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Commonsense knowledge for Machine Intelligence - part 3

These are the slides of the tutorial on commonsense knowledge for machine intelligence, presented by Dr. Niket Tandon, Dr. Aparna Varde, and Dr. Gerard de Melo at the CIKM conference 2017.

*Part 3/3: Commonsense for smart cities*


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Commonsense knowledge for Machine Intelligence - part 3

  1. 1. Part 3: Applications and Open Issues 1 Commonsense for Machine Intelligence: Text to Knowledge and Knowledge to Text
  2. 2. Smart Cities • A smart city is an urban area that uses different types of electronic data collection sensors to supply information used to manage assets and resources efficiently [Source: Wiki] • Energy efficiency, ubiquitous information access, pollution control, transparent government, good healthcare etc. 2
  3. 3. Smart City Characteristics [Source: TU Wien 2015] 3
  4. 4. Potential Role of Commonsense Knowledge • Smart Environment: Commonsense & related concepts in pedestrian and traffic systems • Smart Government: Commonsense in mining urban legislation for transparency in govt. • Smart Living: Opinion mining with commonsense from social media data on health, safety etc. • Smart Mobility: Autonomous vehicles with commonsense knowledge • Smart People: Systems entailing commonsense for 21st century education • Smart Economy: Use of commonsense & world knowledge on economics in policy decisions [Note: These are just a few examples] 4
  5. 5. Commonsense for Smart Environment • Buses in Barcelona run on routes designed to optimize energy efficiency • Street lights in Amsterdam brighten & dim based on pedestrian usage • Make such systems smarter using commonsense knowledge & reasoning • This enhances Smart Environment [Source: TU Wien 2015] 5
  6. 6. Commonsense for Smart Government • Ordinances: Laws passed & enacted at local levels • Mine Web-based ordinance data to analyze issues addressed etc. • Commonsense to select relevant ordinances, interpret content, map ordinance to dept. etc. • Answer questions, e.g., Which dept. was most active in a given ordinance session? • This contributes to Smart Govt. A Local Law in relation to the date of submission by the Mayor of the proposed executive budget and budget message, the date of submission by the Borough Presidents of recommendations in response to the Mayor executive budget, the date of publication of a report by the director of the independent budget office analyzing he executive budget, the date by which the Council hearings pertaining to the executive budget shall conclude, the date by which if the expense budget has not been adopted, the expense budget and tax rate adopted as modified for the current fiscal year shall be deemed to have...... [Source: NYC Council Websites 2017; Du et al., 2017] 6
  7. 7. Commonsense for Smart Living • Opinion mining from social media, e.g., Twitter • Commonsense knowledge for simulating human judgement in mining tweets • Address health & safety issues w.r.t. Smart Living • E.g., Indonesian Peat Fires affected Singapore etc. • Pollutants PM2.5 (particulate matter, diameter < 2.5µm) harmful to lungs • Public tweeted on pollutant impacts & controls • Sentiment analysis for user satisfaction on health effects • Commonsense useful in tweet selection & analysis [Source: Forsyth T. 2014; Du, Emebo et al. 2016] 7
  8. 8. Commonsense for Smart Mobility • If autonomous vehicles have commonsense, they can make intuitive, logical decisions • This would avoid accidents e.g. Tesla Model S & truck in 2016 • Tesla confused truck with overpass due to height & tried going through it, crashing! • Commonsense can augment domain KBs to make autonomous vehicles smarter • This promotes Smart Mobility [Source: Driggs-Campbell et al. 2014, Persaud et al. 2017] 8
  9. 9. Commonsense for Smart People • 21st century education affected by technology • Computer literacy is crucial • Commonsense in relevant systems is helpful • Intelligent Tutoring Systems: more interactive; cater to different expertise levels • Writing aids in multiple languages: address collocations etc. • This promotes inclusiveness & fosters global education, enhancing Smart People [Source: Long et al. 2011, Park et al. 2008, Koedinger et al., 2013] 9
  10. 10. Commonsense for Smart Economy • Use commonsense with principles of economics for depoliticized transparent policy • Balance productivity & energy efficiency using commonsense knowledge of systems • Economic principle: “Free cooling can be used to reduce air conditioning in data centers” • Commonsense fact: “Provided location details are taken into account” • Economic principle: “More spending on public schools will improve student performance” • Commonsense fact: “As long as that spending is done in the classroom” [Source: Leef et al. 2007, Pawlish et al. 2014] 10
  11. 11. Further Research on Smart Cities & Commonsense • Optimize data centers for smarter economy • Embed more commonsense in street systems for smarter environment • Build better healthcare apps for smarter living • Enhance ITS, writing aids with commonsense facts, collocations for smarter people • Make autonomous vehicles at least as good as human drivers for smarter mobility • Improve overall urban legislation policies for smarter government 11
  12. 12. References • Driggs-Campbell K., Shia V., Bajcsy R., “Decisions for autonomous vehicles: Integrating sensors, communication, and control”, ACM HiCoNS 2014, pp. 59-60. • Du, X., Liporace, D. and Varde, A., “Urban Legislation Assessment by Data Analytics with Smart City Characteristics”, IEEE UEMCON 2017, To appear. • Du, X., Emebo, O., Varde, A., Tandon, N., Nag Chowdhury, S. and Weikum, G. Air quality assessment from social media and structured data: Pollutants and health impacts in urban planning, IEEE ICDE Health Data Mgmt. & Mining Workshop 2016, pp. 54-59. • Forsyth, T. “Public concerns about transboundary haze: a comparison of Indonesia, Singapore and Malaysia.”, Global Environmental Change 2014, 25:76-86. • Koedinger, K., Brunskill, E., Baker, R., McLaulin, E. and Stamper, J., New Potentials for Data-Driven Intelligent Tutoring System Development and Optimization, AI Magazine 2013, 34(3): 27-28. • Leef, G., Smart Economics: Commonsense Answers to 50 Questions about Government, Taxes, Business and Households, Foundation for Economic Education (FEE) 2007. • Long, P., Siemens, G., Penetrating the fog: Analytics in learning & education, Educause Review 2011, 46(5): 31-40. • New York City Council - Legislation,, 2017 • Park, T., Lank, E., Poupart, P. and Terry, M., Is the sky pure today - awkchecker: An assistive tool for detecting and correcting collocation errors. ACM Symposium on User Interface Software and Technology 2008, pp. 121–130. • Pawlish, M., Varde, A., Robila, S. and Ranganathan, R., A call for energy efficiency in data centers, SIGMOD Record 2014, 43(1): 45-51. • Persaud, P., Varde, A. and Robila, S., “Enhancing Autonomous Vehicles with Commonsense: Smart Mobility in Smart Cities”, IEEE ICTAI Smart Cities Workshop 2017, To appear. • Vienna University of Technology (TU Wien), European Smart Cities, Tech. Rep., Vienna, Austria 2015. 12
  13. 13. Tutorial Summary • Part 1: Acquiring Commonsense Knowledge • What is commonsense • Representing commonsense knowledge (CSK) • Processes in acquisition of CSK • Evaluation methods • Part 2: Detecting and Correcting Odd Collocations in Text • Meaning of collocations • Treatment of odd collocations • Linguistic classification approaches • Tools for detection and correction • Part 3: Applications and Open Issues • Smart cities and their characteristics • Role of commonsense to enhance smart city characteristics • Specific applications with scope for further research 13
  14. 14. Conclusions • Commonsense has made people smarter J • Commonsense is making machines smarter! • Commonsense will make smart cities smarter… 14
  15. 15. Questions 15