Victor Yingjie Chen
Victor received a Bachelor of Engineering and a Master of Information Technology. He studies as a PhD student in Simon Fraser University and his research combines data mining to compute implicit relations in large data collections with information visualization of neighbourhoods in the computed relations.
Publications by Victor Yingjie Chen (bibliography)
Qian, Cheryl Zhenyu, Chen, Victor Yingjie and Woodbury, Robert F. (2008): Developing a Simple Repository to Support Authoring Learning Objects. In International Journal of Advanced Media and Communication, 2 (2) pp. 154-173.
This paper reports our experience of designing a human-centric repository to support learning object authoring. The users of DesignPatterns.ca are designers who want to explore, communicate and share parametric modelling knowledge and strategies. Aiming to support such a community, we provided succinct functions to meet their evident needs, kept the effort of packaging and publishing to a minimum, and left space for user innovation. We used agile methods and negotiated process and design with users regularly. The paper records and critically reviews the process we followed and lessons we learned in this repository development.
© All rights reserved Qian et al. and/or Inderscience Publishers
Qian, Cheryl Zhenyu, Chen, Victor Yingjie and Woodbury, Robert F. (2007): Participant Observation can Discover Design Patterns in Parametric Modeling. In: ACADIA 2007: Expanding Bodies October 1-7, 2007, Halifax, Canada. pp. 230-241.
Chen, Victor Yingjie, Qian, Cheryl Zhenyu and Woodbury, Robert F. (2007): Visualizing Collaborative Filtering in Digital Collections. In: 11th International Conference of Information Visualization July 4-6, 2007, Zurich, Switzerland. pp. 203-210.
The NEAR (Navigating Exhibitions, Annotations and Resources) panel is a method of managing digital collections and user preferences through collaborative filtering and graphically revealing implicit data relations such as sharing, reference and similarity. It is implemented on AVIRE, an online multimedia repository. AVIRE supports semi-structured collections (exhibitions) which containing various resources and annotations. Its users are encouraged to contribute, share, annotate and interpret resources. Similar to the act of adding items into shopping carts in the e-commence applications, a user's activities of searching, organizing and interpreting data in AVI-RE are considered as evidence of user's preferences. The design process of NEAR was guided by several principles from the visualization literature. It implements new navigation and communication approaches that support discovery of relations. Having tested NEAR with several users, we further analyze the design, report the evaluation and consider its use in other applications.
© All rights reserved Chen et al. and/or IEEE Computer Society
Chen, Victor Yingjie, Qian, Cheryl Zhenyu and Woodbury, Robert F. (2007): Local Navigation Can Reveal Implicit Relations. In: Dong, Andy, Moere, Andrew Vande and Gero, John S. (eds.) CAAD Futures July 11-13, 2007, Sydney, Australia. pp. 403-416.
This paper intends to analyze, compare, understand and explore the data relations among a collection, the collected items and user-created meaning appearing in different digital applications. Details of such relations are introduced and investigated with reference to several actual systems. In order to represent these three components in a way easy for users to interpret, navigate and interact, we introduce NEAR, a localized graph visualization tool to help people browse, understand and manipulate information in a digital architectural repository A•VI•RE.
© All rights reserved Chen et al. and/or Springer
Qian, Cheryl Zhenyu, Chen, Victor Yingjie and Woodbury, Robert F. (2006): NEAR: Collaborative Filtering & Visualizing Information Relations in a Multimedia Repository. In: Butz, Andreas, Fisher, Brian D., Kruger, Antonio and Olivier, Patrick (eds.) Proceedings of the Sixth International Symposium on Smart Graphics July 23-25, 2006, Vancouver, Canada. pp. 236-241.
The NEAR (Navigating Exhibitions, Annotations and Resources) is a compact panel designed to help people navigating, searching and interacting in an information repository by visualizing implicit data relations such as sharing, reference and similarity. It is implemented on A•VI•RE, an online multimedia repository. A•VI•RE supports semi-structured collections (exhibitions) containing various resources and annotations. Its users are encouraged to contribute, share, annotate and interpret resources. Similar to the act of adding items into shopping carts in the e-commence applications, a user’s acts of searching and organizing and interpreting data in A•VI•RE are considered as evidence of the user’s preferences. The design process of NEAR was guided by several design moves analyzed from literatures. It implements new navigation and communication approaches that support discovery of relations.
© All rights reserved Qian et al. and/or Springer
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We have decided to give away world-class educational materials
because we believe that universal access to high quality education is key to the building
of peace, sustainable social and economic development, and intercultural dialogue.
To calculate just have much we have saved you, our wonderful readers, we compare our free encyclopedia to two
books we love:
$110: Human-Computer Interaction by Dix et al (a great textbook but without video interviews)
$116: Shneiderman's Designing the User Interface
(a great textbook but without video interviews).
As you are reading our encyclopedia on your iPad/tablet (and saving a few trees), we estimate that the price would be $90 if sold as an eBook.
With that number, we can calculate how much money we have saved our readers, based on calculating the number of readers.
How we calculate readership
Because of our online and tablet/iPad approach to publishing, we are able to precisely measure reading behaviour across hundreds of parameters in realtime: Anything from reading
speed, drop-off points in the text, reader demographics, and much more.
Based on our server logs and the Google Analytics API,
we calculate the number of readers as described in the calculation method below.
A reader is not the same as a simple pageview and a reader is not the same as a
website visitor (as described in our calculation method below).
We calculate readership for two types of readers:
- Readers that have read our whole encyclopedia, much the same way you read a printed book
- Readers that have reader an individual chapter
Calcalution method: How we define a reader
- First we use the Google Analytics API to get a report of the number of unique human visitors to a chapter/page. Google runs its business on ads and thus completely relies on the ability to distinguish between a human visitor and an automated request. If not, you could earn millions on automating clicks on Google Ads.
- We then compare that number to our Apache webserver logs, which report the much higher number of actual visits to a chapter/page (both human and automated). We calculate the difference in percent, which we call an "exaggeration factor", which we use in step 6 below.
- With a large part of the visitors excluded, we further exclude any visitor who:
- has not remained on the page for at least 3 minutes (this factor is calculated by recording visit durations of 1000 randomly selected visitors) or has not printed the page (i.e. has not visited the printerfriendly version of the chapter/page)
- has not scrolled the page (this factor is calculated by recording scroll movements on 1000 randomly selected visitors)
- We then further exclude "double readers", i.e. readers who read a portion of a chapter and then returns in,
say, a week or a month to read the rest.
Although this person's reading activity spans multiple server sessions, the person is only counted as a single reader.
We categorize a "double reader" as a visitor who:
- visits a page, or multiple pages, across multiple server sessions
- qualifies to be defined as a reader, cf step 1-3 above, in all server sessions
- uses the same originating IP address
- We then subtract 5% from the final number to counter-balance a last remaining factor, namely the situation where one reader reads a chapter on his/her tablet
using a WiFi connection (and counted as one reader) but then picks up his other tablet using a 3G dongle
(with another IP address) and re-reads some of the chapter. That will equal two readers, not one. We have no way
of calculating how many times this situation arises, but to be on the safe side we subtract 5%
from the final number.
- We then take half of the "exaggeration factor" from step 2 and substract from the final number. We do this for no rational reason. We do it only as a further measure to be certain that our number of readers is not inflated.
- To qualify as a reader who has read our whole encyclopedia - much the same way you read a printed book - that person must have qualified as a reader (cf. 1-6 above) of at least 80% of the encyclopedia chapters.
As a result, we have eliminated everything from automated requests to the more casual visitors. That leaves us with what we can safely call readers.
Changes to this page (author)
22 Feb 2010: Enabled abstracts to be shown on Victor Yingjie Chen's author page.16 May 2008: Author was added to the bibliography (approved by an editor)18 Feb 2008: Page was edited
11 Feb 2008: Author was added to the bibliography (approved by an editor)
11 Feb 2008: Author was added to the bibliography (approved by an editor)
09 Dec 2007: Added a picture of Victor Y. Chen
09 Dec 2007: Added a picture of Victor Yingjie Chen
09 Dec 2007: Added a picture of Victor Y. Chen
09 Dec 2007: Author was added to the bibliography (approved by an editor)
09 Dec 2007: Author was added to the bibliography (approved by an editor)
09 Dec 2007: Author was added to the bibliography (approved by an editor)
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