AutoComPaste Auto-Completing Text as an Alternative to Copy-Paste


НазваAutoComPaste Auto-Completing Text as an Alternative to Copy-Paste
Дата конвертації30.04.2013
Розмір445 b.
ТипПрезентации


AutoComPaste Auto-Completing Text as an Alternative to Copy-Paste

Shengdong (Shen) Zhao 1

Fanny Cheviler 2

Wei Tsang Ooi 1

Chee Yuan Lee 1

Arpit Agarwal 1,3

Background & Motivation



Background & Motivation

Current copy-paste techniques:

6-Step Common Workflow



6-Step Common Workflow



6-Step Common Workflow



6-Step Common Workflow



6-Step Common Workflow



6-Step Common Workflow



6-Step Common Workflow



6-Step Common Workflow









Logger Study

  • Logger that logs copy-paste event

    • Automatically turned on, data send to a central server
    • For each copy-paste event, we record
    • Type (copy | paste)
    • Number of windows open, host window, and application name
    • Timestamp
    • Nearest typing event in terms of time
    • Content copied
      • “joe12@gmail.com” is stored as “xxx00@xxxxx.xxx”
  • Participants

    • 22 students (9 female, 13 male, 21-27, M 23.14)
  • Duration

    • 2 weeks


Logger Study - Result

  • Data collected

    • 34.1 MB of text data, 8168 events with 3481 (43%) copy and 4687 (57%) paste.
  • Windows opened

    • 83% of the time, users have 6-20 concurrently opened windows (average 12) when performing CP
  • Type of copy-paste

    • 57% (2672) cross-document CP
    • 43% (2015) within-document CP
  • Interleaving with typing

    • 42% of copy events were performed after typing, and 54% of paste events were followed by typing
  • Text size

    • Phrases (39%), Sentences (33%), Paragraphs (28%)




AutoComPaste Video

http://www.youtube.com/watch?v=KoDT3UeAoRE

How does AutoComPaste Compare with Traditional Copy-Paste Techniques?



What are the conditions or factors?

















































Controlled Experiment

12 university participants

X 2 techniques (XWin, ACP)

X 2 content knowledge type (known, unknown)

X 2 location knowledge type (known, unknown)

X 2 visibility type (visible, invisible)

X 2 pre-copy activity type (isolated, typing)

X 6 trials of 3 different units of text (2 phrases + 2 sentences + 2 paragraphs)

= 2304 trials total

Results





Qualitative Study

  • 6 participants (3 female, 3 male; aged 22-25, mean 23.8)

  • Realistic trip planning task

    • plan a 5-day trip to Santa Barbara by gathering relevant information from 10 given webpages
    • asked to include at least one outdoor activity, one indoor activity, and one restaurant for each day of the trip
  • Can use either AutoComPaste and other copy-paste techniques



Results

AutoComPaste is heavily used and highly rated by 5/6 participants

However, one rated AutoComPaste negatively
  • He is a non-native English speaker participant



Conclusion

  • AutoComPaste nicely complements the traditional copy-paste techniques

    • AutoComPaste has advantage when the keyword/prefix is known
    • When keywords/prefix is known and location is unknown, AutoComPaste will have the most advantage
    • XWin has advantage when the keyword/prefix is unknown
  • Performance of AutoComPaste is subject to typing and spelling skills



Acknowledgment

  • Shi Xiaoming for programming the logger

  • Guia Gali and Symon Oliver for video editing

  • Study participants

  • Members in the NUS-HCI lab

  • This research is supported by National University of Singapore Academic Research Fund R-252-000-464-112



Q & A



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