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I will be at CHI 2010: 28th ACM Conference on Human Factors in Computing Systems in Atlanta, GA from April 10 – 16.

On Sunday, my student Dongwoo Kim will present our paper at the Microblogging workshop. Another student, Sunjun Kim, has a work-in-progress poster. And I am a co-author of a paper for the “Know Thyself” Personal Informatics workshop. Finally, I will be chairing a session “Cooking, Classrooms, and Craft” on Thursday morning.

Of course, I am looking forward to attending sessions, meeting friends, and generally having fun. ๐Ÿ™‚

Here are our papers:

Dongwoo Kim, Yohan Jo, Il-Chul Moon, and Alice Oh. Analysis of Twitter Lists as a Potential Source for Discovering Latent Characteristics of Users. Workshop on Microblogging at the ACM Conference on Human Factors in Computer Systems (CHI 2010).

Younkyung Lim, Alice Oh, Tekjin Nam, and Kee-Eung Kim. Personal Informatics for Discovering Human-Centered Lifecare System Opportunities. Workshop on Know Thyself at the ACM Conference on Human Factors in Computer Systems (CHI 2010).

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My students Yohan, Dongwoo, and I visited Princeton two days ago. (Now we’re at Carnegie Mellon, which may be the topic of my next blog post.) Our original plan was just to visit CMU for some meetings about a collaboration effort. But we thought it would be a much better plan to add another fruitful meeting since we are spending thousands of dollars on plane tickets and many many hours traveling from Korea to the US east coast.

Since we have been working with topic models for the last six months, I thought David Blei at Princeton would be the best person to visit. He accepted my request, and on top of that, invited us to give a talk at his machine learning reading group. Although we don’t yet have fancy results, we gave a presentation that summarizes our research goals, preliminary results, discussion questions, and future plans. We also had a separate meeting with Dave which led to helpful discussions and neat ideas. Dave was a gracious host and answered lots of our questions even though he had a very jam-packed day because it was the visit day for Princeton CS new admits. It was a great experience for us, and we will follow up on our discussions with Dave by trying out some new ideas for LDA evaluation and topic-sentiment model.

Here are the slides from the presentation. (Yohan and I made & delivered the talk, Dongwoo and Hyunjong contributed to the results in the talk.)
Talk @ Princeton, March, 2010

The readings associated with the presentation are:

J. Chang, J. Boyd-Graber, S. Gerrish, C. Wang, and D. Blei. ย  ย Reading tea leaves: How humans interpret topic models. Neural Information Processing Systems, 2009.

C. Lin and Y. He. Joint Sentiment Topic Model for Sentiment Analysis. CIKM 2009.

If you’re interested in learning about LDA, Dave’s tutorial is great.

I am co-organizing a workshop located at the IEEE International Conference on Social Computing (SocialCom-2010). Here I pasted the top portion of the workshop description.

Call For Papers

We solicit research papers, works-in-progress, and position papers. Click here for the CFP in PDF.

Important Dates (US EDT)

Submission Deadline: May 1, 2010
Notification of Acceptance: June 8, 2010
Final Paper Due: June 15, 2010

1. Workshop Overview

This is a workshop at IEEE International Conference on Social Computing (SocialCom-2010), and the goal of the workshop is bring together researchers from various disciplines to discuss ways to find synergies between text analysis and network analysis. The workshop will contribute to Social Computing by

  1. initiating a dialogue about and an in-depth look at the methodologies used in social network analysis and text analysis
  2. discussing holistic approaches for combining network and text analysis
  3. sharing and defining needs for data sets that include content and metadata
  4. illustrating informative data analysis results from the combination of text and network analysis
  5. presenting novel applications combining text and network analysis including their validations

Click here for more information.

Taesik (my husband and a colleague in the Industrial & Systems Engineering Department) teaches a graduate course on health care delivery. Part of that course discusses health information, such as Electronic Health Records, Personal Health Records, and online health information. I volunteered to give a lecture on health information on the Web: what the current status is, what improvements can be made so that users can get better health information from the Web, and how some computational methodologies can be applied to health information on the Web.

I did this in part because Taesik is suffering from a wisdom tooth extraction procedure, and it was a win-win-win situation. I gave him a couple of days to recover from the operation without having to give a lecture. I had a good time preparing for and delivering the lecture, and at the same time, I got to organize my thoughts about applying the ideas and methods used in our lab to health information. And I think, for the most part, students appreciated this change of perspective, from a systems engineering point of view to a computer science point of view.

I spent quite a long time preparing the presentation, so I want to share it with everyone here. Note that it is not a very technical talk. It’s intended to serve a general audience.

The Social Web and Health Information: A Computational Perspective

While browsing through the blogs on the left (Blogs I Read), I found a recent JAIR paper by Peter Turney on Vector Space Models (VSM). Peter Turney is a well-known expert in the field of information retrieval (IR), so I had high hopes for this paper. Indeed, it is a great paper! I read through it pretty quickly (so I can get some sleep tonight), and it seems to be jam packed with insights, history, mathematical and technical details, pointers to tools, and lots and lots of very good references. This one is a keeper for weeks so I can get a thorough reading of it and many of the papers in the references section.

P. D. Turney and P. Pantel (2010) “From Frequency to Meaning: Vector Space Models of Semantics”, Journal of Artificial Intelligence Research, Volume 37, pages 141-188

http://www.jair.org/papers/paper2934.html

As bloggers, we are aware that there must be good blogs out there that we don’t know about. Putting aside the question of, do you really want to read another blog?, here is an academic paper on recommending blogs based on some query words. This problem is different from the traditional query-search on the Web because, well, blogs are different from webpages. Read the paper to find out more:

J. Arguello, J. L. Elsas, J. Callan, and J. G. Carbonell. (2008.) “Document representation and query expansion models for blog recommendation.” In Proceedings of the Second International Conference on Weblogs and Social Media.

This is much closer to my research than most other posts in the blog… From Daniel Tunkelang (of Endeca) ‘s blog.

Symposium on Semantic Knowledge Discovery, Organization and Use, Day 1

Posted using ShareThis

Here is something interesting. It is a new way to explore and browse data. David is a friend through MIT, and though he and I both graduated, his work keeps me interested. I couldn’t figure out how to embed a Vimeo video here, so you’ll just have to click on the link to view it. Instead of trying to explain what Freebase does, I’ll let him do the talking. ๐Ÿ™‚

Freebase Parallax: A new way to browse and explore data from David Huynh on Vimeo.

Users & Information Lab @ KAIST

Users & Information Lab @ KAIST

I just made this logo (and updated versions) for our Users & Information Lab. I possess very very little artistic creativity, so this is pretty much all I could come up with. Any good graphic designers out there?

Our research statement is:

We engage in active research for delivering information that satisfies the user. We strive to re-define what it means for information to be relevant–to go above and beyond the popular notions of word- and phrase-based queries and page ranks. We ponder about re-representing the user–to understand and model at a deeper and higher level than preferences and profiles.

Stay tuned for our website. We just ordered a server. ๐Ÿ™‚