Knowledge-Driven Analytics Impacting Human Quality Of Life Arijit Ukil Leandro Marin Antonio Jara John Farserotu Tata Consultancy Services University of Murcia University of Applied CSEM, Switzerland Kolkata, India Spain Sciences Western john.farserotu@csem.ch leandro@um.es Switzerland (HES-SO) arijit.ukil@tcs.com.com Switzerland jara@ieee.org Abstract human life would be impacted in long term that eventually influences the betterment to human society. The theme of this workshop is knowledge- driven analytics and systems that will attempt 2 Objective to ensure positive influence to society and quality of life. The likely areas are: managing The prime objective of this workshop is to bring and analysis of knowledge for human mental forward the applications and technologies that through and physical health condition improvement, knowledge-driven analytics bring positive outcomes to maximizing the benefits of social network the human life and to the world at large. For example, interactions while minimizing the ill-effects, knowledge-managed learning techniques have the assisting human decision making in financial capability of providing robust prediction of medical domain, controlled social network foot- condition, automated summarization, report generation, printing, behavioral understanding and minimization of diagnosis error, enabling remote subsequent necessary action recommendation, disease screening. It can predict the suicidal trend or ensuring personal data privacy preservation, as state of depression from analyzing Facebook posts, well as attempting to address few pertinent tweets or recent posted images. Prediction of questions: How will I be alerted before a psychiatric disorders like schizophrenia, which devastating financial decision? How can a physicians find difficult to anticipate would have doctor be given augmented knowledge on immense impact on millions of human life. Traditional diagnosis? All of us are different. Why we are coarse evidence driven medical treatment needs to be not given personalized treatment instead of more precise and personalized. Big data and average case treatment plan? How can we use availability of vast information invite severe data big data and knowledge mining for developing privacy attacks which can potentially ruin one’s life and sustainable societies by optimizing energy, reputation. One of the challenging applications is the waste and perishable resource management? controlled release of private data without How to prevent privacy breach? And many compromising the beneficial influence, prediction and others. subsequent prevention of cyber-attacks and privacy breach incidents. Knowledge-driven analytics will 1 Focus restrict an individual to venture into risky investments, traps of false social requests. The main focus of this workshop is to bring The goal of this workshop is to inculcate the proposals and insights that demonstrate the knowledge- realization of long-term co-existence of human-life with driven technologies, developments, applications for big data, artificial intelligence and deep analytics. ensuring improvement of human quality of life. The Powerful tools, applications and ever-increasing impact would be micro-level, where human life is knowledge sources will drive human life, its micro and impacted in daily basis and at macro-level where macro conditions for augmenting the human capabilities, minimizing the nuisances of infiltratory technologies and overall betterment of human experiences. We expect researchers in the field of knowledge management, artificial intelligence, data mining, Copyright © CIKM 2018 for the individual papers by the papers' privacy analytics will provide insights of technological authors. Copyright © CIKM 2018 for the volume as a collection by its editors. This volume and its papers are published under the Creative Commons License Attribution 4.0 International (CC BY 4.0). aspects as well as application-specific scenarios of [Ukil17A]A.Ukil, S. Bandyopadhyay, C. Puri, R. knowledge. Singh, A. Pal, A. Mukherjee. Heartmate: automated integrated anomaly analysis for effective remote cardiac health management. 3 Relevance IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), We are at the crucial juncture of welcoming the (2017): 6578-6579. knowledge-driven management of our life. The theme of CIKM 2018 “From Big Data and Big Information to [Ukil16] A. Ukil, S. Bandyopadhyay, C. Puri, R. Big Knowledge" is appropriately aligned to the Singh, A. Pal, KM Mandana. CardioFit: objective and goal of the workshop and rightly conveys Affordable Cardiac Healthcare Analytics for the message of apparent arrival of inflection point of Clinical Utility Enhancement. eHealth 360° big data analytics based industry solutions and research (2016): 390 - 396. outcomes. Knowledge-driven technologies and applications for improving human quality of life will [Puri17] C. Puri, R. Singh, S. Bandyopadhyay, A.Ukil, potentially enable long-term human-centric A.Mukherjee. Analysis of phonocardiogram convergence of futuristic applications. CIKM 2018 will signals through proactive denoising using provide the platform to the researchers engaged in novel self-discriminant learner. 39th Annual developing, implementing computational models and International Conference of the IEEE analysis of such applications and technologies to Engineering in Medicine and Biology Society present their works, interact with fellow researchers and (EMBC), (2017): 2753-2756. gain ideas. [Ukil17B] A. Ukil, U. Kumar Roy. Smart cardiac Many researchers from academia, industry and start- health management in IoT through heart ups are engaged in developing knowledge-driven intelligent systems and applications like prediction of sound signal analytics and robust noise medical condition from healthcare data, developing the filtering. IEEE 28th Annual International intelligent physical, emotional and mental diagnosis Symposium on Personal, Indoor, and Mobile systems, detecting incoherence human decisions and Radio Communications (PIMRC), (2017) actions, personalization of drug administration and [Fraser14] F. Graham D. Adrian DC Chan, James R. treatment, forecasting financial fraud or opportunities, Green, and Dawn T. MacIsaac. "Automated advising personalized retail and financial decision biosignal quality analysis for recommendation, deep learned systems, alert systems electromyography using a one-class support for social networking misuse, proactive identification vector machine." IEEE Transactions on data privacy breach. Such researchers and industry Instrumentation and Measurement 63, no. 12 persons would be interested to participate in this workshop. This workshop will promote collaboration (2014): 2919-2930. and discussion among scholars from the domains of [Puri16A] C.Puri et al.. iCarMa: Inexpensive Cardiac machine learning, knowledge management and Arrhythmia Management--An IoT Healthcare engineering, data science, bio-informatics, data privacy Analytics Solution. First Workshop on IoT- and data security, and related others. enabled Healthcare and Wellness Technologies and Systems (2016): 3-8. Acknowledgments Gim18] J. Gim, S. Lee, and W. Joo, A Study of Prescriptive Analysis Framework for Human Leandro Marin is partially supported by Research Care Services Based On CKAN Cloud. Journal Project TIN2017-86885-R from the Spanish Ministery of Sensors, (2018) of Economy, Industry and Competitivity and Feder [Puri16B] C. Puri et al. Classification of Normal and (European Union). Abnormal Heart Sound Recordings through Robust Feature Selection. IEEE Computing in References Cardiology, Vol. 43 (2016). [Thor13]C. Thornton, et al. Auto-WEKA: Combined [Ukil10] A. Ukil, J. Sen. Secure multiparty privacy selection and hyperparameter optimization of preserving data aggregation by modular classification algorithms. 19th ACM SIGKDD arithmetic. IEEE International Conference on international conference on Knowledge Parallel Distributed and Grid Computing discovery and data mining, (2013): 847-855. (PDGC), (2010): 344-349. [Ukil14] A. Ukil, S. Bandyopadhyay, A. Pal. Sensitivity [Sen11] J. Sen, S. Koilakonda, A. Ukil. A mechanism inspector: Detecting privacy in smart energy for detection of cooperative black hole attack applications. IEEE Symposium on Computers in mobile ad hoc networks. IEEE International and Communication (ISCC), (2014): 1- 6. Conference on Intelligent Systems, Modelling [Molina14] A. Molina-Markham, P, Shenoy, K. Fu, E. and Simulation (ISMS), pp. 338-343, 2011. Cecchet. and D. Irwin. Private memoirs of a smart meter. ACM BuildSys (2010): 61-66. [Ukil15] A. Ukil, S. Bandyopadhyay, A. Pal. Privacy for IoT: Involuntary privacy enablement for smart energy systems. IEEE International Conference on Communications (ICC) (2015): 536-541. [Sweeny02]L. Sweeney. Achieving k-anonymity Privacy Protection Using Generalization and Suppression. Int. J. of Unc. Fuzz. Know. Syst, (2002): 571 – 588. [Mach07]A. Machanavajjhala, D. Kifer, J, Gehrke, and M. Venkitasubramanian. l-diversity:Privacy beyond k-anonymity. ACM Trans. Knowl. Disc. Data, vol. 1, issue. 1 (2007). [Ukil12] A. Ukil, J. Sen, and S. Ghosh. An Efficient Distribution Sensitive Privacy for Real-time Applications. Computer Science and Convergence, LNEE, vol. 114, (2012): 81-91. [Ukil14] A. Ukil, et al. Lightweight security scheme for IoT applications using CoAP. International Journal of Pervasive Computing and Communications, Volume 10, Issue 4 (2014): 372-392. [Ukil11] A. Ukil, J. Sen, S. Koilakonda. Embedded security for Internet of Things. IEEE National Conference on Emerging Trends and Applications in Computer Science (NCETACS), (2011): 1- 6. [Gentry09]C. Gentry. Fully Homomorphic Encryption Using Ideal Lattices. ACM Symposium on Theory of Computing (STOC), (2009): 169- 178.