Big Data Analytics for Human-Computer Interactions: A New Era of Computation

Innovation HCI Knowledge

Author(s): Kuldeep Singh Kaswan*, Anupam Baliyan*, Jagjit Singh Dhatterwal* and Om Prakash Kaiwartya * .

Pp: 266-300 (35)

DOI: 10.2174/9789815079937123030010

* (Excluding Mailing and Handling)

Abstract

Design thinking has a significant influence on innovation in business, education, health, and other vital fields. This involves human-centered approaches lijke fast prototyping, and abductive reasoning. There are many parallels and contrasts between design visualized and a path to the innovative design of Human-Computer Interaction (HCI). In this chapter, we will discuss the method of Hasse diagrams for structured learning domains visualizing the progress of a learner through this domain and reducing attrition through early risk identification, improving learning performance and achievement levels, enabling more effective use of teaching time, and enhancing performance learning design/instructional design.


Keywords: Empirical analyses, Grammar-based methods, Hasse diagrams, HCIKDD, Hashing method, Hyperbolic network trees, Internet slang, Linguistic detection techniques, LDA, Opinion mining, Parallel processing, Radar charts, Recommender systems, SVM, SHAP D2 algorithm, Semantic networks, Semantic compression, Vector space model, Web 2.0.

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