The University of Washington was one of several universities participating in Amazon’s pilot study of the Kindle DX to see whether the Kindle DX served as a suitable replacement for students’ textbooks. About 40 CSE students enrolled in a dozen Computer Science courses participated in the study. A number of articles published last summer (e.g., Forbes ) touted the advantages of the device for students, citing lower weight and cost compared to the paper editions of the same textbooks.

The results, unsurprisingly, were disappointing.

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Thanks to Fernando’s post on Probably Irrelevant, I discovered the IR Museum, an  interesting resource hosted on the SIGIR web site. The site was created to archive documents related to the IR community that are not found in the ACM Digital Library or other similar archives, and yet, are considered fundamental work to the field. The collection, as far as I can tell, includes the Cranfield reports (Cleverdon, 1962),  Rocchio’s PhD Thesis (Rocchio, 1966), a variety of SMART reports (ISR-11, ISR-12, ISR-13,  and ISR-15), and other things that are impossible to find.

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A couple of weeks ago I wrote about iAnnotate, a document annotation app for the iPad. On Friday, the folks who develop the app left a comment on the blog enumerating some of the changes made to program. In addition to redesigning the document view, the most significant change made it easier to import documents. Now not only can you download documents through a dedicated server that you run on the network (I run it on my laptop) but also from an integrated web browser. This makes it easy to collect PDF files and then to switch back to the reading mode of iAnnotate to read the newly-downloaded documents.

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Today is FXPAL’s 15th anniversary. While we’re young by the standards of research labs (IBM Watson was founded in 1945, (Xerox) PARC in 1970,  IBM Almaden in 1986, and MSR in 1991), we’ve managed to accumulate a pretty good record for our size. With an annual staff of 20-25 PhD-level researchers and a bunch of summer interns, we’ve consistently produced about 30 research publications a year on a variety of research topics ranging from multimedia to HCI to information retrieval. While no single post can do justice to the great work of so many people, here are some highlights.

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I was intending to write a post on the varied reasons mathematicians give for taking long walks as an aid to research. I couldn’t find my favorite quote, so instead I’m posting a search challenge.

I thought I remembered reading, in the book Littlewood’s Miscellany, something along the lines of the following advice:

Researchers spend the vast majority of their time feeling frustrated. To improve the ratio of time feeling fulfilled to time feeling frustrated, whenever you find a new result or succeed in completing a proof, take the time to enjoy it, preferably by taking a long walk.  Definitely don’t dive into the next problem, or go back and check the proof. There is plenty of time for that later.

However, it doesn’t seem to be in that book. Littlewood certainly approved of walking, and the tone of much of his advice is consistent with this quote, but this particular piece of advice doesn’t appear to be there.  I couldn’t find it in a web search either.

I would love to know the true source for this piece of wisdom.

A  Tcho chocolate bar to anyone who can track down the source!

Eric Fischer recently published a visualization of traffic in the Bay Area based on location and time data associated with photographs. It’s a lovely image that traces the major routes in the Bay Area and highlights points of interest to locals and tourists alike. The image is beautiful, reminiscent of sketches or studies done in preparation to painting.

But what about its effectiveness as a visualization? What does it tell us that we didn’t know?

Jeremy Pickens (wearing his curmudgeon hat) wrote:

Think about your own mental model of San Francisco, and where you think the interesting or appealing places are.  I.e. if you were visiting the city and/or out for the day taking pictures, where in the city would you go?  You’d probably go to Golden Gate Park, to anywhere along the water, and to the downtown shopping areas (the grid around and north of Market).  And that’s pretty much what the map shows, right?  So we don’t really learn much from this, do we?  It confirms our existing intuitions.

He is partially correct.

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Traditional models of academic publishing have been under attack from a number of directions, with factors such as the decreasing cost of publication and dissemination leading to the proliferation of online journals and alternative publishing models. One such alternative, straddling the border between  blog and refereed publication, is Not Relevant, a web site recently created by Ian Soboroff as a venue for publishing and discussing work related to information retrieval that might have been rejected by traditional publication venues.

The goal of Not Relevant is to provide a novel dissemination venue for research in information retrieval, particularly when that research does not fit well in existing channels. Not Relevant strives for open dissemination of research, to put that research into the wild quickly, and to foster open and public discussion of that research.

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There are lots of ways to display search results, and the familiar (if impoverished) ranked list of links with snippets is just one possibility. It doesn’t work particularly well for Twitter, for example because for many kinds of searches it’s hard to make sense of the tweets individually; instead, a more holistic approach is more appropriate.  I described in one such approach in Making Sense of Twitter Search (the position paper was co-authored with Miles Efron and was presented at a CHI 2010 workshop on microblogging) .

Paper.li is another approach to visualizing sets of Tweets. For a given topic or user, it identifies documents referred to by your followers and builds a two-column online newspaper-style layout out of those documents. It classifies documents by broad categories (media, education, technology, etc.) and prominent hashtags (e.g., #facebook), show the leading paragraphs or two of the document, and the person who tweeted it. Media such as YouTube videos are embedded directly into the layout. And, you can, of course, switch to a list view.

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Building effective search interfaces is hard, particularly when the goal is to support exploratory search rather than precision-oriented fact finding that the major search engines excel at. The challenge is to support a complex, evolving, information-rich task in a generalizable, understandable, and manageable way. We have some good ideas about how to make various components of information exploration interfaces; Marti Hearst’s book, for example, details much of the science and engineering that goes into good design for information seeking interfaces. None the less, the challenge of how to put these techniques into usable, effective and engaging interfaces that make it possible to do serious information seeking, remains.

A team of students at SIMS took a step in this direction with their Masters’ Thesis project called Migratory Words. The system allows people to search and browse a collection of news articles. Results are presented in a combination of visualizations and text lists that highlight terms, documents, and collections. The use terms and phrases that represent the ideas latent in the documents is a particularly welcome addition to traditional document-focused interfaces.

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It seems that the Twitter API function that returns  @mentions fails to return new-style retweets. I discovered this by accident after seeing references to tweets on my blog that TweetDeck didn’t show me in the @mentions column. I then looked on the Twitter site, and saw the same behavior there.

This seems like yet another problem with the RT API, and, like the lack of ability to add comments to a new style retweet, this behavior also seems unwarranted. It doesn’t really complicate the system to include new-style RTs of one’s tweets in @mentions, and it certainly makes for a more consistent interface.

If Twitter doesn’t fix it API, perhaps the good folks at TweetDeck could inject those missing tweets into the @mentions stream.