This year’s main Computational Linguistics conference ACL 2010 features a special category of negative-result papers, so there must be a need. Now as the deadline season for this year’s conferences is winding down, we invite you to revisit your less-than-successful experiences (even if we hope you had none). Consider sharing your interesting negative results with the community. We invite, nay, we welcome all submissions which meet the journal’s standards. Visit its Web site for more.
For the disinclined to surf, here are the essential points on the home page of the Journal of Interesting Negative Results in Natural Language Processing and Machine Learning:
“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.
Because of the nature of the journal, there should be good justification for trying out the ideas presented. The experiments reported should be shown in a manner that allows their reproduction. The negative results should be explained and justified, along with the reasons why the idea did not lead to the predicted results. The lessons learned should be clearly stated.”
All the best,
Vivi Nastase and Stan Szpakowicz