23 maggio 2008
JNIR – Journal of Interesting Negative Results
Da una email che mi e’ arrivata pochi minuti fa. Idea semplicemente fantastica, cosi’ come il logo.
We are happy to announce the on-line publication of the first article in the Journal of Interesting Negative Results in Natural Language Processing and Machine Learning. Please visit http://www.jinr.org and click on “articles”.
JINR is an electronic journal, with a printed version to be negotiated with a major publisher once we have established a steady presence. The
journal will bring to the fore research in Natural Language Processing and Machine Learning that uncovers interesting negative results.
It is becoming more and more obvious that the research community in general, and those who work NLP and ML in particular, are biased
towards publishing successful ideas and experiments. Insofar as both our research areas focus on theories “proven” via empirical methods,
we are sure to encounter ideas that fail at the experimental stage for unexpected, and often interesting, reasons. Much can be learned by
analysing why some ideas, while intuitive and plausible, do not work. The importance of counter-examples for disproving conjectures is
already well known. Negative results may point to interesting and important open problems. Knowing directions that lead to dead-ends in
research can help others avoid replicating paths that take them nowhere. This might accelerate progress or even break through walls!
We propose this journal as a resource that gives a voice to negative results which stem from intuitive and justifiable ideas, proven wrong
through thorough and well-conducted experiments. We also encourage the submission of short papers/communications presenting counter-examples to usually accepted conjectures or to published papers.
The journal’s scope encompasses all areas of Natural Language Processing and Machine Learning. Papers published in JINR will meet
the highest quality standards, as measured by the originality and significance of the contribution. They will describe research with
theoretical and practical significance. All theories and ideas will have to be clearly stated and justified by a deep literature review.
Nota a margine. Da oggi Talking Robots chiude i battenti. Lo fa con un podcast estremamente piacevole da ascoltare, nel quale vengono intervistate quattro persone, di diverse estrazioni sociali, che dicono la loro a riguardo della robotica. Ad ogni modo, pare che per fortuna non rimarremo orfani dei nostri podcast robotici. Dovremo semplicemente spostarci su Robots.
