CONCEPT GENERATION SUPPORT BY CONCEPTUAL BLENDING MULTI AREA INSPIRATION SEARCH

CONCEPT GENERATION SUPPORT BY CONCEPTUAL BLENDING: MULTI-AREA INSPIRATION SEARCH DO THANH MAI NATIONAL UNIVERSITY OF SINGAPORE 2013 CONCEPT GENERATION SUPPORT BY CONCEPTUAL BLENDING: MULTI-AREA INSPIRATION SEARCH DO THANH MAI B.Eng (Hons.), NUS A THESIS SUBMITTED FOR THE DEGREE OF MASTER OF ENGINEERING DEPARTMENT OF INDUSTRIAL AND SYSTEM ENGINEERING NATIONAL UNIVERSITY OF SINGAPORE 2013 DECLARATION I hereby declare that the thesis is my original work and it has been written by me in its entirely I have duly acknowledged all the sources of information which have been used in the thesis This thesis has also not been submitted for any degree in any university previously _ Do Thanh Mai 23 August 2013 i ACKNOWLEDGEMENT I would not have enough courage to go into this branch of research without encouragement and tremendous support from A/Prof Poh Kim Leng His ideas, exemplary guidance, and most importantly, his belief in new adventures, have ignited my passion, conceptualized the project and kept me moving forwards, overcoming moments of doubts, uncertainty and disappointment in the past one year In addition, he is a true mentor who cares and gives me advice on coursework and other student matters such as finance and careers I have learnt and grown up to be an independent, critical thinker in new domains of Computer Science, Cognitive Science Although his influence is probably unknown to him, my deepest gratitude is with A/Prof Poh I am grateful for the support from the Department and University: French Double Degree Program committee for giving me tuition waiver for one year; Lai Chun, Weiting and Steven for supporting me with administration procedures and ISE Department for providing me with research facility I thank almighty my family and friends for their constant encouragement without which this assignment would not be possible I dedicate this document to my mother Thank you for giving me life, for letting me go and for sustaining me with shower of unconditional love always I would like to send special thanks to my close friends Hong Nhung and Lam Thanh for always being by my side Finally, I extend heartfelt thanks for my loving, supportive and patient dearest Despite our long distance apart, he has shared my wildest dreams He constantly provides me with ideas, takes care of my health and enlightens my every day with the brightest sunshine Thank you for being my life-long companion whom I treasure every single day ii CONTENT DECLARATION i ACKNOWLEDGEMENT ii CONTENT iii SUMMARY vii LIST OF TABLES ix LIST OF FIGURES x INTRODUCTION 1 1.1 Brief introduction to Concept Generation Support System 1.2 Research Questions, Scopes and Approaches of the Book 1.3 Historical Background and Contribution 1.3.1 Concept Generation System based on Conceptual Blending Framework: Multi-area Inspiration Search 1.3.2 Knowledge representation (KR) versus non-KR approach 1.3.3 Summary of Key Contribution and Conclusions 1.4 Structure of the Book 10 BACKGROUND ON CONCEPT GENERATION AND APPROACHES 12 2.1 Research on Concept Generation: An Interdisciplinary View 12 2.1.1 Definition of Concept Generation and its criteria 12 2.1.2 Ideation support methods 13 2.1.3 Conceptual Blending Framework 15 2.1.4 Concept synthesis and specific methods 18 2.2 A Knowledge Representation (KR) approach on Conceptual Blending: Conceptual Graph 20 2.3 A statistics-based (Non-KR) approach on Conceptual Blending 24 2.4 Summary 25 GLOSSARY 26 A THEORETICAL APPROACH: THEORY OF CONCEPTUAL GRAPH AS A REPRESENTATION TO CONCEPTUAL BLENDING 27 iii 3.1 Introduction 27 3.2 Representation for Conceptual Blending 28 3.2.1 General Theory Framework 30 3.2.2 Elements 31 3.2.3 Structures 35 3.2.4 Flexi-representation of mental space 36 3.3 Elementary Operations of Conceptual Blending 39 3.3.1 Previous Implementations of blending and blending operations 39 3.3.2 List of blending operations 40 3.3.3 Why blending mechanism is not presented in this research 44 3.4 Viewpoint representation 45 3.4.1 Literature Review on viewpoint 45 3.4.2 Viewpoint subtype on concept or relation type 46 3.4.3 Viewpoint vector on concept nodes’ relationship 47 3.4.4 Viewpoint matrix to define emotion on Conceptual Blending network 48 3.5 Theoretical work and Characteristics of mental spaces as benchmark for KR approach 50 3.5.1 Flexibility 50 3.5.2 Structured representation of knowledge 52 3.5.3 Dynamical modifiability 52 3.5.4 Variation by perspectives 53 3.6 Summary 54 A PRACTICAL APPROACH: MULTI-AREA INSPIRATION SEARCH 56 4.1 Introduction 56 4.2 Challenge and Motivation 57 4.3 Use Case Definition of Multi-area Inspiration Search 59 4.4 Previous work in search engines 60 4.4.1 Conventional Search Engines 60 iv 4.4.2 Semantic Search and Semantic Web 64 4.4.3 Cross domain search and meta-search 67 4.5 Other related works to Multi-area Inspiration Search 68 4.6 Ecosystem of Multi-area Inspiration Search 70 4.7 Multi-area Inspiration Search framework to measure and to classify resources across disciplines 73 Multi-area Inspiration Search Process in KR approach 76 4.8 4.8.1 KR-based Search Architecture 77 4.8.2 KR-based semantic relatedness measure 78 Multi-area Inspiration Search Process in statistics-based approach 86 4.9 4.9.1 Statistics-based Search Architecture 86 4.9.2 Statistics-based semantic relatedness measure 87 4.10 Semantic threshold: Sensitivity on Threshold 90 4.11 Summary 92 MULTI-AREA INSPIRATION SEARCH IN BIOMIMIRY: EXPERIMENT AND EVALUATION 93 5.1 Introduction to Multi-area Inspiration Search in Biomimicry 93 5.1.1 Context 93 5.1.2 Multi-area Inspiration Search vision and example 95 5.1.3 Chapter overview 99 5.2 Approach Multi-area Inspiration Search in Biomimicry – Experiment Rationale and 99 5.2.1 Normal Retrieval Distance Comparison Matrix 99 5.2.2 Rationale and Approach to experiment set up 106 5.3 Experiment 1: Single Query – Source Experiments 108 5.3.1 Objectives and Experimental set up 108 5.3.2 Experiment and Observation 109 5.4 Experiment 2: Single Query and Extended Source – Four Search Groups of Multi-Area Inspiration Search Engine 114 v 5.4.1 Objectives and Experimental set up 114 5.4.2 Experiment data and Observation 115 5.4.3 Conclusion on experiment 2: 118 Experiment 3: Extended Query and Extended Sources 119 5.5 5.5.1 Objectives and Experimental set up 119 5.5.2 Experiment data and Observation 121 Summary 134 5.6 CONCLUSION AND FUTURE WORK 136 6.1 Possible extensions from the book 136 6.1.1 Applications of Multi-area Inspiration Search other than in Biomimicry 136 6.1.2 Applications of Conceptual Blending Framework in Security and Education 137 6.2 Limitations and Future work 139 6.3 Conclusions 141 BIBLIOGRAPHY 144 ANNEXES 156 ANNEX EXPERIMENT SUPPLEMENTARY DATA 156 ANNEX EXPERIMENT SUPPLEMENTARY DATA 159 ANNEX BIOMIMICRY ARTICLES FOR EXPERIMENT 163 ANNEX EXPERIMENT 164 vi SUMMARY This work describes a concept generation system to provide designers and engineers with better ideation support in a very early phase of creativity We focus on cross-domain innovation and introduce a new search scheme called Multi-area Inspiration Search Our motivation is to assist human beings in complex problems that require cross-domain knowledge In a multi-domain problem, it is common to encounter blockage due to lack of knowledge integration In a single-domain one, the lack of cross-domain knowledge inhibits designers or solution engineers to explore other methods Without any guidance, they may either unconsciously or forcefully limit their search domains to meet time and resources constraints because it is timeconsuming, frustrated and risky to venture in an unknown territory of knowledge Existing ideation support systems stimulate thinking processes by popping new keywords (verbs, phrases), representing design workflows, which improves brainstorming process to a certain extent Though valuable, such systems often result in an explosion of irrelevant suggestion and not provide useful guidance in a new domain In contrast, this work uses Conceptual Blending framework, a cognitive theory, to learn and to imitate human creativity model The word ‘blending’ comes from integration of existing knowledge to form a new one We introduce a representation of Conceptual Blending framework based on Conceptual Graph (CG), a well-known theory to represent knowledge In particular, we formalize and discuss in details four typical Conceptual Blending networks and their blending elementary operations, which makes a computational theoretical foundation for the framework The Multi-area Inspiration Search is an application of Conceptual Blending, which provides inspiration search results in different areas of knowledge from that of a query We are especially interested in applying Multi-area Inspiration Search in Biomimicry, a research branch mimicking nature design in design and engineering solutions There are two possible approaches to implement the new search algorithm: Knowledge representation approach and statistics-based (non-KR) approach We encounter major challenges in implementing KR approach as many vii concepts in Biomimicry not exist in current ontologies, which results in incomplete background knowledge Since constructing ontologies for Biomimicry domain is too time-consuming, we decided to use the second approach leveraged on Google search engine An empirical study on Statistics-based approach in Biomimicry domain with up to 7000 concepts provides promising results and justifies the use of statistical measure, Normalize Retrieval Distance, for the search Most importantly, the search is able to retrieve existing information in a database and through a comparison of search results distribution; it also behaves reasonably to a query outside its database As an interwoven research of cognitive science and artificial intelligence, this work suggests that by combining existing knowledge from different domains, designers can come up with creative solutions to a domain-specific problem 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kingfisher or (train, kingfisher) and (train, kingfisher) N NGD or NRD Experiment noisy train kingfisher or and N NGD or NRD Experiment airplane kingfisher or and N NGD or NRD Experiment Dancing Saliva or and N NGD or NRD Experiment Dancing Cow Saliva or and N NGD or NRD AskNature full Result Counts 25 32 52 12329 0.30 AskNature full Result Counts 29 32 56 12329 0.31 AskNature Result Counts 13 32 45 12329 999.00 AskNature Result Counts 27 30 12329 999.00 AskNature Result Counts 39 42 12329 999.00 Log 1.40 1.51 0.70 4.09 NRDf Log 1.46 1.51 0.70 4.09 NRDf Log 1.11 1.51 #N/A 4.09 Log 0.48 1.43 #N/A 4.09 Log 0.48 1.59 #N/A 4.09 AskNature limited Result Counts Log 0.70 0.78 10 0.00 12329 4.09 0.23 NRDl Google Search Result Counts Log 982,000,000 8.99 6,630,000 6.82 AskNature limited Result Counts Log 0.78 0.78 10 0.30 12329 4.09 0.14 NRDl Google Search Result Counts Log 26,100,000 7.42 6,630,000 6.82 Biomimicry Taxonomy Result Counts Log 0.95 0.78 15 #N/A 12329 4.09 999.00 Google Search Result Counts Log 123,000,000 8.09 6,630,000 6.82 Biomimicry Taxonomy Result Counts Log 0.00 13 1.11 14 #N/A 12329 4.09 999.00 Google Search Result Counts Log 631,000,000 8.80 31,800,000 7.50 Biomimicry Taxonomy Result Counts Log 0.00 16 1.20 17 #N/A 12329 4.09 999.00 Google Search Result Counts Log 631,000,000 8.80 2,250,000 6.35 156 3,750,000 50,000,000,000 0.62 16,000,000 50,000,000,000 0.05 1,130,000 50,000,000,000 0.53 2,670,000 50,000,000,000 0.74 50,000,000,000 1.86 6.57 10.70 NGD 7.20 10.70 NGD 6.05 10.70 6.43 10.70 0.70 10.70 Experiment Sharkskin auto-clean wide-screen or and N NGD or NRD Experiment horse rider or (horse, rider) and (horse, rider) N NGD or NRD Experiment AskNature Result Counts 0 12329 999.00 AskNature full Result Counts 41 42 999.00 run dive or (run, dive) and (run, dive) N NGD or NRD Experiment fungus mushroom or (fungus, mushroom) and (fungus, mushroom) N NGD or NRD #N/A 4.09 Log 1.61 #N/A #N/A ##### NRDf AskNature full Result Counts Log Shakespeare Cheese or (shakespeare, cheese) and (shakespeare, cheese) N NGD or NRD Experiment Log 0.00 #N/A Biomimicry Taxonomy Result Counts Log 0.90 #N/A 0 #N/A 12329 4.09 999.00 Google Search Result Counts Log 44,200 4.65 367,000,000 8.56 AskNature limited Result Counts Log 0.95 #N/A 10 #N/A #NUM! 999.00 NRDl Google Search Result Counts Log 46700000 7.67 12200000 7.09 AskNature limited Result Counts Log Google Search Result Counts Log 73,700,000 7.87 213,000,000 8.33 999.00 NRDf AskNature full Result Counts Log 105 29 134 999.00 NRDf NRDl AskNature limited Result Counts Log 38 10 48 NRDf AskNature full Result Counts Log 144 error of display 175 12329 #DIV/0! 999.00 999.00 NRDl AskNature limited Result Counts Log 47 1.67 12 1.08 56 0.48 12329 4.09 0.40 NRDl 157 11,500 50,000,000,000 0.74 4.06 10.70 2630000 6.42 50000000000 10.70 0.35 NGD 7,160,000 50,000,000,000 0.52 6.85 10.70 NGD Google Search Result Counts Log 1,400,000,000 9.15 36,600,000 7.56 92,200,000 50,000,000,000 0.38 7.96 10.70 NGD Google Search Result Counts Log 25,100,000 7.40 122,000,000 8.09 5,505,000 50,000,000,000 0.41 6.74 10.70 NGD Experiment train turtle or (train, turtle) and (train, turtle) N NGD or NRD Experiment noisy train turtle or (noisy train, turtle) and (noisy train, turtle) N NGD or NRD Experiment bird train or and N NGD or NRD Experiment shark skin swimming suit or and N NGD or NRD Experiment cat fish or and N NGD or NRD AskNature full Result Counts Log 25 1.40 error error AskNature limited Result Counts Log 0.70 0.95 14 #NUM! 12329 4.09 999.00 NRDl Google Search Result Counts AskNature limited Result Counts Log 0.78 0.95 15 12329 4.09 999.00 NRDl Google Search Result Counts Google Search Result Counts NRDf AskNature limited Result Counts Log 58 1.76 0.70 63 12329 4.09 999.00 NRDl AskNature full Result Counts Log 436 2.64 160 2.20 572 24 1.38 12329 4.09 0.67 AskNature limited Result Counts Log 184 2.26 70 1.85 238 16 1.20 12329 4.09 0.47 Google Search Result Counts AskNature full Result Counts Log error #VALUE! 327 2.51 AskNature limited Result Counts Log 12 1.08 128 2.11 139 0.00 12329 4.09 0.70 Google Search Result Counts NRDf AskNature full Result Counts Log 29 1.46 error error NRDf AskNature full Result Counts Log #DIV/0! error 12329 999.00 #N/A 4.09 158 622,000,000 118,000,000 38,000,000 50,000,000,000 0.46 25,500,000 118,000,000 25,200,000 50,000,000,000 0.20 124,000,000 622,000,000 160,000,000 50,000,000,000 0.23 18,800,000 22,300,000 1,150,000 50,000,000,000 0.38 321,000,000 629,000,000 102,000,000 50,000,000,000 0.36 Log 8.79 8.07 7.58 10.70 NGD Log 7.41 8.07 7.40 10.70 NGD Log 8.09 8.79 8.20 10.70 NGD Log 7.27 7.35 6.06 10.70 Log 8.51 8.80 8.01 10.70 ANNEX EXPERIMENT SUPPLEMENTARY DATA Table A2 Experiment on ‘Swordtail butterfly’ Normalized Retrieval Distance AskNature Source Query Google NGD Swordtail butterfly paint furniture 1,315 limited AskNature search full search NBDl NBDf 0.386 0.748 0.181 0.128 blue green paint furniture 0.007 coloring paint furniture 0.228 0.256 0.138 enhance paint furniture 0.299 0.545 0.780 diffusion paint furniture 0.488 0.144 0.072 butterfly wings paint furniture 0.564 0.167 0.116 light reflection paint furniture 0.652 0.162 0.124 coloration paint furniture 0.712 0.328 0.212 scattering paint furniture 0.754 0.120 0.189 0.461 0.238 0.220 0.556 0.254 0.279 Average NRD related POS (excl.999) Average NRD including target concepts 159 Table A2 Experiment on ‘Velvet worm’ Normalized Retrieval Distance Source Query Biomimicry AskNature Google limited search full search NGD NBDl NBDf velvet worm paint furniture 0.209 0.431 0.794 eject paint furniture 0.064 999 999 nozzle paint furniture 0.088 0.390 0.576 multiple strands paint furniture 0.108 0.725 0.881 stream of glue paint furniture 0.192 0.460 0.728 crisscross paint furniture 0.311 999 999 lasso-like motion paint furniture 0.394 0.683 0.956 shoot paint furniture 0.438 999 999 mouth paint furniture 0.442 999 999 move from side to side paint furniture 0.458 0.705 0.973 ensnare prey paint furniture 0.510 0.747 1.040 dry in seconds paint furniture 0.529 0.703 1.0003 ejectable adhesive liquid paint furniture 0.531 0.574 0.845 dry 0.539 0.691 0.841 paint furniture 999,00 seconds paint furniture Average NRD related POS (excl.999) Average concepts NRD including 0.795 999,000 0.386 0.631 0.871 0.374 0.611 0.863 target 160 Table A2 Experiment on ‘Earthworm’ Normalized Retrieval Distance Source Query Biomimicry AskNature full Google limited search search NGD NBDl NBDf earthworm paint furniture 0,374 999 999 electric current paint furniture 0,008 999 1,027 reducing drag paint furniture 0,087 0,618 0,891 soil adhesion paint furniture 0,089 0,835 1,206 friction paint furniture 0,102 0,512 0,833 lubricants paint furniture 0,173 0,550 0,725 repels paint furniture 0,185 0,462 0,673 aggregate water paint furniture 0,214 0,730 1,127 reduces friction paint furniture 0,298 0,739 1,016 auto-lubrication paint furniture 0,319 skin of earthworms paint furniture 0,326 0,647 0,842 electricity paint furniture 0,411 999 0,859 thin water film paint furniture 0,558 0,685 1,065 electro-osmotic flow paint furniture 0,622 999 1,136 charges paint furniture 0,680 0,420 0,617 paint furniture 0,833 999 0,977 Average NRD related POS (excl.999) 0,327 0,620 0,928 0,330 0,620 0,928 without toxic not found not found self-generated cutaneous bioelectrical current Average NRD including target concepts 161 Table A2 Experiment on ‘Oriental hornet’ Normalized Retrieval Distance Source Query Biomimicry AskNature full Google limited search search NGD NBDl NBDf Oriental hornet paint furniture 0.221 999 999 synthesized paint furniture 0.039 0.734 biomineralization paint furniture 0.060 999 999 electrons paint furniture 0.084 0.506 0.738 microscopic paint furniture 0.090 0.512 0.656 wavelengths paint furniture 0.130 999 999 strengthen paint furniture 0.134 999 999 yellow bands paint furniture 0.149 1 reflected paint furniture 0.186 cuticular paint furniture 0.193 999 999 granules paint furniture 0.223 999 999 electrical energy paint furniture 0.251 1 cuticle paint furniture 0.252 999 999 ridges paint furniture 0.279 0.467 0.704 electrical potential paint furniture 0.342 0.584 0.802 absorbed paint furniture 0.425 999 999 pigment paint furniture 0.482 0.623 0.910 pigment paint furniture 0.488 0.561 0.847 sunlight paint furniture 0.530 999 999 UV light paint furniture 0.534 1 solar energy paint furniture 0.551 1 compound paint furniture 0.569 999 999 transform paint furniture 0.583 999 shell paint furniture 0.654 0.662 0.905 calcium carbonate paint furniture 0.690 999 999 movement paint furniture 0.711 1 xanthopterin paint furniture 0.797 999 999 (excl.999) 0.362 0.571 0.817 Average NRD including target 0.357 0.571 0.817 higher Photovoltaic Average NRD related POS 162 concepts ANNEX BIOMIMICRY ARTICLES FOR EXPERIMENT Articles used in Experiment of this book are extracted from the official AskNature.org website It is an award winning open source of knowledge for nature design in engineering The following article titles were randomly chosen for experiment Interesting readers can find a full article at www.asknature.org Scales on the ventral side of swordtail butterfly wings enhance blue/green coloring via light reflection and diffusion Lotusan® paint Relationship provides thermal protection: hot springs panic grass, fungus Secretions break down algal walls: stony corals Pili direct electron transfer: Geobacter Photovoltaic pigments aid biomineralization: Oriental hornet Structures create colorful feathers: common kingfisher Covering protects eye: pied kingfisher Eyes manage glare: kingfishers 10 Adhesive glues prey: velvet worms 11 Enzyme catalyzes many reactions: plants 12 Electrosensitivity used to navigate: rattlesnake 13 Larvae ditch threatened hosts: parasitic fly 14 Electric current reduces friction: common earthworm 15 Digesting various substances: fungi 16 Mineral crystals enhance cutting ability: limpet 17 Head bores through wood: shipworm 18 Secretion kills bacteria: burying beetle 19 Siphon filters seawater: sea squirt 163 ANNEX EXPERIMENT Due to large size of data, we enclosed the experiment details in the Compact Disc attached to this book in form of an Excel file The Excel file is named as ‘Experiment Data’ and consists of all experimental data in this book and Visual basic program to execute the experiments In the file, the experiment data is documented as follow: Ex3_Query Record: contains all query concepts in experiment 3, each of which is encoded by query number, type of concept (target or related) Ex3_Source Record: contains all source concepts in experiment 3, each of which is encoded by query number, type of concept (target or related) These concepts are extracted from Biomimicry source in Annex 3 Experiment_3_Data: contains all statistics of the experiments The tab ‘Experiment_3_Sim Matrix’, ‘Experiment 3_Summary’ and ‘Experiment 3_Close up’ calculate the results which have been presented in Chapter 164 ... domain search and meta -search 67 4.5 Other related works to Multi- area Inspiration Search 68 4.6 Ecosystem of Multi- area Inspiration Search 70 4.7 Multi- area Inspiration Search. .. 1.3.1 Concept Generation System based on Conceptual Blending Framework: Multi- area Inspiration Search Computer-aid Concept Generation System in this work follows the theory of Conceptual Blending. .. frameworks, which is called Conceptual Blending 2.1.3 Conceptual Blending Framework There are several Concept Synthesis frameworks, among which is Conceptual Blending As Conceptual Blending is the focus