Read e-book online Advances in Artificial Intelligence: 27th Canadian PDF

By Marina Sokolova, Peter van Beek

ISBN-10: 3319064827

ISBN-13: 9783319064826

ISBN-10: 3319064835

ISBN-13: 9783319064833

This booklet constitutes the refereed court cases of the twenty seventh Canadian convention on man made Intelligence, Canadian AI 2014, held in Montréal, quality control, Canada, in could 2014. The 22 usual papers and 18 brief papers provided including three invited talks have been conscientiously reviewed and chosen from ninety four submissions. The papers hide a number of themes inside of AI, corresponding to: agent structures; AI functions; computerized reasoning; bioinformatics and BioNLP; case-based reasoning; cognitive versions; constraint delight; info mining; E-commerce; evolutionary computation; video games; info retrieval; wisdom illustration; laptop studying; multi-media processing; normal language processing; neural nets; making plans; privacy-preserving info mining; robotics; seek; shrewdpermanent images; uncertainty; consumer modeling; net applications.

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Read 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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Additional 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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83 based on the following formula: Ci = Cw,i (1) w The positional value for each sentence in a document is calculated as follows: Pi = (n − i + 1) ∗ Cmax n (2) Rhetorical Figuration as a Metric in Text Summarization 15 While n, i are the total number of sentences in a cluster of documents and the order number of a sentence in the cluster respectively, Cmax is the highest centroid value in the cluster. Note that the position value of the first sentence in the cluster is assigned Cmax since the first sentence tends to possess more important information than other sentences.

A new, mobile-based version of PHIS2 (PHIS2-M) has since been introduced, in order to make the PHIS accessible from a mobile-based platform. A quality-in-use measurement model was developed specifically for the MUI to evaluate the quality of the mobile-based version of PHIS2 (PHIS2-M) [12]. The MUI features were adapted in an intelligent way using an AI rule-based technique to match the requirements of the mobile device to the user model. The device recognizes the context at runtime, and the designer adapts the interface widgets based on preprogramming requirements.

The questionnaire contained two types of questions: general questions, which focused on personal information and were applicable to any application; and specific questions, which only apply to the applications tested. We have to point out here that the responses to the questions relating to personal information, such as age group, gender, domain experience, and smartphone experience, were collected during the formal testing of PHIS2-MA when the participant signed in to create a user name before starting the test.

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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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