By Elizabeth Chang, Tharam Dillon (auth.), Harris Papadopoulos, Andreas S. Andreou, Lazaros Iliadis, Ilias Maglogiannis (eds.)
This publication constitutes the refereed court cases of the ninth IFIP WG 12.5 overseas convention on synthetic Intelligence functions and strategies, AIAI 2013, held in Paphos, Cyprus, in September/October 2013. The 26 revised complete papers provided including a keynote speech on the major occasion and forty four papers of eight collocated workshops have been conscientiously reviewed and chosen for inclusion within the quantity. The papers of the most occasion are geared up in topical sections on info mining, clinical informatics and biomedical engineering, challenge fixing and scheduling, modeling and determination aid structures, robotics, and clever sign and snapshot processing.
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Additional info for Artificial Intelligence Applications and Innovations: 9th IFIP WG 12.5 International Conference, AIAI 2013, Paphos, Cyprus, September 30 – October 2, 2013, Proceedings
Fig. 3. 3 Data Mining u to populate the ontology backbone and are stored iin a All player annotations are used database for further processsing, that includes statistical as well as data mining teechniques. g. ), and its statisttical significance, as well as high her-level association information governing them. Data mining and machin ne learning techniques will also be employed. The conceepts and attributes described earrlier will enable the transformation of the annotation seet of a given advertisement into a learning feature-value vector.
Presented at the Proceedings of the 1st ACM/IEEE International Conference on Cyber-Physical Systems, Stockholm, Sweden (2010) 14. : An AdaptiveDiscrete Event Model for CyberPhysical System. In: Analytic Virtual Integration of Cyber-Physical Systems Workshop, USA, pp. 9–15 (2010) 15. : Smart Grids: An Industrial Electronics Perspective. IEEE Industrial Electronics Magazine IEM-02 (2011) 16. : Trust and Reputation for Service-Oriented Environments. Technologies for Building Business Intelligence and Consumer Confidence.
However, the eﬀectiveness of the other methods are also high indicating that the formulation of VAA missing value problem as recommendation system is successful. In the near future we plan to implement the SVD approach of missing value estimation in our VAAs so as to improve recommendation eﬀectiveness by ﬁlling in unanswered questions. We are also going to investigate the eﬀectiveness of the compared algorithms by artiﬁcially increasing the sparsity of our datasets. Finally, comparison with other techniques for missing value estimation such as ML and simple imputation will be also investigated.