New PDF release: Biometric and Intelligent Decision Making Support

By Arturas Kaklauskas

ISBN-10: 3319136585

ISBN-13: 9783319136585

ISBN-10: 3319136593

ISBN-13: 9783319136592

This ebook offers various equipment for interpreting the physique language (movement, place, use of non-public area, silences, pauses and tone, the eyes, scholar dilation or constriction, smiles, physique temperature and so on) for larger figuring out people’s wishes and activities, together with biometric information collecting and analyzing. varied reports defined during this publication point out that sufficiently a lot info, info and data will be received by using biometric applied sciences.

This is the 1st, wide-ranging e-book that's committed thoroughly to the realm of clever choice help structures, biometrics applied sciences and their integrations.

This publication is distinct for students, practitioners and doctoral and master’s measure scholars in quite a few components and those that have an interest within the most up-to-date biometric and clever determination making aid difficulties and capacity for his or her resolutions, biometric and clever selection making aid platforms and the idea and perform in their integration and the possibilities for the sensible use of biometric and clever selection making help.

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Extra resources for Biometric and Intelligent Decision Making Support

Sample text

Association mining has been employed to identify the repairs performed in the field for a given symptom, whereas, text mining is used to infer repairs from the textual instructions mentioned in service documents for the same symptom. These in turn are compared and contrasted to identify the anomalous cases. The developed approach has been applied to automotive field data. 04). This knowledge, in the form of anomalies, can subsequently be used to improve the service/trouble-shooting procedure and identify technician training needs (Khare and Chougule 2012).

Froelich and Ananyan (2008) deliberate various decision support via text mining technologies (tokenization, morphological analysis, quality improvement using string similarity, part of speech tagging, collocation analysis, named entity recognition, word association, summarization and concept analysis, classification, clustering, dictionaries). Several decision support via text mining technologies are presented next in-brief (Froelich and Ananyan 2008): • Word Association. Word association involves the identification and representation of a relationship between any two words or phrases or entities.

Procedia Eng 54:615–624 Gao S, Wang H, Xu D, Wang Y (2007) An intelligent agent-assisted decision support system for family financial planning. Decis Support Syst 44(1):60–78 Garay-Vega L, Pradhan AK, Weinberg G, Schmidt-Nielsen B, Harsham B, Shen Y, Divekar G, Romoser M, Knodler M, Fisher DL (2010) Evaluation of different speech and touch interfaces to in-vehicle music retrieval systems. Accid Anal Prev 42(3):913–920 García-Cascales MS, Lamata MT (2007) Solving a decision problem with linguistic information.

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Biometric and Intelligent Decision Making Support by Arturas Kaklauskas


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