This volume aims to provide a reference to the development of robotic intelligence, built upon Semantic Computing, in terms of "action" to realize the "context" and "intention" formulated by Semantics Computing during the "thinking" or reasoning process. It addresses three core areas:
Ability to interface and interact with human in the form of natural languages and map them onto Semantic Services,
Understanding the (possibly naturally-expressed) intentions (semantics) of users and develop into plans to deliver the outcomes by means of robots,
Improve on the sophistication in a big data environment to develop the capability to process and analyze massive data on-the-fly.
Contents:
Foreword
Part 1: Understanding Semantics:
Goodness of Machine Learning Models (J R Barr)
Part 2: Data Science:
Goodness-of-Fit of Statistical Distributions (J R Barr and S Zacks)
Forensics: Assessing Model Goodness: A Machine Learning View (J R Barr and J Cavanaugh)
Diffusion Analysis (M Kim and M Hayakawa)
Part 3: Data Integration:
Network Analysis and GOLAP (J Jin and M Hayakawa)
Part 4: Applications:
Automatic Analysis of Microblogging Data to Aid in Emergency Management (S Manna)
Applications of Natural Language Processing (NLP) for Improving Classroom Learning Experiences Using Student Surveys (P Kuiper and K Hood)
A Semantic Recommendation System for Cancer-Related Articles (C C N Wang, Y-L Chung, I-S Chang and J J P Tsai)
Rapid Qualification of Mereotopological Relationships Using Signed Distance Fields (R Schubotz, C Vogelgesang and Dmitri Rubinstein)
Part 5: Robotic Intelligence:
