%0 Journal Article %1 reiter03lessons %A Reiter, Ehud %A Robertson, Roma %A Osman, Liesl M. %C Essex, UK %D 2003 %I Elsevier Science Publishers Ltd. %J Artificial Intelligence %K advice, health, nlg, smoking %N 1-2 %P 41--58 %R 10.1016/S0004-3702(02)00370-3 %T Lessons from a failure: Generating tailored smoking cessation letters %U http://dx.doi.org/10.1016/S0004-3702(02)00370-3 %V 144 %X is a Natural Language Generation ( ) system that generates short tailored smoking cessation letters, based on responses to a four-page smoking questionnaire. A clinical trial with 2553 smokers showed that was not effective; that is, recipients of a non-tailored letter were as likely to stop smoking as recipients of a tailored letter. In this paper we describe the system and clinical trial. Although it is rare for papers to present negative results, we believe that useful lessons can be learned from . We also believe that the community as a whole could benefit from considering the issue of how, when, and why negative results should be reported; certainly a major difference between and more established fields such as medicine is that very few papers report negative results.

@article{reiter03lessons, abstract = {{ is a Natural Language Generation ( ) system that generates short tailored smoking cessation letters, based on responses to a four-page smoking questionnaire. A clinical trial with 2553 smokers showed that was not effective; that is, recipients of a non-tailored letter were as likely to stop smoking as recipients of a tailored letter. In this paper we describe the system and clinical trial. Although it is rare for papers to present negative results, we believe that useful lessons can be learned from . We also believe that the community as a whole could benefit from considering the issue of how, when, and why negative results should be reported; certainly a major difference between and more established fields such as medicine is that very few papers report negative results.}}, added-at = {2010-12-17T18:47:41.000+0100}, address = {Essex, UK}, author = {Reiter, Ehud and Robertson, Roma and Osman, Liesl M.}, biburl = {https://www.bibsonomy.org/bibtex/2f57c7cd99ab56ac4fc5f180d59e5ba6e/mortimer_m8}, citeulike-article-id = {398598}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=767243.767245}, citeulike-linkout-1 = {http://dx.doi.org/10.1016/S0004-3702(02)00370-3}, citeulike-linkout-2 = {http://linkinghub.elsevier.com/retrieve/pii/S0004-3702(02)00370-3}, doi = {10.1016/S0004-3702(02)00370-3}, interhash = {c29661e457165cd70797dc4e349bb59b}, intrahash = {f57c7cd99ab56ac4fc5f180d59e5ba6e}, issn = {00043702}, journal = {Artificial Intelligence}, keywords = {advice, health, nlg, smoking}, month = {March}, number = {1-2}, pages = {41--58}, posted-at = {2005-11-17 12:25:04}, priority = {0}, publisher = {Elsevier Science Publishers Ltd.}, timestamp = {2010-12-20T11:11:25.000+0100}, title = {{Lessons from a failure: Generating tailored smoking cessation letters}}, url = {http://dx.doi.org/10.1016/S0004-3702(02)00370-3}, volume = 144, year = 2003 }