This volume contains the papers presented at the 23rd Canadian Conference on Arti?cial Intelligence (AI 2010). The conference was held in Ottawa, Ontario, fromMay31toJune2,2010,andwascollocatedwiththe36thGraphicsInterface Conference(GI2010),andthe7thCanadianConferenceonComputerandRobot Vision (CRV 2010). The Program Committee received 90 submissions for the main conference, AI2010,fromacrossCanadaandaroundtheworld.Eachsubmissionwasreviewed byuptofourreviewers.Forthe?nalconferenceprogramandforinclusioninthese proceedings, 22 regular papers, with allocation of 12 pages each, were selected. Additionally,26 shortpapers,with allocationof 4 pageseach,wereaccepted. The papers from the Graduate Student Symposium are also included in the proceedings:sixoral(fourpages)andsixposter(twopages)presentationpapers. The conference programfeatured three keynote presentations by Dekang Lin (Google Inc.), Guy Lapalme (Universit'edeMontr' eal), and Evangelos Milios (Dalhousie University). The one-page abstracts of their talks are also included in the proceedings. Two pre-conference workshops, each with their own proceedings, were held on May 30, 2010. The Workshop on Intelligent Methods for Protecting Privacy and Con?dentiality in Data was organized by Khaled El Emam and Marina Sokolova. The workshop on Teaching AI in Computing and Information Te- nology (AI-CIT 2010) was organized by Danny Silver, Leila Kosseim, and Sajid Hussain. This conference wouldnot havebeen possible without the hardworkofmany people.WewouldliketothankallProgramCommitteemembersandexternal- viewers for their e?ort in providing high-quality reviews in a timely manner. We thank all the authors of submitted papers for submitting their work,and the - thors of selected papers for their collaboration in preparation of the ?nal copy. ManythankstoEbrahimBagheriandMarinaSokolovafororganizingtheGra- ateStudentSymposium,andchairingtheProgramCommitteeofthesymposium. We are in debt to Andrei Voronkov for developing the EasyChair conference managementsystemandmakingitfreelyavailabletotheacademicworld.Itisan amazinglyelegantand functionalWeb-basedsystem,whichsavedus muchtime.

In recent years, online social networking has revolutionized interpersonal communication. The newer research on language analysis in social media has been increasingly focusing on the latter's impact on our daily lives, both on a personal and a professional level. Natural language processing (NLP) is one of the most promising avenues for social media data processing. It is a scientific challenge to develop powerful methods and algorithms that extract relevant information from a large volume of data coming from multiple sources and languages in various formats or in free form. This book will discuss the challenges in analyzing social media texts in contrast with traditional documents. Research methods in information extraction, automatic categorization and clustering, automatic summarization and indexing, and statistical machine translation need to be adapted to a new kind of data. This book reviews the current research on NLP tools and methods for processing the non-traditional information from social media data that is available in large amounts, and it shows how innovative NLP approaches can integrate appropriate linguistic information in various fields such as social media monitoring, health care, and business intelligence. The book further covers the existing evaluation metrics for NLP and social media applications and the new efforts in evaluation campaigns or shared tasks on new datasets collected from social media. Such tasks are organized by the Association for Computational Linguistics (such as SemEval tasks), the National Institute of Standards and Technology via the Text REtrieval Conference (TREC) and the Text Analysis Conference (TAC), or the Conference and Labs of the Evaluation Forum (CLEF). In this third edition of the book, the authors added information about recent progress in NLP for social media applications, including more about the modern techniques provided by deep neural networks (DNNs) for modeling language and analyzing social media data.