The "Help" user interface

It is sad that this paper is still relevant today. Written more than ten years ago, it describes the shortcomings of GUIs that we use today and offers an alternate approach:

http://www.fywss.com/plan9/plan9man/12help.ps.gz

The system described here is a precursor to the "acme" user interface that is currently shipped with plan9 and available on UN*X through
http://swtch.com/plan9port/.

Mapping weblog communities

It's been a while since I posted here, but this topic has been on my mind for a while. I'm attempting to discern interesting links within the InfosecDaily blog roll, aking to how Blogdex or Popdex does it. I have been reading a few papers on the subject and have a failing implementation at this point, but I need to go back to the drawing board. This paper caught my eye because it's a similar problem and problem-space. While it contains a few uninformed perceptions and conclusions about blog communities, overall it's just community discovery.

Websites of a particular class form increasingly complex networks, and new tools are needed to map and understand them. A way of visualizing this complex network is by mapping it. A map highlights which members of the community have similar interests, and reveals the underlying social network. In this paper, we will map a network of websites using Kohonen’s self-organizing map (SOM), a neural-net like method generally used for clustering and visualization of complex data sets. The set of websites considered has been the Blogalia weblog hosting site (based at http://www.blogalia.com/), a thriving community of around 200 members, created in January 2002. In this paper we show how SOM discovers interesting community features, its relation with other community-discovering algorithms, and the way it highlights the set of communities formed over the network.

Source: Mapping weblog communities, Juan J. Merelo-Guerv&oaccent;s, Beatriz Prieto. Fatima Rateb, and Fernando Tricas.

Content-rich biological network constructed by mining PubMed abstracts.

I suppose this might work for a variety of well formed abstracts. Someone could turn it loose on Citeseer and see what happens ... I've felt that the burgeoning quantity of data means that we have to work hard to jump across niches if we are to grow and prevent duplication of effort, to actually find progress, and keep ourselves inspired. Something like this might help.

The integration of the rapidly expanding corpus of information about the genome, transcriptome, and proteome, engendered by powerful technological advances, such as microarrays, and the availability of genomic sequence from multiple species, challenges the grasp and comprehension of the scientific community. Despite the existence of text-mining methods that identify biological relationships based on the textual co-occurrence of gene/protein terms or similarities in abstract texts, knowledge of the underlying molecular connections on a large scale, which is prerequisite to understanding novel biological processes, lags far behind the accumulation of data. While computationally efficient, the co-occurrence-based approaches fail to characterize (e.g., inhibition or stimulation, directionality) biological interactions. Programs with natural language processing (NLP) capability have been created to address these limitations, however, they are in general not readily accessible to the public. RESULTS: We present a NLP-based text-mining approach, Chilibot, which constructs content-rich relationship networks among biological concepts, genes, proteins, or drugs. Amongst its features, suggestions for new hypotheses can be generated. Lastly, we provide evidence that the connectivity of molecular networks extracted from the biological literature follows the power-law distribution, indicating scale-free topologies consistent with the results of previous experimental analyses. CONCLUSIONS: Chilibot distills scientific relationships from knowledge available throughout a wide range of biological domains and presents these in a content-rich graphical format, thus integrating general biomedical knowledge with the specialized knowledge and interests of the user. Chilibot http://www.chilibot.net can be accessed free of charge to academic users.

Source: Content-rich biological network constructed by mining PubMed abstracts., Chen H, Sharp BM. BMC Bioinformatics. 2004 Oct 08;5(1):147. You can also view the paper on BioMedCentral.

Lion's Commentary on UNIX

The infamous Lion's commentary is now available at


http://www.ercb.com/feature/feature.0067.html
or

http://www.lulu.com/content/99701

This book contains the entire source code of UNIX sixth edition with commentary.

If you're an OS buff, into retro computing and unix history or just trying to impress your friends, you should have this on your bookshelf.

Itanium - A System Implementor's Tale

https://www.disy.cse.unsw.edu.au/papers/disy/Gray_CCMH_05.pdf

This paper discusses some challenges faced by systems implementors when using the itanium. One of the more interesting sections discusses hand tuning the IPC mechanism in the L4 kernel. By hand-scheduling the code they were able to achieve better absolute (wall-time) and cycle performance than has been achieved on any other processor. A good read.