Download PDF by Marina Sokolova, Peter van Beek: Advances in Artificial Intelligence: 27th Canadian

By Marina Sokolova, Peter van Beek

ISBN-10: 3319064827

ISBN-13: 9783319064826

ISBN-10: 3319064835

ISBN-13: 9783319064833

This booklet constitutes the refereed lawsuits of the twenty seventh Canadian convention on synthetic Intelligence, Canadian AI 2014, held in Montréal, quality controls, Canada, in might 2014. The 22 typical papers and 18 brief papers offered including three invited talks have been conscientiously reviewed and chosen from ninety four submissions. The papers hide quite a few subject matters inside of AI, comparable to: agent platforms; AI functions; automatic reasoning; bioinformatics and BioNLP; case-based reasoning; cognitive versions; constraint delight; information mining; E-commerce; evolutionary computation; video games; details retrieval; wisdom illustration; computing device studying; multi-media processing; typical language processing; neural nets; making plans; privacy-preserving facts mining; robotics; seek; clever pictures; uncertainty; person modeling; net applications.

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Read Online or Download Advances in Artificial Intelligence: 27th Canadian Conference on Artificial Intelligence, Canadian AI 2014, Montréal, QC, Canada, May 6-9, 2014. Proceedings PDF

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Extra resources for Advances in Artificial Intelligence: 27th Canadian Conference on Artificial Intelligence, Canadian AI 2014, Montréal, QC, Canada, May 6-9, 2014. Proceedings

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Radhakrishnan HYP0: There is no significant difference between the effectiveness of PHIS2-M and the effectiveness of PHIS2-MA. HYP1: There is a significant difference between the effectiveness of PHIS2-M and the effectiveness of PHIS2-MA. HYPA0: There is no significant difference between the user satisfaction of the participant using PHIS2-M and using PHIS2-MA, in terms of the median of each feature for mobile users, in the case where it is the same for mobile adaptation users. HYPA1: There is a significant difference between the user satisfaction of the participant using PHIS2-M and using PHIS2-MA, in terms of the median of each feature for mobile users, in the case where it is not the same for mobile adaptation users.

Intelligent Systems. ISRL, vol. 17, pp. 149–185. Springer, Heidelberg (2011) 10. : Characterising Context for Mobile User Interfaces in Health Care Applications. Procedia Computer Science 10, 1086–1093 (2012) 11. : There is more to context than location. Computers & Graphics 23(6), 893–901 (1999) 12. : A New Quality-in-Use Model for Mobile User Interfaces. In: Proceedings of the 23rd International Workshop on Software Measurement, IWSM-MENSURA (2013) 13. : A Practical Guide to Usability Testing, 3rd edn.

Also, since measures of influence are used to evaluate research, better measures of influence could help us make better strategic decisions, improving processes ranging from hiring, funding, promotion, and award-giving, to the assessment of organizations and funding programs. Both quantitative and qualitative factors are commonly used to assess researcher influence. Quantitative measures based on citation counts, such as the hindex [3], provide a convenient and objective indicator of influence. But are these measures reliable?

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Advances in Artificial Intelligence: 27th Canadian Conference on Artificial Intelligence, Canadian AI 2014, Montréal, QC, Canada, May 6-9, 2014. Proceedings by Marina Sokolova, Peter van Beek


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