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Semantic Computing SEMANTIC COMPUTING 10651_9789813227910_TP.indd 1 24/7/17 1:49 PM World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence ISSN: 2529-7686 Published Vol. 1 Semantic Computing edited by Phillip C.-Y. Sheu 10651 - Semantic Computing.indd 1 27-07-17 5:07:03 PM World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence – Vol. 1 SEMANTIC COMPUTING Editor Phillip C-Y Sheu University of California, Irvine World Scientific NEW JERSEY • LONDON • SINGAPORE • BEIJING • SHANGHAI • HONG KONG • TAIPEI • CHENNAI • TOKYO 10651_9789813227910_TP.indd 2 24/7/17 1:49 PM World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence ISSN: 2529-7686 Published Vol. 1 Semantic Computing edited by Phillip C.-Y. Sheu Catherine-D-Ong - 10651 - Semantic Computing.indd 1 22-08-17 1:34:22 PM Published by World Scientific Publishing Co. Pte. Ltd. 5 Toh Tuck Link, Singapore 596224 USA office: 27 Warren Street, Suite 401-402, Hackensack, NJ 07601 UK office: 57 Shelton Street, Covent Garden, London WC2H 9HE Library of Congress Cataloging-in-Publication Data Names: Sheu, Phillip C.-Y., editor. Title: Semantic computing / editor, Phillip C-Y Sheu, University of California, Irvine. Other titles: Semantic computing (World Scientific (Firm)) Description: Hackensack, New Jersey : World Scientific, 2017. | Series: World Scientific encyclopedia with semantic computing and robotic intelligence ; vol. 1 | Includes bibliographical references and index. Identifiers: LCCN 2017032765| ISBN 9789813227910 (hardcover : alk. paper) | ISBN 9813227915 (hardcover : alk. paper) Subjects: LCSH: Semantic computing. Classification: LCC QA76.5913 .S46 2017 | DDC 006--dc23 LC record available at https://lccn.loc.gov/2017032765 British Library Cataloguing-in-Publication Data A catalogue record for this book is available from the British Library. Copyright © 2018 by World Scientific Publishing Co. Pte. Ltd. All rights reserved. This book, or parts thereof, may not be reproduced in any form or by any means, electronic or me- chanical, including photocopying, recording or any information storage and retrieval system now known or to be invented, without written permission from the publisher. For photocopying of material in this volume, please pay a copying fee through the Copyright Clearance Center, Inc., 222 Rosewood Drive, Danvers, MA 01923, USA. In this case permission to photocopy is not required from the publisher. Desk Editor: Catherine Domingo Ong Typeset by Stallion Press Email: [email protected] Printed in Singapore Catherine-D-Ong - 10651 - Semantic Computing.indd 2 22-08-17 1:34:22 PM July 21, 2017 8:45:03am WSPC/B2975 Foreword World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence Foreword The line between computer science and robotics is continuing is realistic to expect that future robots are connected to the to be softened. On one hand computers are continuing to be world of knowledge, so as to interact with humans intelli- humanized and a large number of cyber-physical systems are gently as a collaborative partner to solve general as well as being developed to act upon the physical world. On the other domain specific problems. We call such intelligence robotic hand, the robotic community is working on future robots that intelligence. are versatile computing machines with very sophisticated It is for this reason that a marriage between Semantic intelligence compatible to human brain. Computing and Robotic Intelligence is natural. Accordingly, As a branch of computer science, semantic computing we name this encyclopedia the Encyclopedia with Semantic (SC) addresses the derivation, description, integration, and Computing and Robotic Intelligence (ESCRI). We expect the use of semantics (\meaning", \context", \intention") for all marriage of the two, together with other enabling technolo- types of resource including data, document, tool, device, gies (such as machine vision, big data, cloud computing, process and people. It considers a typical, but not exclusive, mobile computing, VR, IoT, etc.), could synergize more semantic system architecture to consist of five layers: significant contributions to achieve the ultimate goal of Artificial Intelligence. (Layer 1) Semantic Analysis, that analyzes and converts We believe that while the current society is information signals such as pixels and words (content) to meanings centric, the future will be knowledge centric. The challenge is (semantics); how to structure, deliver, share and make use of the large . (Layer 2) Semantic Data Integration, that integrates data amounts of knowledge effectively and productively. The and their semantics from different sources within a unified concept of this encyclopedia may constantly evolve to meet model; the challenge. Incorporating the recent technological advan- . (Layer 3) Semantic Services, that utilize the content and ces in semantic computing and robotic intelligence, the en- semantics as the source of knowledge and information for cyclopedia has a long term goal of building a new model of building new applications - which may in turn be available reference that delivers quality knowledge to both profes- as services for building more complex applications; sionals and laymen alike. (Layer 4) Semantic Service Integration, that integrates I would like to thank members of the editorial board for services and their semantics from different sources within a their kind support, and thank Dr. K. K. Phua, Dr. Yan Ng, Ms. unified model; and Catherine Ong and Mr. Mun Kit Chew of World Scientific . (Layer 5) Semantic Interface, that realize the user inten- Publishing for helping me to launch this important journal. tions to be described in natural language, or express in some other natural ways. A traditional robot often works with a confined context. If we Phillip Sheu take the Internet (including IoT) as the context and consider Editor-in-Chief the advances in clouding computing and mobile computing, it University of California, Irvine v This page intentionally left blankThis blank July 21, 2017 8:44:01am WSPC/B2975 content World Scienti¯c Encyclopedia with Semantic Computing and Robotic Intelligence CONTENTS Foreword v Part 1: Understanding Semantics 1 Open information extraction 3 D.-T. Vo and E. Bagheri Methods and resources for computing semantic relatedness 9 Y. Feng and E. Bagheri Semantic summarization of web news 15 F. Amato, V. Moscato, A. Picariello, G. Sperl{,A.D'Acierno and A. Penta Event identi¯cation in social networks 21 F. Zarrinkalam and E. Bagheri Community detection in social networks 29 H. Fani and E. Bagheri High-level surveillance event detection 37 F. Persia and D. D'Auria Part 2: Data Science 43 Selected topics in statistical computing 45 S. B. Chatla, C.-H. Chen and G. Shmueli Bayesian networks: Theory, applications and sensitivity issues 63 R. S. Kenett GLiM: Generalized linear models 77 J. R. Barr and S. Zacks OLAP and machine learning 85 J. Jin Survival analysis via Cox proportional hazards additive models 91 L. Bai and D. Gillen Deep learning 103 X. Hao and G. Zhang Two-stage and sequential sampling for estimation and testing with prescribed precision 111 S. Zacks Business process mining 117 A. Pourmasoumi and E. Bagheri The information quality framework for evaluating data science programs 125 S. Y. Coleman and R. S. Kenett (Continued ) July 21, 2017 8:44:01am WSPC/B2975 content World Scienti¯c Encyclopedia with Semantic Computing and Robotic Intelligence CONTENTS — (Continued ) Part 3: Data Integration 139 Enriching semantic search with preference and quality scores 141 M. Missiko®, A. Formica, E. Pourabbas and F. Taglino Multilingual semantic dictionaries for natural language processing: The case of BabelNet 149 C. D. Bovi and R. Navigli Model-based documentation 165 F. Farazi, C. Chapman, P. Raju and W. Byrne Entity linking for tweets 171 P. Basile and A. Caputo Enabling semantic technologies using multimedia ontology 181 A. M. Rinaldi Part 4: Applications 189 Semantic software engineering 191 T. Wang, A. Kitazawa and P. Sheu A multimedia semantic framework for image understanding and retrieval 197 A. Penta Use of semantics in robotics — improving doctors' performance using a cricothyrotomy simulator 209 D. D'Auria and F. Persia Semantic localization 215 S. Ma and Q. Liu Use of semantics in bio-informatics 223 C. C. N. Wang and J. J. P. Tsai Actionable intelligence and online learning for semantic computing 231 C. Tekin and M. van der Schaar Subject Index 239 Author Index 241 July 20, 2017 7:08:31pm WSPC/B2975 ch-01 World Scientific Encyclopedia with Semantic Computing and Robotic Intelligence Open information extraction † Duc-Thuan Vo* and Ebrahim Bagheri Laboratory for Systems, Software and Semantics (LS3Þ Ryerson University, Toronto, ON, Canada *[email protected] † [email protected] Open information extraction (Open IE) systems aim to obtain relation tuples with highly scalable extraction in portable across domain by identifying a variety of relation phrases and their arguments in arbitrary sentences. The first generation of Open IE learns linear chain models based on unlexicalized features such as Part-of-Speech (POS) or shallow tags to label the intermediate words between pair of potential arguments for identifying extractable relations. Open IE currently is developed in the second generation that is able to extract instances of the most frequently observed relation types such as Verb, Noun and Prep, Verb and Prep, and Infinitive with deep linguistic analysis. They
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