Some nice thoughts about scientific research:
Some nice thoughts about scientific research:
I’ve started trying out a new service, called Mendeley. The quickest way to describe it is a “last.fm for research;” they have a desktop client that can monitor the pdf files that you are reading, and an online presence where each user has a profile. (Read about them on their blog; my profile is here). So far, it seems that they are at a very early stage. However, the basic functionality (seeing/tagging/searching papers you read) seems quite nice. On the other hand, an obvious difficulty is that of extracting accurate meta-data from research pdf files.
The similarity between research papers and songs is quite striking. Think of it this way: songs (research papers) are made by musicians (authored by researchers), have a name (title), and are collected in albums (journals/conference proceedings). Both have a time of release; both can be tagged/described/loved/hated; both are blogged and talked about. Sometimes artists make music videos, sometimes researchers make presentations or demos. (more…)
I came across an interesting blog post by @HDrachsler, who I started following on twitter after this year’s RecSys conference. The post contains a recording of the question/answer time at the RecSys doctoral symposium (which I unfortunately did not attend). The clearest voice in the recording is Prof. Joseph Konstan, who (obviously, I know) has some very interesting things to say about collaborative filtering, recommender system research, and the state of the field. Here are some notes that I jotted down while I was listening: (more…)
We followed up the pitches with a brainstorming session on the future of mobisys seminars and collaborative work. Lots of great ideas emerged: we are looking forward to incorporating them into our seminar series in the near future!
Yesterday was the first day of RecSys 2008, and was dedicated to three very interesting tutorials:
1. Robust Recommender Systems. Robin Burke introduced the wide range of attacks that typical collaborative filtering algorithms are vulnerable to; scenarios that arise when people attempt to force, rather than express, opinions. An attack was strictly defined as a set of profiles intending to obtain excessive influence on others, which can be aimed at pushing (making recommendation more likely) or nuking (i.e. recommendation less likely) items. His talk was an interesting blend of attack strategies, knowledge that attackers need to have, and a high-level description of approaches aiming at preventing or fixing the system when attacked. Of course, there are strong overlaps between this work and work in other areas (p2p trust, adversarial information retrieval, search engine spam..); I particularly like this area as pushes the point that recommender systems are about people/dynamic datasets, and not just prediction.
2. Recent Progress in Collaborative Filtering. Yehuda Koren (who has recently moved from AT&T to Yahoo! Research) gave a tutorial about the leading approaches in the Netflix prize competition. The techniques he described blend matrix factorisation and neighbourhood models, and include a number of other factors (such as user biases and time) that result in techniques that have multiple-billions of parameters (and the resulting ranking of team BellKor in the competition). His work is remarkable and worthy of the progress prizes he has been awarded thus far. He also explored alternative techniques of evaluating recommender systems, explaining his take on evaluating top-N recommendation lists.
3. Context-Aware Recommendations. Gedas Adomavicius and Alex Tuzhilin introduced their work on incorporating context into recommender systems, including pre-, post-, and hybrid-filtering of recommendation algorithm results based on user context. A running example that was repeated throughout the tutorial was going to the theatre with your girlfriend on the weekend: if you always watch comedy, then your recommendations can be filtered to match what you did in previous instances of the same context (i.e. you can be recommended comedy). They have done a lot of cool stuff on multi-dimensional recommenders, extending the common rating scales into cubes of ratings, and stressed more than once that this is virgin territory. Their work is also impressive, but raised a few questions. For example, should context be described by a well-enumerated taxonomy? Moreover, if you always watch comedy at the theatre with your girlfriend on weekends, then why should you need a recommender system in the first place (especially a collaborative one- what happened to serendipity or diversity)? They have a number of papers that are worth reading before trying to answer these questions!
There is an interesting short video here about trusted computing. Consider it an amateur introduction to what a lot of recent research has been discussing, and perhaps a useful video to spark some discussion with non-research friends.
However, there is a twist in the short- a doubt about the utlity of trust, once trust decision are made by a machine rather than a person. Do you agree?
Partnership with Apple to make UCL the first UK university to offer
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If you are running particularly long experiments like me, or are looking for something to watch for 45 minutes, then I suggest this video on youtube: a documentary about truth and wikipedia. It features interviews with big pro- and anti- web 2.0 names, and discusses the extent to which sites like wikipedia encourage truth, freedom, and democracy (or mob-rule, lies, and social fragmentation).
I was recently reading Dorris Lessing’s Nobel Prize for Literature acceptance speech (full text here). It’s an excellent read, a story of storytelling, that recalls her experiences in Africa and the influence of books on a writer. I strongly recommend all to read it. However, as inspirational as it is, there is also a strong feeling of cynicism towards the culture heralded on by the technology revolution, and some points worth thinking about. Here is a short quote:
“We are in a fragmenting culture, where our certainties of even a few decades ago are questioned and where it is common for young men and women, who have had years of education, to know nothing of the world, to have read nothing, knowing only some speciality or other, for instance, computers.
What has happened to us is an amazing invention – computers and the internet and TV. It is a revolution. This is not the first revolution the human race has dealt with. The printing revolution, which did not take place in a matter of a few decades, but took much longer, transformed our minds and ways of thinking. A foolhardy lot, we accepted it all, as we always do, never asked: “What is going to happen to us now, with this invention of print?” In the same way, we never thought to ask, “How will our lives, our way of thinking, be changed by the internet, which has seduced a whole generation with its inanities so that even quite reasonable people will confess that, once they are hooked, it is hard to cut free, and they may find a whole day has passed in blogging etc?”
I found it strange how she describes the printing revolution as something good, by allowing “voices unheard” to wield their talent, but the internet revolution as something meaningless, fragmenting, and wasteful. It seems to either imply that publishers have been given the divine gift of knowing what is good to publish, or that people (are dumb, and) lack the collective knowledge to find what is worth reading. Is there no such thing as collective wisdom? Does a change of medium naturally imply a change in content and quality? Perhaps her words reflect Toffler’s predictions, or it is impossible for her to find any quality in the chaotic community that we call the web?
After all, her message came to me by means of blogs and online news. Any thoughts?
The GroupLens blog mentioned something I found very interesting; a Google/IBM partnership is offering university students (from a select number of universities) the chance to develop software for large-scale distributed systems. They will be offering students access to lots of dedicated clusters. The website even offers sample content to help lecturers develop their courses! There is also some stuff on web security. Maybe sometime soon this opportunity will come across the Atlantic..