 Example #3:Example #3:
  • 18. However, information visualization suffers from the following common problems:  Clutter  Data overload  Size of the graph  Time complexity 18 Visualization ProblemsVisualization Problems
  • 19. 19 Correlated DisciplinesCorrelated Disciplines A. Decision Making  Decision making is the selection of a course of action from two or more alternatives in order to solve a problem or to achieve an objective.  It was found that the format of the information presented can affect what decisions consumers can make.  The integration of recommendation technologies with a profound realization of human decision making can improve the quality of recommendation for users and the predictability of decision outcomes. There is strong a relationship between visualization of information and two other disciplines. Understanding this relationship is important for a better RS design:
  • 20. B. Human Computer Interaction  Human Computer Interaction (HCI) is concerned with how people interact with computers and how computers can be developed for successful interaction with human beings.  The goal of HCI is to design systems that minimize the barrier between the human's cognitive model of what they want to accomplish and the computer's understanding of the user's task.  By designing a good explanation interface, we can better explain recommendations and can even push users to make further requests. 20 Correlated DisciplinesCorrelated Disciplines
  • 21. 21 There are a number of future research directions we would like to explore. For example: Future DirectionsFuture Directions
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