Optimization of Text Input
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Invited talk at the Dagstuhl Seminar on Computational Interactivity. I presented my PhD work on the optimization of text input methods. More information: http://www.dagstuhl.de/de/programm/kalender/semhp/?semnr=17232 Also see: http://computationalinteraction.org
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Grading Guide
<QNT/561 Version 9>
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Statistics Concepts and Descriptive Measures Grading Guide
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Applied Business Research and Statistics
Purpose of Assignment
The purpose of this assignment to orient students to the key concepts in statistics. This assignment will introduce students to the language of statistics. Students will also get a chance to warm-up on evaluating some basic descriptive statistics using Excel® prior to the course start.
Assignment Steps
This assignment has an Excel® dataset spreadsheet attached. You will be required to only do one of the three datasets.
Resource: Microsoft Excel®, Statistics Concepts and Descriptive Measures Data Set
Download the Statistics Concepts and Descriptive Measures Data Set.
Choose one of the following datasets to complete this assignment:
· Consumer Food ( This is the one I chose)
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Answer each of the following in a total of 90 words:
· For each column, identify whether the data is qualitative or quantitative.
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Copyright
Copyright © 2017, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008 by University of Phoenix. All rights reserved.
University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries.
Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation.
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Purpose of Assignment
The purpose of this assignment to orient students to the key concepts in statistics. This assignment will introduce students to the language of statistics. Students will also get a chance to warm-up on evaluating some basic descriptive statistics using Excel® prior to the course start.
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This assignment has an Excel® dataset spreadsheet attached. You will be required to only do one of the three datasets.
Resource: Microsoft Excel®, Statistics Concepts and Descriptive Measures Data Set
Download the Statistics Concepts and Descriptive Measures Data Set.
Choose one of the following datasets to complete this assignment:
· Consumer Food ( This is the one I chose)
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Answer each of the following in a total of 90 words:
· For each column, identify whether the data is qualitative or quantitative.
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· Evaluate the mean and median
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· Use the Excel =AVERAGE function to find the mean
· Use the Excel =MEDIAN function to find the median
· For each column containing quantitative data:
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· Use the Excel =STDEV.S function to find the standard deviation
· For range (maximum value minus the minimum value), find the maximum value using the Excel =MAX function and find the minimum value using the Excel's =MIN function
Copyright
Copyright © 2017, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008 by University of Phoenix. All rights reserved.
University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries.
Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation.
Edited in accordance with University of Phoenix® editorial standards and practices.
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Resources Required
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Statistics Concepts and Descriptive Measures Grading Guide.docx
Statistics Concepts and Descriptive Measures
Grading Guide
<QNT/561 Version 9>
4
Statistics Concepts and Descriptive Measures Grading Guide
QNT/561 Version 9
Applied Business Research and Statistics
Copyright
Copyright © 2017, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008 by University of Phoenix. All rights reserved.
University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries.
Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation.
Edited in accordance with University of Phoenix® editorial standards and practices.
Individual Assignment: Statistics Concepts and Descriptive MeasuresPurpose of Assignment
The purpose of this assignment to orient students to the key concepts in statistics. This assignment will introduce students to the language of statistics. Students will also get a chance to warm-up on evaluating some basic descriptive statistics using Excel prior to the course start.Resources Required
· Microsoft Excel®
· Statistics Concepts and Descriptive Measures Data SetGrading Guide
Content
Met
Partially Met
Not Met
Comments:
This assignment has an Excel® dataset spreadsheet attached. Students will be required to do one of the three datasets only and submit.
Download the Consumer Food, Financial, or Hospital Excel® Data Set.
Note: you have to work on only ONE dataset and not ALL.
Answer each of the following in a total 90 words:
· For each column, identify whether the data is qualitative or quantitative.
· Identify the level of measurement for the data in each column.
· For each column containing quantitative data:
· Evaluate the mean and median
· Interpret the mean and median in plain non-technical terms
· Use the Excel =AVERAGE function to find the mean
· Use the Excel =MEDIAN function to find the median
· For each column containing quantitative data:
· Evaluate the standard deviation and range
· Interpret the standard deviation and range in plain non-technical terms
· Use the Excel =STDEV.S function to find the standard deviation
For range (maximum value minus the minimum value), find the maximum value using the Excel =MAX function and find the minimum value using the Excel’s =MIN function
Total Available
Total Earned
3
#/3
Writing Guidelines
Met
Partially Met
Not Met
Comments:
The paper—including tables and graphs, headings, title page, and reference page—is consistent with APA formatting guidelines and meets course-level requirements.
Intellectual property is recognized with in-text citations and a reference page.
Paragraph and sentence transitions are present, logical, and maintain the flow throughout the paper.
Sentences are complete, clear, and concise.
.
Statistics Concepts and Descriptive Measures Grading Guide.docx
Statistics Concepts and Descriptive Measures
Grading Guide
<QNT/561 Version 9>
2
Statistics Concepts and Descriptive Measures Grading Guide
QNT/561 Version 9
Applied Business Research and Statistics
Copyright
Copyright © 2017, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008 by University of Phoenix. All rights reserved.
University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries.
Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation.
Edited in accordance with University of Phoenix® editorial standards and practices.
Individual Assignment: Statistics Concepts and Descriptive MeasuresPurpose of Assignment
The purpose of this assignment to orient students to the key concepts in statistics. This assignment will introduce students to the language of statistics. Students will also get a chance to warm-up on evaluating some basic descriptive statistics using Excel prior to the course start.Resources Required
· Microsoft Excel®
· Statistics Concepts and Descriptive Measures Data SetGrading Guide
Content
Met
Partially Met
Not Met
Comments:
This assignment has an Excel® dataset spreadsheet attached. Students will be required to do one of the three datasets only and submit.
Download the Consumer Food, Financial, or Hospital Excel® Data Set.
Note: you have to work on only ONE dataset and not ALL.
Answer each of the following in a total 90 words:
· For each column, identify whether the data is qualitative or quantitative.
· Identify the level of measurement for the data in each column.
· For each column containing quantitative data:
· Evaluate the mean and median
· Interpret the mean and median in plain non-technical terms
· Use the Excel =AVERAGE function to find the mean
· Use the Excel =MEDIAN function to find the median
· For each column containing quantitative data:
· Evaluate the standard deviation and range
· Interpret the standard deviation and range in plain non-technical terms
· Use the Excel =STDEV.S function to find the standard deviation
For range (maximum value minus the minimum value), find the maximum value using the Excel =MAX function and find the minimum value using the Excel’s =MIN function
Total Available
Total Earned
85
#/85
Writing Guidelines
Met
Partially Met
Not Met
Comments:
The paper—including tables and graphs, headings, title page, and reference page—is consistent with APA formatting guidelines and meets course-level requirements.
Intellectual property is recognized with in-text citations and a reference page.
Paragraph and sentence transitions are present, logical, and maintain the flow throughout the paper.
Sentences are complete, clear, and concise.
.
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Abstract of Aaron Han’s Presentation
The main topic of this presentation will be the “evaluation of machine translation”. With the rapid development of machine translation (MT), the MT evaluation becomes more and more important to tell whether they make some progresses. The traditional human judgments are very time-consuming and expensive. On the other hand, there are some weaknesses in the existing automatic MT evaluation metrics:
– perform well in certain language pairs but weak on others, which we call the language-bias problem;
– consider no linguistic information (leading the metrics result in low correlation with human judgments) or too many linguistic features (difficult in replicability), which we call the extremism problem;
– design incomprehensive factors (e.g. precision only).
To address the existing problems, he has developed several automatic evaluation metrics:
– Design tunable parameters to address the language-bias problem;
– Use concise linguistic features for the linguistic extremism problem;
– Design augmented factors.
The experiments on ACL-WMT corpora show the proposed metrics yield higher correlation with human judgments. The proposed metrics have been published on international top conferences, e.g. COLING and MT SUMMIT. Actually speaking, the evaluation works are very related to the similarity measuring. So these works can be further developed into other literature, such as information retrieval, question and answering, searching, etc.
A brief introduction about some of his other researches will also be mentioned, such as Chinese named entity recognition, word segmentation, and multilingual treebanks, which have been published on Springer LNCS and LNAI series. Precious suggestions and comments are much appreciated. The opportunities of further corporation will be more exciting.
Statistics Concepts and Descriptive Measures Grading Guide.docx
Statistics Concepts and Descriptive Measures
Grading Guide
<QNT/561 Version 9>
4
Statistics Concepts and Descriptive Measures Grading Guide
QNT/561 Version 9
Applied Business Research and Statistics
Copyright
Copyright © 2017, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008 by University of Phoenix. All rights reserved.
University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries.
Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation.
Edited in accordance with University of Phoenix® editorial standards and practices.
Individual Assignment: Statistics Concepts and Descriptive MeasuresPurpose of Assignment
The purpose of this assignment to orient students to the key concepts in statistics. This assignment will introduce students to the language of statistics. Students will also get a chance to warm-up on evaluating some basic descriptive statistics using Excel prior to the course start.Resources Required
· Microsoft Excel®
· Statistics Concepts and Descriptive Measures Data SetGrading Guide
Content
Met
Partially Met
Not Met
Comments:
This assignment has an Excel® dataset spreadsheet attached. Students will be required to do one of the three datasets only and submit.
Download the Consumer Food, Financial, or Hospital Excel® Data Set.
Note: you have to work on only ONE dataset and not ALL.
Answer each of the following in a total 90 words:
· For each column, identify whether the data is qualitative or quantitative.
· Identify the level of measurement for the data in each column.
· For each column containing quantitative data:
· Evaluate the mean and median
· Interpret the mean and median in plain non-technical terms
· Use the Excel =AVERAGE function to find the mean
· Use the Excel =MEDIAN function to find the median
· For each column containing quantitative data:
· Evaluate the standard deviation and range
· Interpret the standard deviation and range in plain non-technical terms
· Use the Excel =STDEV.S function to find the standard deviation
For range (maximum value minus the minimum value), find the maximum value using the Excel =MAX function and find the minimum value using the Excel’s =MIN function
Total Available
Total Earned
3
#/3
Writing Guidelines
Met
Partially Met
Not Met
Comments:
The paper—including tables and graphs, headings, title page, and reference page—is consistent with APA formatting guidelines and meets course-level requirements.
Intellectual property is recognized with in-text citations and a reference page.
Paragraph and sentence transitions are present, logical, and maintain the flow throughout the paper.
Sentences are complete, clear, and concise.
.
Statistics Concepts and Descriptive Measures Grading Guide.docx
Statistics Concepts and Descriptive Measures
Grading Guide
<QNT/561 Version 9>
2
Statistics Concepts and Descriptive Measures Grading Guide
QNT/561 Version 9
Applied Business Research and Statistics
Copyright
Copyright © 2017, 2015, 2014, 2013, 2012, 2011, 2010, 2009, 2008 by University of Phoenix. All rights reserved.
University of Phoenix® is a registered trademark of Apollo Group, Inc. in the United States and/or other countries.
Microsoft®, Windows®, and Windows NT® are registered trademarks of Microsoft Corporation in the United States and/or other countries. All other company and product names are trademarks or registered trademarks of their respective companies. Use of these marks is not intended to imply endorsement, sponsorship, or affiliation.
Edited in accordance with University of Phoenix® editorial standards and practices.
Individual Assignment: Statistics Concepts and Descriptive MeasuresPurpose of Assignment
The purpose of this assignment to orient students to the key concepts in statistics. This assignment will introduce students to the language of statistics. Students will also get a chance to warm-up on evaluating some basic descriptive statistics using Excel prior to the course start.Resources Required
· Microsoft Excel®
· Statistics Concepts and Descriptive Measures Data SetGrading Guide
Content
Met
Partially Met
Not Met
Comments:
This assignment has an Excel® dataset spreadsheet attached. Students will be required to do one of the three datasets only and submit.
Download the Consumer Food, Financial, or Hospital Excel® Data Set.
Note: you have to work on only ONE dataset and not ALL.
Answer each of the following in a total 90 words:
· For each column, identify whether the data is qualitative or quantitative.
· Identify the level of measurement for the data in each column.
· For each column containing quantitative data:
· Evaluate the mean and median
· Interpret the mean and median in plain non-technical terms
· Use the Excel =AVERAGE function to find the mean
· Use the Excel =MEDIAN function to find the median
· For each column containing quantitative data:
· Evaluate the standard deviation and range
· Interpret the standard deviation and range in plain non-technical terms
· Use the Excel =STDEV.S function to find the standard deviation
For range (maximum value minus the minimum value), find the maximum value using the Excel =MAX function and find the minimum value using the Excel’s =MIN function
Total Available
Total Earned
85
#/85
Writing Guidelines
Met
Partially Met
Not Met
Comments:
The paper—including tables and graphs, headings, title page, and reference page—is consistent with APA formatting guidelines and meets course-level requirements.
Intellectual property is recognized with in-text citations and a reference page.
Paragraph and sentence transitions are present, logical, and maintain the flow throughout the paper.
Sentences are complete, clear, and concise.
.
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Optimization of Text Input
- 1. Optimization ofText Input Anna Feit, Doctoral student, Aalto University Dagstuhl Seminar on Computational Interactivity, 06.06.2017
- 3. … Mid-air hand gestures for text input
- 4. A B C … Z space ? … 27 letters32 gestures 1033 mappings Which hand gesture to use for which letter?
- 5. Decisions: For each letter and gesture, assign the letter to the gesture or not. Constraints: No letter / gesture is assigned more than once. Evaluation criteria: Evaluate each design and pick the best one. 1033 feasible designs
- 6. Mathematical or algorithmic method to find the best design in the space • Search very large design spaces • Efficient and rigorous process • Quantitative guarantees on the goodness of the outcome • Explicitly trade-off different criteria and constraints Optimization
- 7. Challenges Formulation Objectives Optimization Formulation of the design problem and space, identification of design variables and constraints argmin 𝐾 𝑘𝜖𝐾 𝑙𝜖𝐾 𝐶 𝐾(𝑘, 𝑙) Modeling of evaluation criteria and combination into a fast to compute objective function (interaction cost) Mathematical solver or approximation algorithm to efficiently and thoroughly search the design space Objective 1 Objective2
- 8. The (quadratic) letter assignment problem Given: n letters – 𝑖, 𝑗 𝜖 𝛴 m gestures – 𝑘, 𝑙 𝜖 𝐺 Let: 𝑥𝑖𝑘 = 1 if letter 𝑖 is assigned to gesture 𝑘, 𝑥𝑖𝑘 = 0 otherwise 𝐗 = {𝑥𝑖𝑘 | ∀ 𝑖 𝜖 𝛴, 𝑘 𝜖 𝐺, 𝑥𝑖𝑘 𝜖 0,1 } characterises the full design space [Burkhard, 1977] Formulation
- 9. Goal: Find the assignment of letters to gestures that minimize the cost of typing one character after another Formulation
- 10. [Zhai, Hunter & Smith, 2000] [Light & Anderson, 1993] Formulation [Oulasvirta & Karrenbauer, 2014]
- 11. ” It is almost impossible to write correctly French with a keyboard marketed in France” French Ministry of Culture and Communications [Feit, Nancel,Weir, John, Bailly, Karrenbauer, Oulasvirta, upcoming] Formulation
- 12. [Feit, Nancel,Weir, John, Bailly, Karrenbauer, Oulasvirta, upcoming] Formulation é è à ù ê Ê É È À ç Ç æ Æ œ Œ ß ẞ þ Þ ð Ð ŋ Ŋ ij IJ ə Ə ʒ Ʒ & θ ı İ @ ™ ® © ſ º ª · ´ ˋ ˆ ¨ ˉ ̲ ˘ ̑ ˇ ˜ ˙ ̣ ̊ ˝ ˵ ¸ ˛ ̦ ̵ ̷ + < > = ± × ÷ ≤ ≥ ≃ % ‰ √ ∞ ¼ ½ ¾ # / | . , ; : ! ? ¡ ¿ … - - — – _ * † ‡ § ( ) [ ] { } “ ” ‘ ’ « » ‚ „ ‹ › € $ £ ¢ ¤ ¥ ₩ ?? ? > 𝟏𝟎 𝟐𝟏𝟑 𝒂𝒔𝒔𝒊𝒈𝒏𝒎𝒆𝒏𝒕𝒔
- 13. [Feit, Nancel,Weir, John, Bailly, Karrenbauer, Oulasvirta, upcoming] Formulation è
- 14. Objectives • Performance – Fitts’ law weighted by letter pair frequency • QWERTY similarity [Dunlop & Levine 2012] • Word or gesture clarity [Dunlop & Levine 2012, Smith, Bi & Zhai 2015]
- 15. Objectives Text entry is a complex task involving cognitive and motor processes. Fast performance involves more than quickly pointing from one key to another • Different performance factors • Different tasks • Different skill levels • Different strategies
- 16. Objectives [How we type, Feit, Weir, Oulasvirta, CHI 2016]
- 17. Objectives … |C6| = 0.38 Middle vs. Ring, participant 2046 Non-instructed:Ring Instructed: Middle Gesture performance models based on Fitts’ law and theories of motor control Anatomical comfort: Individuation index for each finger [Investigating the Dexterity of Multi-Finger Input for Mid-AirText Entry, Sridhar, Feit,Theobalt, Oulasvirta, CHI 2015]
- 18. Objectives [Feit, Nancel,Weir, John, Bailly, Karrenbauer, Oulasvirta, upcoming] Standardization committee: ”The new keyboard should facilitate typing of correct french, should be easy to learn and intuitive to use” • Performance and ergonomics of typing a special character before or after a letter • Intuitive and easy to learn: • Grouping similar characters • Position similar to QWERTY • Language statistics take into account different typing tasks, e.g. programming, social media usage, formal writing, etc.
- 19. Optimization Mathematical, exact methods Linear or Integer Programming, Branch and Bound methods Pro: • Explicit bounds and guarantees on optimality • Fast solvers available, e.g. Gurobi, CPLEX (IBM) Con: • Objective function in closed mathematical form • Not so flexible (e.g. noisy input data, interactive optimization, multi-objectives, etc. ) Heuristic approximation algorithms • Simulated annealing, Genetic algorithms, Biology inspired algorithms etc. Pro: • Straightforward to implement and standard implementations available • Flexible, e.g. combine with simulation models Con: • No bounds or guarantee to find the global optimum • Potentially slow • Formulation of design space and constraints
- 20. Optimization [Feit, Nancel,Weir, John, Bailly, Karrenbauer, Oulasvirta, upcoming] Mathematical solver: Gurobi • Guarantees to cover the full design space • Gives explicit bounds • Nevertheless: cannot solve to the global optimum Challenge: integrate optimization with stakeholders’ opinions
- 21. Challenges • Multi-objective optimization: weighted sum versus pareto optimization • No ”one size fits all”: trade-off different tasks, skills, strategies, etc. or optimally adapt • Models and input data: efficient, mathematical models, noisy data
- 23. www.annafeit.de @AnnaFeit Anna Feit Doctoral student, finishing end 2017 Research topics: • Text entry • UI Optimization I also know a bit about: • User modeling • Mid-air input • Eye tracking