By Francesco Ricci, Kalina Bontcheva, Owen Conlan, Séamus Lawless

This e-book constitutes the refereed lawsuits of the twenty third foreign convention on consumer Modeling, edition and Personalization, UMAP 2015, held in Dublin, eire, in June/July 2015.

The 25 lengthy and seven brief papers of the learn paper music have been conscientiously reviewed and chosen from 112 submissions. The papers replicate the convention topic "Contextualizing the World", highlighting the importance and influence of consumer modeling and adaptive applied sciences on numerous daily program components corresponding to: clever studying environments, recommender platforms, e-commerce, ads, customized info retrieval and entry, electronic humanities, e-government, cultural history, and customized health.

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Extra info for User Modeling, Adaptation and Personalization: 23rd International Conference, UMAP 2015, Dublin, Ireland, June 29 -- July 3, 2015. Proceedings

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Of the remaining pages, 30% (6,718 pages) contained a mind wandering report. 6,237 of these reports were probe-caught reports, while 481 were self-caught reports. Of the probe-caught reports, 32% were positive instances of mind wandering. Only a subset of all users (78) provided self-caught reports of mind wandering, but all 178 users were included in the analysis when selecting negative instances of MW. 3 Model Building Both negative and positive instances of MW are tracked when using probe-caught reports, so it is readily apparent that the classification task involves distinguishing negative probe-caught reports from positive probe-caught reports.

Pages fell into four categories; self-caught pages, positive probe-caught pages, negative probe-caught pages, and non-report pages (pages with no report). Positive probe-caught pages were not considered further since the goal was to detect self-caught MW. Pages that included reports of both types were considered to be a self-caught page if the self-caught report occurred first, and vice versa. All self-caught pages were included in the models as positive instances of MW. Negative instances were taken to be (a) only negative probe-caught pages (PC No), (b) only non-report pages (NR), or (c) both negative probe-caught pages and non-report pages (PC No + NR).

LNCS, vol. 8538, pp. 301–313. Springer, Heidelberg (2014) 2. : A Visual Lambda-Calculator Using Typed Mind-Maps. In: International Conference on Computer and Electrical Engineering, pp. 250–255 (2008) 3. : An alignment equation for using mind maps to filter learning queries from Google. In: 2006. Sixth International Conference on Advanced Learning Technologies, pp. 153–155 (2006) 4. , Cunha, R. : Applying Mind Maps at Representing Software Requirements. Contributions on Information Systems and Technologies, 1 (2013) 5.

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