Showing posts with label academic. Show all posts
Showing posts with label academic. Show all posts

IEEE goes evil?

Posted in Labels: , , , , , , , | at 23:01

In November, the IEEE released a new copyright agreement, that is to be signed by the authors of all papers published by the organization since January 2011. The main novelty is that the authors are not allowed to publish final versions of their papers on-line. Fortunately, we still may post the versions accepted for print (with post-review corrections), which is still great, indeed. You can find the FAQ concerning the new policy here.

It seems the IEEE realizes that nowadays there is almost no need in their printed materials and the digital library as search engines manage to find papers posted by their authors. No doubt that they do not want to restrict dissemination of scientific results, but that is a question of their survival as a major publishing organization. The worst is they use the drug-dealer strategy: first they organize great conferences and journals (the majority of top venues in my field are run by IEEE), and allow authors to re-publish anything on-line ("the first hit for free"), then cut it off. Yes, one still may post an accepted version, but who knows what is their next step?

The IEEE motivate their decision by preserving the value of their database: "the IEEE is better able to track usage of articles for the benefit of authors and journals". One can object that there are big and growing open-access databases like Mendeley, where all the statistics is open and refined (the personal info of users is known). Also, not all institutions have an access to the library. For example, my university (the largest one in Russia) does not. And I cannot afford to pay $25 per paper.

What can we do about that? Sure, it is impossible to stop publish in IEEE venues, although the community can find the way around, as was demonstrated by the founders of JMLR, now the major journal in machine learning, which was created to cancel the overhead of the commercial publishing model. Matt Blaze encourages the researchers not to serve as reviewers for IEEE. As for me, I'm too young (as a researcher) to be a reviewer. But it also has effect on me: I am now preparing a final version for the proceedings published by the IEEE, and I doubt if there is any use in improving my paper (even given a quality review), assuming that majority of researchers will use the accepted version and will never see the revised one.

UPD (Mart 14, 2011). I should have misunderstood the new policy at first, Blaze's post and IEEE terminology somehow misled me. The accepted paper means accepted for print by the IEEE, not the submitted for review. So, you still can use review results to correct the paper and post it on-line, then submit for publishing, where the formatting will probably be adjusted. So, any meaningful part could be reflected in the on-line version. I have corrected the post now, so it may seem weird.

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Papers, citations, co-authorship, and genealogy

Posted in Labels: , , , , , , | at 10:10

This summer I accidentally found out that there are two papers citing our CMRT 2009 paper. I was excited a bit about that since they were the first actual citations of me, so I even read those papers.

The first of them [Димашова, 2010] was published in Russian by OpenCV developers from Nizhny Novgorod. They implemented cascade-based face detection algorithm that used either Local Binary Patterns (LBP) or Haar features. The algorithm was released within OpenCV 2.0. They cite our paper as an example of using Random Forest on the stages of the cascade. However, they implemented the classical variation with the cascade over AdaBoost.

Another citation [Sikiric et al., 2010] is more relevant since it came from the road mapping community. They address the problem of recovering a road appearance mosaic from the orthogonal views to the surface. They contrast their approach with ours in the way that theirs do not employ human interaction. In fact, we need human input for recognizing road defects and lane marking, rectification is done in the previous stage, which is fully automatic.

The rest of the post is devoted to some interesting metrics and structures concerning citations, co-authorship and supervising students.

Citations

The number of citations is a weak measure of paper quality. We can also go further and estimate the impact of a journal or a particular researcher based on the number of citations. A generally accepted measure is the journal impact factor, which is simply the mean number of citations by paper published in the journal for some period in time. Individual researchers could be evaluated by the impact factor of the journals they published in, though it is considered as a bad practice. Another not-so-bad practise is h-index. By definition, one's h-index equals H if there are at least H citations of his top H papers1. It has also been criticised widely.

So, citation-based scoring has a lot of flaws. But what can we use instead? Another interesting approach is introduced by ReaderMeter. They collect the information about the number of people who have added some paper to their Mendeley collections and compute something like h-index. Unfortunately, they recently excluded some papers from their database, so the statistics became less representative but more accurate.

Co-authorship and Erdős number

Paul Erdős was a Hungarian mathematician who published about 14 hundred research papers with 511 different co-authors. That's why he has a special role in bibliometrics. Erdős number is defined as a collaborative distance from a researcher to Erdős. More strictly, Wikipedia defines:
Paul Erdős is the one person having an Erdős number of zero. For any author other than Erdős, if the lowest Erdős number of all of his coauthors is k, then the author's Erdős number is k + 1.
My Erdős number is at most 7 (via Olga Barinova, Pushmeet Kohli, Philip H.S. Torr, Bernhard Schölkopf, John Shawe Taylor, David Godsil). To be honest, Erdős number system is primarily used for math papers. Even if we use the wider definition, it is not that beautiful, because there are not too many gates, e.g. all the vision community will probably connect to Erdős via the machine learning gate. Thus, the researchers who work on the edge will be closer. To illustrate this fact, David Marr probably had not any finite Erdős number during his lifetime (now he definitely has). So, we can introduce, say, Zisserman number for computer vision.2 According to DBLP, Andrew Zisserman has 165 direct co-authors so far. Now, my Zisserman number is 3, David Marr's is 4 (via Tomaso Poggio, Lior Wolf, Yonatan Wexler).

The movie industry have their own metrics, which is the Bacon number (after Kevin Bacon). The distance is established 1 if two actors have appeared in a single movie. Someone tried to combine those two to the Erdős-Bacon number. For some person, it is just a sum of her Erdős and Bacon numbers. Of course, very few people have a finite Erdős-Bacon number, since one should both appear in a movie and publish a research paper (and it is still not sufficient). Often they are possessed by researchers who consulted the filming crew and accidentally were filmed. =) Erdős himself has this number 3 or 4 (depending on the details of definition), since he starred in N is a Number (1993) and his Bacon number is thus 3 0r 4.

The person with the probably lowest Erdős-Bacon number is Daniel Kleitman, an MIT mathematician, who has appeared in one of my favourite movies Good Will Hunting (1997) along with Minnie Driver, who collaborated with Bacon in Sleepers (1996). Since Kleitman has 6 joint papers with Erdős, his Erdős-Bacon number is 3.

Surprisingly, Marvin Minsky has his Erdős number (4) greater than his Bacon number (2), which he obtained via The Revenge of the Dead Indians (1993) and Yoko Ono. Another strange example is the paedophile's dream Natalie Portman. She has graduated from Harvard, saying she would rather "be smart than a movie star". That's my kind of a girl! A neuroscience paper [Baird et al., 2002] brought Natalie Hershlag (her real name) Erdős number of 5, and then she appeared in New York, I Love You (2009) along with Kevin Bacon, so she reached the same Erdős-Bacon number as Minsky, i.e. 6.

UPD (Mart 13, 2011). There is a totally relevant xkcd strip.

Scientific genealogy

Finally, I tell about what is known as scientific genealogy. Every grown-up researcher has a PhD advisor, usually one, while an advisor can have a lot of students. Let's just use the analogy with parents and children. We get a tree (or a forest) representing the historical structure of science. The mathematics genealogy project aims to recover this structure.

I tried to track my genealogy back. Unfortunately, I failed to find who was Yury M. Bayakovsky's PhD advisor. But if consider Olga Barinova my advisor, I am the 11th generation descendant of Carl Friedrich Gauß. Nice ancestry, huh?

The similar project exists for computer vision. There are 290 people in the base, though there are duplicates (I've found five Vitorio Ferrari's :). It seems strange that some trees have depth as big as 5 (e.g. Kristen Graumann and Adriana Quattoni are the 5th generation after David Marr), though vision is a relatively young field.

1 Okay, take the supremum of the set if you want to stay formal
2 It seems that Philip Torr has already used that number.

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Mendeley news

Posted in Labels: , , , , , | at 11:53

Few months ago I posted about Mendeley, the reference management system. I've been using it all the time and I am really satisfied. It is much more convenient to have your papers on a server than on a flash drive. Also keeping meta-information about the papers makes dealing with them (exploring, reading, citing etc.) more pleasant.

In this month a major update was released and a monetizing scheme was introduced. There are now 3 tariff plans in addition to the free one that allows one to use up to 1Gb of server disk space. There are also restrictions on the max number of shared collections and the number of users per collection. It does not look critical after all: there are no features you cannot use in the free version, so the company seems not evil. However, on the sister project last.fm the radio feature became paid after years of free service, which caused many users drift to grooveshark.

The update has affected the design of the paper info right-hand bar, and the references bar was eliminated. They promise to rebirth the bar in the future releases. It was really unusable before. When you read a paper, it is handy to have the list of indexed references on the bar, especially if the reference-style citing is used (it is the major problem with reading papers from the screen: where the hell [42] is referencing to?) I hope the people in Mendeley realize it.

It would be great to have a possibility to find papers without leaving the application. In theory, you could drag a citation from the references bar to a collection, find its (more) precise details via Internet search, and you are likely to have the link, and if it is direct, you can add the pdf with the Add File dialog using the found URL. In practice, the found URLs usually are not direct, they refer to IEEE/ACM/Springer pages, where the paper could be downloaded (usually not freely). In the same time, the paper is likely to be available for free through the direct link on the author's homepage. Moreover, Google Scholar often finds them too, but Mendeley chooses indirect links.

Mendeley needs to be more "semantic" while working with authors and conferences. It stores the author name as it appears in the paper. When you want to filter your papers by author, you can see "Shapovalov, R", "Shapovalov, R.", "Shapovalov, Roman", "Shapovalov, Roman V." etc. in the list. There are bases like DBLP, Mendeley can build their own index, so the author should be identified. If we know the author (but not only her name appearance in the paper), we are able to filter Google Scholar results and retrieve the direct link to the paper hosted on the author/university site. Finally, it is feasible to create the system, where human don't need to find papers. If I see the reference, I can automatically retrieve the pdf in a few seconds. I want Mendeley to develop in this direction.

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The disruption of scholarly publishing [in Russia]

Posted in Labels: , , , , , , | at 10:39

You know, I am relatively new to the big science. The first 2-column paper I read was Antonin Guttman's paper about R-Trees.1 It was about 2.5 years ago. So, I've never used published journals or conference proceedings. I have been wondering why do they spend money to printing journals if the researchers usually publish their papers on their home pages. Recently, I've read the article about the disruption of scholarly publishing by Michael Clarke. The article is quite dragged out, so I summarize its ideas in the following paragraphs.

When Tim Berners-Lee came up with the idea of WWW in 1991, he thought of its purpose as some kind of scientific media, which would replace conferences and journals. Nowadays, the Internet is used for social networking, illegal distribution of music and pornography, but we still have journals and conferences off-line. Why?

The author indicates 5 main points:
  • Dissemination - journals distribute papers all over the world
  • Registration of discovery - to know who was the first, Popov or Marconi
  • Validation - to ensure that the results are correct; now provided by peer-review
  • Filtration - you are likely to read a paper from the journal with bigger impact factor
  • Designation - if you have publications on top conferences, you might be a cool scientist
The author argues that only the last point is critical for the modern system of journals and conferences. The others could be better handled with on-line services, we already have a lot of examples.

But in Russia, we don't rank scientists according to their citation index!2 (because we don't have one :) ) So, the designation problem is not solved here, and Russia is already ready to the new publishing system. Why do we still have journals? I don't know, probably the sluggishness of minds...

1 Actually, I had read this paper about Google before, but it accidentally was not 2-column formatted. :)
2 I am cunning a bit: some journals carry out designation purposes. I mean journals published by VAK. One should have at least one publication in such a journal to get Candidate of Science degree (Russian PhD equivalent). But the review process is usually lousy, there was also Rooter case with one of them.

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Mendeley: the reference management software

Posted in Labels: , , | at 14:55

Yesterday, a friend of mine Dmitry Konstantinov told me about Mendeley. His problem was he had got a lot of papers within his computer and needed to handle them efficiently. After digging the Internet, he found Mendeley reference management system. The system allows you to sort papers, extract the title, abstract, authors, and references from textual PDFs, automatically retrieve meta-information about them from services like CiteSeerx, annotate papers and even their paragraphs, tag papers, flag them as read/favourite etc. Full text search across all your library is very convenient too.


The project is based in London, and share some management with Last.fm. Unsurprisingly, they have a social network upon all that. You can share you paper collections, upload your articles, synchronize your library with Mendeley Web. A user has up to 500 Mb space on servers. Now I see, where the idea of SciPeople, Russian scientific network, comes from. I don't know if such networks are the future of science, but they are, however, worth paying attention.

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Science vs. Industry

Posted in Labels: , , , , , , | at 21:35

Yesterday I was called by an HR officer from NetCracker, my former employer. She told me they "have a lot of new activities", so now they "fulfil repeated recruiting" and suggested to return to NetCracker. It is really funny, because 1.5 years ago they told me that according to the corporate policy it was impossible to employ somebody who had left the company once. I politely rejected them, but the talk refreshed my memories about previous hesitations.


When I switched the company to Graphics & Media Lab, it was a hard decision. That time I firmly decided to prefer scientific career over industrial. I considered a lot of pros and cons to make the decision. Although they are often personal, I'd like to share my observations with you.

Advantages of research work:
  • When you work as a researcher, you invent something new instead of just coding different stuff. This job is creative, not just constructive.
  • When you work as a programmer, you result is just a code. You don't publish papers, no one knows about your results. Moreover, they are often proprietorial.
  • If you work as an office worker or a manager, you could be paid a lot of money, but you are supposed to work 24x7. It really sucks because you do really annoying paperwork or participate in meetings, but do not produce anything substantial. If you have a lot of money, you have no time or desire to spend them to anything interesting. That's the reason why my roommate Andrey Korolev left Shell.
  • When you work as a scientist, you should not learn all the boring technologies. You can't be a prominent Java programmer without knowing heaps of jXxx libraries, a number of frameworks and without having some useless certificates. Besides, your knowledge could be narrow, they are restricted by your employer's needs.
  • Scientists are mobile: they move from one university to another. Some universities do not prolong contracts with professors, even if they are very cool. For me, it seems boring to live all the life in one place. (Though you could be sent to business trips while you work at some big corporation)
  • If you work at university, you might have a teaching experience of some kind, which is useful for you, if you use it properly.
Advantages of industrial work:
  • The main advantage is a good salary. :) If you are not a complete geek, it does matter. Science is usually funded by grants, which is unstable.
  • Since your employer needs profit, you do something practical. You can be sure that you don't investigate some abstract stuff that will never be applied.
Trust or not, our lab combines advantages of both directions. We usually work on projects ordered by customers who pay for it. Of course, we select only those projects, in which we can get some scientific results. Actually, it is done automatically, because it is not profitable for a customer to pay us for coding. That's how applied science should work, I think.

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