Revue: Journal of Interesting Negative Results in NLP and ML

Thierry Hamon thierry.hamon at LIPN.UNIV-PARIS13.FR
Mon May 5 10:40:17 UTC 2008

Date: Fri, 18 Apr 2008 10:05:46 -0400 (EDT)
From: <szpak at>
Message-Id: <200804181405.KAA17279 at kamla.csi.UOttawa.CA>

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 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.

Vivi Nastase, EML Research
Stan Szpakowicz, SITE, University of Ottawa

Stan Szpakowicz, PhD, Professor __ 613-562-5800/6687
SITE, Computer Science _______ szpak at
University of Ottawa ____

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