By Dekang Lin (auth.), Atefeh Farzindar, Vlado Kešelj (eds.)
This publication constitutes the refereed lawsuits of the twenty third convention on synthetic Intelligence, Canadian AI 2010, held in Ottawa, Canada, in May/June 2010. The 22 revised complete papers offered including 26 revised brief papers, 12 papers from the graduate pupil symposium and the abstracts of three keynote displays have been conscientiously reviewed and chosen from ninety submissions. The papers are equipped in topical sections on textual content category; textual content summarization and IR; reasoning and e-commerce; probabilistic computer studying; neural networks and swarm optimization; computing device studying and knowledge mining; common language processing; textual content analytics; reasoning and making plans; e-commerce; semantic net; laptop studying; and knowledge mining.
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Additional resources for Advances in Artificial Intelligence: 23rd Canadian Conference on Artificial Intelligence, Canadian AI 2010, Ottawa, Canada, May 31 – June 2, 2010. Proceedings
Canadian AI 2010, LNAI 6085, pp. 16–27, 2010. © Springer-Verlag Berlin Heidelberg 2010 Offensive Language Detection Using Multi-level Classification 17 Squalid language: These phrases target sexual fetishes or physical filth of the reader. Slurs: These phrases try to attack a culture or ethnicity in some way. Homophobia: These phrases are usually talking about homosexual sentiments. Racism: These phrases intimidate race or ethnicity of individuals . Extremism: These phrases target some religion or ideologies.
Since the 10-fold cross-validation works on features selected from the entire dataset, this is different from the operation of a deployed package where the test instances will not participate in the feature selection process. To evaluate the performance in such more realistic situation, we have trained separately, then tested on a held-out (10%) randomly selected test file for system stability verification: at the same level we applied the method on 10% test set (same baseline) and trained the method based on the rest of the data, and we achieved the results shown in the second row in Tables 1 and 2.
Journal of Mathematical Psychology 44, 205–231 (2000) 6. : The Estimation of Probabilities: An Essay on Modern Bayesian Methods. MIT Press, Cambridge (1965) 7. : Do statistical inferences allowing three alternative decision give better feedback for environmentally precautionary decision-making. Journal of Environmental Management 85, 338–344 (2007) 8. : Rough set based decision model in information retrieval and ﬁltering. In: Third World Multiconference on Systemics, Cybernetics and Informatics (SCI 1999) and Fifth International Conference on Information Systems Analysis and Synthesis (ISAS 1999), vol.