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Fuzzy Ontology for Knowledge Mobilisation and Decision Support

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Fuzzy Ontology for Knowledge Mobilisation and Decision Support Robin Wikström Fuzzy Ontology for Knowledge Mobilisation Knowledge Mobilisation for and Decision Ontology Support | Fuzzy Wikström | 2014 Robin and Decision Support Utilizing imprecise data Robin Wikström The objective of the research conducted was to explore how fuzzy ontologies could facili- tate the exploitation and mobilisation of tacit knowledge and imprecise data in organisatio- Fuzzy Ontology for Knowledge nal and operational decision making processes. This thesis shows the benefits of utilizing Mobilisation and Decision Support all the available data one possesses, including imprecise data. By combining the concept of fuzzy ontology with the Semantic Web move- ment, it aspires to show the corporate world and industry the benefits of embracing fuzzy ontologies and imprecision. 9 789521 230745 ISBN 978-952-12-3074-5 Robin Wikström Born 1988 Bachelor of Science from Åbo Akademi 2011 Master of Science from Åbo Akademi 2012 Doctor of Science defence at Åbo Akademi 2014 Fuzzy Ontology for Knowledge Mobilisation and Decision Support Robin Wikström To be presented, with the permission of the Department of Information Technologies of Åbo Akademi University, for public criticism in Auditorium Gamma on June 13, 2014, at 12 noon. Åbo Akademi University Department of Information Technologies Institute for Advanced Management Systems Research (IAMSR) Joukahainengatan 3-5 B. 20520 Åbo. 2014 Supervisors Prof. Dr Christer Carlsson Institute for Advanced Management Systems Research Department of Information Technologies Åbo Akademi University Joukahainengatan 3-5 B. 20520 Åbo Docent József Mezei Institute for Advanced Management Systems Research Department of Information Technologies Åbo Akademi University Joukahainengatan 3-5 B. 20520 Åbo Reviewers Prof. Dr Kauko Leiviskä Control Engineering Laboratory Department of Process and Environmental Engineering University of Oulu P.O.Box 4300, 90014 University of Oulu Finland Prof. Dr José Luis Verdegay Department of Computer Science and Artificial Intelligence University of Granada 18071 Granada, CITIC-University of Granada Spain Opponent Academician Prof. Dr Janusz Kacprzyk Systems Research Institute Polish Academy of Sciences ul. Newelska 6, 01-447 Warsaw Poland ISBN 978-952-12-3074-5 Painosalama Oy - Åbo, Finland 2014 Abstract A growing concern for organisations is how they should deal with increasing amou- nts of collected data. With fierce competition and smaller margins, organisations that are able to fully realize the potential in the data they collect can gain an advan- tage over the competitors. It is almost impossible to avoid imprecision when processing large amounts of data. Still, many of the available information systems are not capable of handling imprecise data, even though it can offer various advantages. Expert knowledge stored as linguistic expressions is a good example of imprecise but valuable data, i.e. data that is hard to exactly pinpoint to a definitive value. There is an obvi- ous concern among organisations on how this problem should be handled; finding new methods for processing and storing imprecise data are therefore a key issue. Additionally, it is equally important to show that tacit knowledge and imprecise data can be used with success, which encourages organisations to analyse their imprecise data. The objective of the research conducted was therefore to explore how fuzzy ontologies could facilitate the exploitation and mobilisation of tacit knowledge and imprecise data in organisational and operational decision making processes. The thesis introduces both practical and theoretical advances on how fuzzy logic, ontologies (fuzzy ontologies) and OWA operators can be utilized for differ- ent decision making problems. It is demonstrated how a fuzzy ontology can model tacit knowledge which was collected from wine connoisseurs. The approach can be generalised and applied also to other practically important problems, such as intrusion detection. Additionally, a fuzzy ontology is applied in a novel consensus model for group decision making. By combining the fuzzy ontology with Se- mantic Web affiliated techniques novel applications have been designed. These applications show how the mobilisation of knowledge can successfully utilize also imprecise data. An important part of decision making processes is undeniably aggregation, which in combination with a fuzzy ontology provides a promising basis for demon- strating the benefits that one can retrieve from handling imprecise data. The new aggregation operators defined in the thesis often provide new possibilities to han- dle imprecision and expert opinions. This is demonstrated through both theoretical examples and practical implementations. This thesis shows the benefits of utiliz- i ing all the available data one possess, including imprecise data. By combining the concept of fuzzy ontology with the Semantic Web movement, it aspires to show the corporate world and industry the benefits of embracing fuzzy ontologies and imprecision. ii Sammanfattning Organisationer har idag stora utmaningar med att hantera ett viktigt element som kan skapa konkurrensfördelar; kunskap. Moderna informationssystem samlar kon- tinuerligt in mängder av data som innehåller användbar kunskap, men som inte utnyttjas till fullo. Hårdare konkurrens och mindre marginaler innebär att organ- isationer som utnyttjar sin ihopsamlade data kommer att ha en konkurrensfördel gentemot sina konkurrenter. Då stora mängder data skall processeras är det nästintill omöjligt att fullständigt undvika oprecis och diffus data. Samtidigt är många av dagens informationssys- tem inte kapabla att hantera oprecis data, fastän den kan innehålla värdefull in- formation. Ett exempel på oprecis men värdefull data är verbal information från experter, med andra ord data som är svår att definitivt fastställa till ett specifikt värde. Att hantera underförstådd kunskap är en utmaning för organisationer; att utveckla nya metoder för att processera och lagra oprecis data är därför väsentligt. Därutöver är det viktigt att demonstrera hur underförstådd kunskap och oprecis data framgångsrikt kan användas, vilket förhoppningsvis inspirerar organisationer och företag att mer än tidigare beakta även oprecis kunskap. Det huvudsakliga målet med den här avhandlingen är att undersöka hur on- tologier som kan arbeta med oprecis data kan underlätta användningen och mo- biliseringen av underförstådd kunskap och oprecis data för beslutsstödsprocesser och operativ och strategisk ledning i organisationer. Avhandlingen introducerar både praktiska och teoretiska framsteg för hur logik och ontologier för oprecisa observationer (eng. “fuzzy logic” och “fuzzy ontolo- gies”) och OWA operatorer (eng. “OWA operators”) kan användas för att stöda olika beslutsstödsprocesser. Avhandlingen visar även hur ontologier kan ge be- greppsunderlag för att hantera underförstådd kunskap. Exemplet som beskrivs i avhandlingen behandlar olika typer av vin och data som samlats in från vinkon- nässörer. Den här ansatsen kan generaliseras och appliceras för att stöda arbetet också med andra praktiska problem såsom intrångsdetektering. Därtill används en ontologi som en central aktör i en ny konsensusmodell för gruppbeslutsfattande. Då ontologier kombineras med tekniker som utvecklats för den semantiska webben så blir det möjligt att konstruera nya applikationer. De här applikationerna visar hur en mobilisering av kunskap kan utnyttja oprecisa data. En viktig del av beslutsfattandet är att kunna aggregera element till större iii helheter för att skapa översikter. Aggregation är användbart tillsammans med de utvecklade ontologierna, speciellt eftersom de kan utnyttja även oprecis data. De nya aggregationsoperatorerna som definieras i avhandlingen erbjuder nya möj- ligheter att hantera oprecisa data och expertkunskap. Det här visas mera ingående med hjälp av både praktiska och teoretiska exempel. Avhandlingen demonstrerar de fördelar man kan erhålla genom att utnyttja till- gänglig data, inklusive oprecisa data. Genom att kombinera ontologier med data och information från den semantiska webben strävar avhandlingen efter att visa fördelarna med att kunna använda data och information som samlats in från verk- ligheten. iv Acknowledgements This thesis is the product of co-operation, without supervisors and research col- leagues it would be a pale shadow of its current self. It is my belief that collabora- tion creates superior research outcome and extensive insights, but in the process it, of course, adds to the acknowledgement section. First of all, I would like to express my gratitude to my supervisor Prof. Chris- ter Carlsson, for giving me the opportunity to continue doing research after my master’s studies. His passion for work and research has been truly inspiring to ex- perience firsthand. It is cumbersome to find a suitable way of expressing the gratitude I feel towards my supervisor József Mezei. It is a fact, that without his friendship and scientific guidance, this thesis would not have been as complete as it is today. Working with him has been both a privilege and a pleasure and I will be forever grateful for the time he has devoted to this endeavour, both professionally and personally. To Prof. Janusz Kacprzyk, I am obliged and honoured that you accepted the task of being the opponent for my thesis. I am also grateful to Prof. Kauko Leiviskä and Prof. José Luis Verdegay who reviewed my thesis. Their constructive com- ments where beneficial for improving the quality of the thesis. As mentioned, co-operation was vital for the
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