Internet Technology (2011-2012) assignments are online
After one year here is another update regarding my Internet Technology class (see here for last year's update). Unfortunately it will also be the last one, at least for the class as it is now, because the master I was teaching this class for has been closed :-/. But hey, there are many ways in which knowledge can be shared and that master was only one, right?
So here they are, the new papers written by my dear students! This year fewer have been shared, but I think their quality kind of compensates the amount. So do not worry if you cannot access all of them and enjoy the fact that the ones you can read are willingly shared by students with a CC BY-NC-SA license :-) If you are interested in any of the topics let me know and I might try to put you in contact with the authors.
New year, new you
... starting from the blog theme. Of course I have just downloaded a ready made one, otherwise with my taste you would have probably gotten something painful for your eyes ;-)
New year's resolutions? Plenty. But after last year's ones, my main resolution is no promises :-). And no creativity-killer posts: I'll try to stay far away from those topics I know will stop me from writing instead of incentivating me. I'll try to make this fun and useful, first of all for me. And if you find something useful here too, well, good for you ;-)
Fist post of the year, first after a long while... And to leave you with some more food for thought than the one you would have just by reading news about my wordpress themes, here you are:
Alon, Uri: "How To Choose a Good Scientific Problem". Molecular cell doi:10.1016/j.molcel.2009.09.013 (volume 35 issue 6 pp.726 - 728).
Here's the abstract:
"Choosing good problems is essential for being a good scientist. But what is a good problem, and how do you choose one? The subject is not usually discussed explicitly within our profession. Scientists are expected to be smart enough to figure it out on their own and through the observation of their teachers. This lack of explicit discussion leaves a vacuum that can lead to approaches such as choosing problems that can give results that merit publication in valued journals, resulting in a job and tenure."
I found the paper very inspiring and I agreed with most of it. Here are few sentences I particularly liked:
- "A lab is a nurturing environment that aims to maximize the potential of students as scientists and as human beings."
- "The projects that a particular researcher finds interesting are an expression of a personal filter, a way of perceiving the world. This filter is associated with a set of values: the beliefs of what is good, beautiful, and true versus what is bad, ugly, and false."
- "... when one can achieve self-expression in science, work becomes revitalizing, self- driven, and laden with personal meaning."
What do you think about it? I think that this self-expression, this possibility of projecting my personal values in my work is one of the main reasons I have chosen to do it. Of course, this is also constraining me somehow: what happens when I work with others? What if there is a clash of values between me and my collaborators? Finally, one last big question arises: how much is this applicable for other job? Is there a chance for everyone to achieve this self-expression or only for someone? What about those who can't?
Ok, enough food for today ;-) One last link, which you might find interesting if you liked this paper too: Uri Alon Lab homepage, where you can find more materials for nurturing scientists.
Take care, have a great 2012!
Slides for “An integrated approach to discover tag semantics”
The slides of my presentation at SAC 2011 are available on SlideShare:
Just to have an idea on what the presentation is about, here's an excerpt of the paper's abstract and the link to the paper itself.
New paper: An integrated approach to discover tag semantics
Antonina Dattolo, Davide Eynard, and Luca Mazzola. An Integrated Approach to Discover Tag Semantics. 26th Annual ACM Symposium on Applied Computing, vol. 1, pp. 814-820. Taichung, Taiwan, March 2011. From the abstract:
"Tag-based systems have become very common for online classification thanks to their intrinsic advantages such as self-organization and rapid evolution. However, they are still affected by some issues that limit their utility, mainly due to the inherent ambiguity in the semantics of tags. Synonyms, homonyms, and polysemous words, while not harmful for the casual user, strongly affect the quality of search results and the performances of tag-based recommendation systems. In this paper we rely on the concept of tag relatedness in order to study small groups of similar tags and detect relationships between them. This approach is grounded on a model that builds upon an edge-colored multigraph of users, tags, and resources. To put our thoughts in practice, we present a modular and extensible framework of analysis for discovering synonyms, homonyms and hierarchical relationships amongst sets of tags. Some initial results of its application to the delicious database are presented, showing that such an approach could be useful to solve some of the well known problems of folksonomies".
Paper is available here. Enjoy! ;)
Harvesting Online Content: An Analysis of Hotel Review Websites
A new paper is out:
Marchiori, E., Eynard, D., Inversini, A., Cantoni, L., Cerretti, F. (2011) Harvesting Online Content: An Analysis of Hotel Review Websites. In R. Law, M. Fuchs & Francesco Ricci (Eds.), Information and Communication Technologies in Tourism 2011 – Proceedings of the International Conference in Innsbruck, Austria (pp. 101-112). Wien: Springer.
Find the paper here ;)
New (old) paper: “On the use of correspondence analysis to learn seed ontologies from text”
Here is another work done in the last year(s), and here is its story. In January, 2009, as soon as I finished with my PhD, I've been put in contact with a company searching for people to implement Fionn Murtagh's Correspondence Analysis methodology for the automatic extraction of ontologies from text. After clarifying my position about it (that is, that what was extracted were just taxonomies and that I thought that the process should have become semi-automatic), I started a 10 months project in my university, officially funded by that company. I say "officially" because, while I regularly received my paycheck each month from the university, the company does not seem to have payed yet, after almost two years from the beginning of the project. Well, I guess they are probably just late and I am sure they will eventually do that, right?
By the way, the project was interesting even if it started as just the development of someone else's approach. The good point is that it provided us some interesting insights about how ontology extraction from text works in practice, what are the real world problems you have to face and how to address them. And the best thing is that, after the end of the project, we found we had enough enthusiasm (and most important a Master student, Fabio Marfia... thanks! ;)) to continue that.
Fabio has done a great work, taking the tool I had developed, expanding it with new functionalities, and testing them with real world examples. The outcome of our work, together with Fabio's graduation of course (you can find material about his thesis here), is the paper "On the use of correspondence analysis to learn seed ontologies from text" we wrote together with Matteo Matteucci. You can find the paper here, while here you can download its poster.
The work is not finished yet: there are still some aspects of the project that we would like to delve deeper into and there are still things we have not shared about it. It is just a matter of time, however, so stay tuned ;-)
New (old) paper: “GVIS: A framework for graphical mashups of heterogeneous sources to support data interpretation”
I know this is not a recent paper (it has been presented in May), but I am slowly doing a recap of what I have done during the last year and this is one of the updates you might have missed. "GVIS: A framework for graphical mashups of heterogeneous sources to support data interpretation", by Luca Mazzola, me, and Riccardo Mazza, is the first paper (and definitely not the last, as I have already written another!) with Luca, and it has been a great fun for me. We had a chance to merge our works (his modular architecture and my semantic models and tools) to obtain something new, that is the visualization of a user profile based on her browsing history and tags retrieved from Delicious.
Curious about it? You can find the document here (local copy: here) and the slides of Luca's presentation here.