Design and evaluation of
a new file browser interface
in Linux environment
Debmalya Sinha
Synopsis Seminar
January 2013
Objective
Provide file browsing convenience to new users
● Filesystem Visualization
● File Arrangement
● Finding Files
Objective
Provide file browsing convenience to new users
● Filesystem Visualization
● File Arrangement
● Finding Files
Fil...
Objective
Provide file browsing convenience to new users
● Filesystem Visualization
● File Arrangement
● Finding Files
Development
SahajBrowser
A novel file Browser
Gardener
A file browser assistant
Helps in Visualization and file
arrangemen...
Development
SahajBrowser
A novel file Browser
Gardener
A file browser assistant
Sahaj Linux
Work Done
1.Design and evaluation of SahajBrowser Visualization
2.Design and evaluation of SahajBrowser File Arrangement
3...
1. Filesystem Visualization
● Helps users understand Folder Hierarchy – the parent-child
relationship between folders
● Re...
1. Filesystem Visualization
● Placement of the folders
● Length of the representation
Good Visualization
Faster File Brows...
Existing file browsers
● Narrow tree-view
● Congested
● No file list in tree-view
● Length of tree depends on
number of ch...
SahajBrowser Visualization
SahajBrowser Visualization
● Constant distance
● Length does not depend on
number of child folders
● Better placement
● In...
SahajBrowser Visualization
● Constant distance
● Length does not depend on
number of child folders
● Better placement
● In...
SahajBrowser Visualization
● Constant distance
● Length does not depend on
number of child folders
● Better placement
● In...
SahajBrowser Visualization
● Constant distance
● Length does not depend on
number of child folders
● Better placement
● In...
SahajBrowser Visualization
● Constant distance
● Length does not depend on
number of child folders
● Better placement
● In...
Issues addressed
Helps new users understand
the Filesystem Hierarchy
intuitively
Constant distance reduces
File browsing t...
The browsing task
Task: To go from one folder in the filesystem to
another folder in an expanded treeview
1) source and de...
The browsing task
Task: To go from one folder in the filesystem to
another folder in an expanded treeview
1) source and de...
The task
● Browse a hierarchy of (N, L):
– N number of average child folders for each folder
– L numbers of level of the h...
Fitts' Law modeling
Calculates the Index of difficulty(ID)
Destination
source
B
H
D
ID = log2
(1+D/W) Where W = min(B,H)
Windows Explorer
● For Explorer, the distance from one source folder to a
destination folder depends on both the number of...
SahajBrowser
● For SahajBrowser, the distance between parent and
child does not depend on number of child folders.
● Thus,...
Result
Windows
Explorer
SahajBrowser
Average number of child folders (N)
IndexofDifficulty
Level
8
6
4
User Interaction Survey
● Finds out how easily new users understand filesystem hierarchy
(with two different visualization...
Method
● Set up and expanded a hierarchy
of level 3 with 12 child folders at
each level
● The folders has same names
(alph...
Result
Q1 Q2 Q3
0
5
10
15
20
25
SahajBrowser
Explorer
Questions
ResponseTimeinseconds
2. File Arrangement
One Source Folder One Destination Folder
File copy
Existing file browsers only provide
Multi Folder File Arrangement
Pictures
File copyDownloads
Desktop
Home
Multi Folder File Arrangement
Pictures
File copyDownloads
Desktop
Home
Conventional method: one-to-one copy for each sourc...
Accross the room
Jars of candy !
Empty jar to put some candies
Empty Bowl
Empty jar to put some candies
File arrangement task
/home
user1 user2 user3
music songs Downloads
media
files
files
Level 1
Level 2
Level 3
Level 4copy
SahajBrowser File Arrangement
Select item A1, A2
from folder A
Select item B1, B2, B3
from folder B
Start
End
Selection Qu...
SahajBrowser Multi-folder selection
KLM-GOMS model analysis
Algorithm for Nautilus
Algorithm for Windows Explorer
Algorithm for SahajBrowser
with Multiple Sel...
KLM-GOMS
Kieras(2003) has analytically and experimentally defined average completion
times for the primitive operators in ...
Predicted time in seconds
Assuming Level = L for every folder to operate on. We also assume
the average time to select fil...
2 3 4 5 6 7 8 9 10
0
50
100
150
200
250
Nautilus
Explorer
SahajBrowser
Number of source folders
Timeinseconds
Result
Compa...
3. Finding files in a filesystem
Maa,
Have you seen
My thesis draft?
3. Finding files in a filesystem
● It is pretty hard to find from an unorganized pile
● Users hardly use “find” utilities ...
Our approach
● Browsing by context needs a semantic hierarchy
● Such hierarchy needs to be maintained by users.
● We provi...
Semantic Folder Hierarchy
● It is very easy to find items while browsing in a Semantic
Folder Hierarchy
● Everytime a new ...
Our work
● Living with Trees: a cognitive experiment that
finds out the nature of categorization and
organization practice...
Our work
● Living with Trees: a cognitive experiment that
finds out the nature of categorization and
organization practice...
Living with Trees
● Categorization: Everyone can .. but people
are reluctant to actually do so
● Do people organize the ca...
The method
● An unorganized pile of 82 cards (bearing pictures of common
objects and personalities) is given to the partic...
Sample placement
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
0
2
4
6
8
10
12
14
Participants
HighestLevelofHierarchy
Result...
Results - (bottom-up)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
0
1
2
3
4
5
6
7
Participants
LevelofBott...
TopDown and BottomUp comparison
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23
0
1
2
3
4
5
6
Top Down
Bottom ...
Result
In top down approach:
1. Average Level of hierarchy during categorization is 3.
2. Average Number of Categories are...
Conclusion
● The initial hierarchical organization is, in average,
moderate (3 levels)
● External assistance has a huge im...
Challenges
● The main challenge for users is:
Maintaining the Semantic Hierarchy each time a file is saved
● Maintenance i...
The Gardener
A filebrowser assistant to help users
create and maintain semantic folder hierarchy tree
How Gardener works
● Whenever a user tries to create a file, Gardener takes the input
filename/foldername and suggests a l...
Contextual Suggestions
Does not suggest only by filenames, but its context
Richard_Feynman_smiling_awkwardly.png
Save this...
Contextual Suggestions
Richard_Feynman_smiling_awkwardly.png
Gotcha..
this fellow is a
Nuclear
Physicist
Does not suggest ...
Architecture
Gardener is a filebrowser plugin. It has two main parts in its execution. The back-end part
has 3 blocks. The...
Architecture
Input Filename
Input
Sanitizer
Gardener
Interface
Keyword
Generator
Filesystem
Search
Output
Suggestions
Inpu...
Input Sanitizer
1. Stop Word Removal: Removes words such as “and”, “of”, etc
2. Stemming: Removes unwanted suffixes like n...
Keyword Generator
Synonym
Generation
Hypernym
Generation
Input keyword
Synonym
keywords
Hypernym
keywords
WordNet
Database...
Filesystem Search
● Categorizes the files into 4 parts: Documents, Music & Video,
Pictures and Misc.
● Search the keywords...
How good is Gardener
● Usability survey with 12 computer experienced users
● Task is to save 32 files with Gardener
● Cate...
Average usage of Gardener
suggestions
24.47
9.11
20.83
49.73
4.17
Actual
Synonym
Hypernym
New folder
Cancel
4.17
Average acceptance rate
Averageacceptance(inpercentage)
Total number of suggestion clicked
We define the “Average Acceptan...
System Usability Scale
● Measured usability with 10 questions of SUS
● Each question is a 5 point “Likert scale” type (Str...
SUS score
The average SUS score of Gardener is very high at 89.42 out of a possible 100.
Questions
Strongly
disagree
Future Work
Clarity.mp3
Black Pearl.jpg
User saves
Which is a song by
John Mayer
Pirates of
Caribbean
If the user doesn't ...
Sahaj Linux
UI survey
● Two tasks were given to 21 target users:
– Open a text file
– Play a music file
● How to open something by cli...
Results
Task 1 Task 2
0
5
10
15
20
25
30
35
40
Sahaj Linux
Windows XP
ResponseTimeinseconds
Overview
1.Design and evaluation of SahajBrowser Visualization
2.Design and evaluation of SahajBrowser File Arrangement
3....
Synopsis Presentation
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Synopsis Presentation

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Synopsis of the work done in my Masters. It describes:
1. SahajBrowser: The benefits and comparative studies
2. Living With Trees: The cognitive experiment and results
3. The Gardener: The intellligent file browser assistant. Architecture and Results

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Synopsis Presentation

  1. 1. Design and evaluation of a new file browser interface in Linux environment Debmalya Sinha Synopsis Seminar January 2013
  2. 2. Objective Provide file browsing convenience to new users ● Filesystem Visualization ● File Arrangement ● Finding Files
  3. 3. Objective Provide file browsing convenience to new users ● Filesystem Visualization ● File Arrangement ● Finding Files File copyDownloads Desktop Home Pictures
  4. 4. Objective Provide file browsing convenience to new users ● Filesystem Visualization ● File Arrangement ● Finding Files
  5. 5. Development SahajBrowser A novel file Browser Gardener A file browser assistant Helps in Visualization and file arrangement Helps saving files into its correct contextual place
  6. 6. Development SahajBrowser A novel file Browser Gardener A file browser assistant Sahaj Linux
  7. 7. Work Done 1.Design and evaluation of SahajBrowser Visualization 2.Design and evaluation of SahajBrowser File Arrangement 3.Living with Trees: a cognitive study to find the nature and extent of categorization and organization practices of target users 4.Design and evaluation of Gardener 5.Design and evaluation of Sahaj Linux
  8. 8. 1. Filesystem Visualization ● Helps users understand Folder Hierarchy – the parent-child relationship between folders ● Reduces time for browsing through the filesystem Good Visualization Faster File Browsing Clearly distinguishable folder relationship
  9. 9. 1. Filesystem Visualization ● Placement of the folders ● Length of the representation Good Visualization Faster File Browsing Clearly distinguishable folder relationship
  10. 10. Existing file browsers ● Narrow tree-view ● Congested ● No file list in tree-view ● Length of tree depends on number of child folders
  11. 11. SahajBrowser Visualization
  12. 12. SahajBrowser Visualization ● Constant distance ● Length does not depend on number of child folders ● Better placement ● Intuitive parent-child relationship ● File list in tree view ● Comparing content easier
  13. 13. SahajBrowser Visualization ● Constant distance ● Length does not depend on number of child folders ● Better placement ● Intuitive parent-child relationship ● File list in tree view ● Comparing content easier between a parent and its child folder
  14. 14. SahajBrowser Visualization ● Constant distance ● Length does not depend on number of child folders ● Better placement ● Intuitive parent-child relationship ● File list in tree view ● Comparing content easier
  15. 15. SahajBrowser Visualization ● Constant distance ● Length does not depend on number of child folders ● Better placement ● Intuitive parent-child relationship ● File list in tree view ● Comparing content easier
  16. 16. SahajBrowser Visualization ● Constant distance ● Length does not depend on number of child folders ● Better placement ● Intuitive parent-child relationship ● File list in tree view ● Comparing content easier
  17. 17. Issues addressed Helps new users understand the Filesystem Hierarchy intuitively Constant distance reduces File browsing time User Interaction Survey Modelling by Fitts' Law
  18. 18. The browsing task Task: To go from one folder in the filesystem to another folder in an expanded treeview 1) source and destination are L levels away 2) all the folders in between source and destination has N number of child folders in an average. /home/ecntrk/Documents/research-writing/Thesis/Chapters
  19. 19. The browsing task Task: To go from one folder in the filesystem to another folder in an expanded treeview 1) source and destination are L levels away 2) all the folders in between source and destination has N number of child folders in an average. /home/ecntrk/Documents/research-writing/Thesis/Chapters In this example, the level difference L = 5 source destination
  20. 20. The task ● Browse a hierarchy of (N, L): – N number of average child folders for each folder – L numbers of level of the hierarchy ● We vary N from 3 to 20 and L from 4 to 8 Level 1 Level 2 Level 3 Level 4 Level 5 } L N
  21. 21. Fitts' Law modeling Calculates the Index of difficulty(ID) Destination source B H D ID = log2 (1+D/W) Where W = min(B,H)
  22. 22. Windows Explorer ● For Explorer, the distance from one source folder to a destination folder depends on both the number of average child folders (N) and the level difference (L) D = (N * L * 17) px W = 17 px ID = log2 ( 1 + N * L )
  23. 23. SahajBrowser ● For SahajBrowser, the distance between parent and child does not depend on number of child folders. ● Thus, distance from one source folder to one destination folder depends only on the level L D = (L * 238.64) px W = 170 px ID = log2 ( 1 + (1.40 L) )∗
  24. 24. Result Windows Explorer SahajBrowser Average number of child folders (N) IndexofDifficulty Level 8 6 4
  25. 25. User Interaction Survey ● Finds out how easily new users understand filesystem hierarchy (with two different visualizations) ● Comparison of Explorer and SahajBrowser ● Users: 21 new users – Computer inexperienced – Digital experience: mobile phone – Age: 32-40 ● Were given a brief introductory concept on folder hierarchy
  26. 26. Method ● Set up and expanded a hierarchy of level 3 with 12 child folders at each level ● The folders has same names (alphabets A – L ) in each level ● 3 Questions asked : – Find parent – Find Grandparent – Find 2 siblings of parent named “B” and “J” A B C D E F G H I J K L A B C D E F G H I J K L A B C D E F G H I J K L
  27. 27. Result Q1 Q2 Q3 0 5 10 15 20 25 SahajBrowser Explorer Questions ResponseTimeinseconds
  28. 28. 2. File Arrangement One Source Folder One Destination Folder File copy Existing file browsers only provide
  29. 29. Multi Folder File Arrangement Pictures File copyDownloads Desktop Home
  30. 30. Multi Folder File Arrangement Pictures File copyDownloads Desktop Home Conventional method: one-to-one copy for each source folders
  31. 31. Accross the room Jars of candy ! Empty jar to put some candies
  32. 32. Empty Bowl Empty jar to put some candies
  33. 33. File arrangement task /home user1 user2 user3 music songs Downloads media files files Level 1 Level 2 Level 3 Level 4copy
  34. 34. SahajBrowser File Arrangement Select item A1, A2 from folder A Select item B1, B2, B3 from folder B Start End Selection Queue Existing Browsers SahajBrowser A1, A2 B1, B2, B3 A1, A2, B1, B2, B3 A1, A2 A1, A2, B1, B2, B3B1, B2, B3 Nil Nil Job:
  35. 35. SahajBrowser Multi-folder selection
  36. 36. KLM-GOMS model analysis Algorithm for Nautilus Algorithm for Windows Explorer Algorithm for SahajBrowser with Multiple Selection
  37. 37. KLM-GOMS Kieras(2003) has analytically and experimentally defined average completion times for the primitive operators in Keystroke Level Modeling(KLM)
  38. 38. Predicted time in seconds Assuming Level = L for every folder to operate on. We also assume the average time to select files from one source folder is C seconds. tnaut = (n (5 L + C + 0.1)) sec∗ ∗ texpl = (2.5 L + n (2.5 L + C + 1.3)) sec∗ ∗ ∗ tsahaj = (n (2.5 L + C) + 2.5 L + 0.1) sec∗ ∗ ∗ n = total number of source folders L = average level of every source and destination folders C = time to select the files in a single source folder
  39. 39. 2 3 4 5 6 7 8 9 10 0 50 100 150 200 250 Nautilus Explorer SahajBrowser Number of source folders Timeinseconds Result Comparison of SahajBrowser with two existing file browsers; Nautilus and Windows Explorer Here we vary the number of source folders “n” and have the graph for 3 different browsers. Assuming: Level L = 4
  40. 40. 3. Finding files in a filesystem Maa, Have you seen My thesis draft?
  41. 41. 3. Finding files in a filesystem ● It is pretty hard to find from an unorganized pile ● Users hardly use “find” utilities (Sasse 2003, Nardi 2001) ● People “Browse” contextually to find files in filesystem
  42. 42. Our approach ● Browsing by context needs a semantic hierarchy ● Such hierarchy needs to be maintained by users. ● We provide necessary assistance to help users maintaining semantic folder hierarchy by putting the files into their correct contextual place while saving Maa, Have you seen My thesis draft? PUT IT WHERE IT BELONGS IN THE FIRST PLACE
  43. 43. Semantic Folder Hierarchy ● It is very easy to find items while browsing in a Semantic Folder Hierarchy ● Everytime a new file is added, it has to be put in its correct contextual place. ● But users are reluctant to maintain it this way ● We help them maintaining the semantic hierarchy
  44. 44. Our work ● Living with Trees: a cognitive experiment that finds out the nature of categorization and organization practices of the target users ● Gardener: A filebrowser assistant that helps users maintaining semantic filesystem hierarchy.
  45. 45. Our work ● Living with Trees: a cognitive experiment that finds out the nature of categorization and organization practices of the target users ● Gardener: A filebrowser assistant that helps users maintaining semantic filesystem hierarchy.
  46. 46. Living with Trees ● Categorization: Everyone can .. but people are reluctant to actually do so ● Do people organize the categories hierarchically? ● upto how many levels target users do organize hierarchically? ● What is the effect of external stimulation on their performance? ● The findings are crucial for implementing semantic folder hierarchy.
  47. 47. The method ● An unorganized pile of 82 cards (bearing pictures of common objects and personalities) is given to the participants ● They were asked to categorize the cards on the floor ● Unlimited space given for placing ● We noted the if they are making smaller concepts from more general concepts ● After they finishes, we asked them if they can do better ● The final performance after our stimulation, is noted
  48. 48. Sample placement
  49. 49. 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 2 4 6 8 10 12 14 Participants HighestLevelofHierarchy Results - (top-down) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 5 10 15 20 25 30 Participants NumberofCategories After Stimulation Before Stimulation After Stimulation Before Stimulation
  50. 50. Results - (bottom-up) 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 1 2 3 4 5 6 7 Participants LevelofBottom-upHierarchies After Before
  51. 51. TopDown and BottomUp comparison 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 1 2 3 4 5 6 Top Down Bottom Up Participants HighestLevelofHierarchy 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 0 1 2 3 4 5 6 7 8 9 Participants HighestLevelofCategories Top Down Bottom Up Before Stimulation After Stimulation
  52. 52. Result In top down approach: 1. Average Level of hierarchy during categorization is 3. 2. Average Number of Categories are 6.43 3. Both the numbers shoot up to 7 and 16.29 after some help from the experimenter In bottom up approach: 1. Participants are much less able to categorize like this 2. Help from experimenter only increases the number to very tiny portion.
  53. 53. Conclusion ● The initial hierarchical organization is, in average, moderate (3 levels) ● External assistance has a huge impact on the performance (135%) ● People can organize much better if an assistant is guiding them.
  54. 54. Challenges ● The main challenge for users is: Maintaining the Semantic Hierarchy each time a file is saved ● Maintenance is a major problem for two main reasons: 1. Users have to “remember” all concepts in filesystem in order to find a suitable place for the new item 2. Filesystem is non associative. Users can't directly access files. Have to browse by the hierarchy
  55. 55. The Gardener A filebrowser assistant to help users create and maintain semantic folder hierarchy tree
  56. 56. How Gardener works ● Whenever a user tries to create a file, Gardener takes the input filename/foldername and suggests a location ● It generates a set of similar keywords from the filename and then searches the filesystem for a contextual match. ● User can store the file/folder in a single click from the Gardener interface. Let's see a little demo
  57. 57. Contextual Suggestions Does not suggest only by filenames, but its context Richard_Feynman_smiling_awkwardly.png Save this picture.. but where?
  58. 58. Contextual Suggestions Richard_Feynman_smiling_awkwardly.png Gotcha.. this fellow is a Nuclear Physicist Does not suggest only by filenames, but its context ~/Pictures/people/physicists So let's save it in:
  59. 59. Architecture Gardener is a filebrowser plugin. It has two main parts in its execution. The back-end part has 3 blocks. The output suggestions of the backend are shown by a front end. 1. Input sanitizer: The input keyword is generated from the raw input. 2. Keyword generator: Takes sanitized input keyword and generates Hypernym and Synonym keywords. 3. Filesystem Search: Takes this list of the keywords list searches them in the filesystem to give parent and the peer suggestions fro the front end. Input Filename Input Sanitizer Gardener Interface Keyword Generator Filesystem Search Output Suggestions Input keyword Synonyms Hypernyms RegExp matches
  60. 60. Architecture Input Filename Input Sanitizer Gardener Interface Keyword Generator Filesystem Search Output Suggestions Input keyword Synonyms Hypernyms RegExp matches falling leaves in autumn123.jpg ['leaf', 'autumn', 'fall'] ['plant organ', 'leaf', 'season', 'leafage', 'autumn', 'foliage', 'fall', 'time of year'] 1) ~/Pictures/walpaper/seasons 2) ~/Pictures/leafy sky
  61. 61. Input Sanitizer 1. Stop Word Removal: Removes words such as “and”, “of”, etc 2. Stemming: Removes unwanted suffixes like numbers and special symbols etc 3. Lemmatization: helps finding the base word from the stemmed word. 4. POS Tagging: chooses only the nouns and verbs from a compound filename Input Filename Stopword Removal Stemming LemmatizationKeyword compound input Significant Words Unwanted Prefix and Suffix removal POS Tagger Clean Words Extracted Nouns Input Sanitizer Module To be used by Keyword Generator
  62. 62. Keyword Generator Synonym Generation Hypernym Generation Input keyword Synonym keywords Hypernym keywords WordNet Database NLTK DB (RDF schema) Instance of Superset keywords
  63. 63. Filesystem Search ● Categorizes the files into 4 parts: Documents, Music & Video, Pictures and Misc. ● Search the keywords in the appropriate folder according to file type. ● will search .jpg, .png etc in /home/Pictures (changable) ● If any match has not been found, it'll ask the user to create a new folder with the right context ● User can cancel suggestions and browse to save in any other folder
  64. 64. How good is Gardener ● Usability survey with 12 computer experienced users ● Task is to save 32 files with Gardener ● Categorized Gardener output into 4 parts: – Actual words, Hypernym, Synonyms and new folder suggesiton ● Average acceptance rate = Total number of suggestion clicked Total number of suggestions generated
  65. 65. Average usage of Gardener suggestions 24.47 9.11 20.83 49.73 4.17 Actual Synonym Hypernym New folder Cancel 4.17
  66. 66. Average acceptance rate Averageacceptance(inpercentage) Total number of suggestion clicked We define the “Average Acceptance rate” = Total number of suggestions generated
  67. 67. System Usability Scale ● Measured usability with 10 questions of SUS ● Each question is a 5 point “Likert scale” type (Strongly agree (5 points) to Strongly disagree (1 point) ) 1. I think that I would like to use this system frequently. 2. I found the system unnecessarily complex. 3. I thought the system was easy to use. 4. I think that I would need the support of a technical person to be able to use this system. 5. I found the various functions in this system were well integrated. 6. I thought there was too much inconsistency in this system. 7. I would imagine that most people would learn to use this system very quickly. 8. I found the system very cumbersome to use. 9. I felt very confident using the system. 10. I needed to learn a lot of things before I could get going with this system.
  68. 68. SUS score The average SUS score of Gardener is very high at 89.42 out of a possible 100. Questions Strongly disagree
  69. 69. Future Work Clarity.mp3 Black Pearl.jpg User saves Which is a song by John Mayer Pirates of Caribbean If the user doesn't provide this, Gardener can't decide the right folder, Unless there's an entry about it in the RDF schema, which is very impractical We will try to include more sparse informations like these in future from Internet. Which is a ship in
  70. 70. Sahaj Linux
  71. 71. UI survey ● Two tasks were given to 21 target users: – Open a text file – Play a music file ● How to open something by clicking was explained. ● The response time was noted.
  72. 72. Results Task 1 Task 2 0 5 10 15 20 25 30 35 40 Sahaj Linux Windows XP ResponseTimeinseconds
  73. 73. Overview 1.Design and evaluation of SahajBrowser Visualization 2.Design and evaluation of SahajBrowser File Arrangement 3.Living with Trees: a cognitive study to find the nature and extent of categorization and organization practices of target users 4.Design and evaluation of Gardener 5.Design and evaluation of Sahaj Linux

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