Academic

Spent an hour going through outstanding feature requests on SourceForge, some mine, some not, and commented where I had something to say.

We have an invitation for a book chapter, but we're not clear on whether we have anything useful to contribute on the topic, or, if we do, what it might be. Discussed it for an hour and threw up some ideas; final decision tomorrow.

Discovered an error in the large-scale test of all the metrics, so I had to run it again (one line was missing from the end of the Quarto line set). Regenerated the appropriate output files, and finished off the presentation, then tested it on various browsers. Added some new JS code to manipulate the z-index of items so that whatever items are currently showing end up with the highest z-index, otherwise you can't interact with them (to scroll them, for instance).

Created a set of portable apps (windows) using Wine on a thumbdrive, and copied all the presentation data onto the drive, as well as an archive of the bibliography and the Apparatus Delphi prototype. Copied the same data onto a second thumb drive.

Lots of rethinking being done as I try to cast the text of the presentation into graphical format; I've ended up regenerating a bunch of the graphs to include two types of data on the same graph, for clarity and efficiency.

Also, while formatting the presentation, we learned that to make centring of an XHTML block element work reliably through CSS, you not only have to use margin-left: auto; margin-right: auto; you often also have to include left: 0; right: 0; (or some fixed values). This is necessary when the element is position: absolute.

Printed out various maps for finding the accommodation and the venues for the DH 2010 conference next week.

With GN's help, got the presentation code set up with our HCMC theme, using pure SVG for the logo, and coded the first three sections of the presentation (which are fairly straightforward). A Firefox 4 beta came out today, so we downloaded and tested that, and discovered that its JS engine is now on a par with Chrome, so we'll be able to use Firefox even for large presentations using this codebase in the future; version 3.6 was really unable to cope with the Coldesp presentation, so this is a good thing. It's especially so because it turns out that Chrome's SVG support leaves a lot to be desired; it seems to fail to handle the fill-opacity setting in text and tspan elements.

I've finished the first draft of the text of my talk, and in the process created all of the graphics I need to use. I might turn this into a word-processor document at some stage (it's plain text right now), and make a PDF of it available, but first I'll build the presentation from it. It's probably too long, but there will be parts I can skip if time is short.

I'm writing the actual prose text of my talk for this presentation, because I want to see how long it turns out to be (doubtless too long), and also to let the argument drive the presentation rather than the presentation materials driving the argument. I've done about two thirds of it today, and also begun converting some of the graphs into graphics I can use in the presentation. I may end up dropping a lot of content relating to the use of containment metrics in SC, because the Jaccard Distance calculation is more appropriate and relevant. That'll simplify things a bit.

I have a complete set of the tests based on the Lear data, and I've rewritten the XSLT to render it more usefully into a set of tables (over 100 pages of them at this point). I haven't been able to look too closely at it yet, but it seems to me that normalizing the data before running the USM comparison results in slightly better results (meaning a larger number of what look like intuitively useful matches before the weird ones start), but USM still doesn't achieve results as good as ShingleCloud. That said, USM is still faster, and still gets reasonably good results without normalization.

I've now expanded my Lear test script so that it includes all three types of ShingleCloud metric (containment averaged, Jaccard with word tokenization, and Jaccard with character tokenization), NCD, and two types of output from my USM library (text normalized and not normalized). That's running now. So far, it looks as though the normalization in USM adds very little to the execution time, so it still looks faster than SC; it remains to be seen whether it finds more candidate matches or not.