Building Customer Complaint Ontology: Using OWL to Express Semantic Relations

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1 Building Customer Complaint Ontology: Using OWL to Express Semantic Relations Yan Yalan,Zhang Jinlong School of Management, Huazhong University of Science and Technology, Wuhan, P.R.China, Abstract: Customer complaint is an important kind of information coming from customers and it is a primary measure of customer dissatisfaction. In order that complaint information could be understood and processed by machine automatically, more semantic descriptions are needed. Ontology has become a promising technology to express semantics and OWL (Ontology Web Language) has the ability to express semantic relations in building complaint ontology. In this paper, we put forward a framework of customer complaint ontology after considering capabilities to express semantic relations provided by OWL. Then we use Protégé-2000 to build OWL representations of the customer complaint ontology and make some analyses. Our exploration might not standardize customer complaint ontology. We explore with the intention to help people better understand the rationality in expressing concepts and relations between the concepts in customer complaint management in order that OWL customer complaint ontology and other ontology are improved and standardized as soon as possible. Keywords: Customer complaint ontology, Framework, OWL, Semantic relations 1 Introduction Customer complaint is an important kind of information coming from customers and it is a primary measure of customer dissatisfaction. Customer complaint management plays an important role in retaining old customers and even obtaining new customers. It is also an important content of Customer Relation Management (CRM). For a company, there exist many kinds of customer complaints. For example, some complaints are about logistic service, some about post sale service, some about quality, some about attitude. The resolution of the complaint might be economic compensation, improving service and so on. If a customer complaint is about quality and not resolved quickly, the company would not only lose this customer but also suffer from losing other customers. Companies should distinguish light complaint and strong complaint and take respective measures. Moreover, complaints own many properties such as hasnumber, hasproblem, hasresolution, madeby. Customers are the origin of the complaint and own many properties such as sex, age, marriage status, number of children, income, affiliation, telephone, , and so on. How to manage all the information of properties; how to define relations of complaints and properties and relations of different kinds of complaints is the problem that should be solved in implementing CRM strategy. Customer complaint information should be shared among departments within a company and even among companies within a supply chain. Best-practice companies have realized the importance of sharing information across the company so that other employees and/or business units can benefit from the same information. In establishing an information-sharing platform, many technologies have been used. For example, customer complaint information could be stored in database or data warehouse. In database, each property of complaint could be defined as a field. According to each field, given complaint could be retrieved very quickly. Generally speaking, database could manage large number of complaints with high efficiency. In data warehouse, many kinds of data mining technologies such as time series, regression, principal components, canonical correlation, K-Means cluster, hierarchical cluster could be used to analyze and discover some rules and relations about complaints. Moreover, technologies such as COM(Component Object Model) CORBA (Common Object Request Broker Architecture)and Agent, have also been developed to solve the technical problem of information sharing [1]. 433

2 Though these technologies behaved very well in information sharing by the mode of message exchanging, objective or component inter-referred and inter-operation among different system they remain syntax sharing basically and cannot describe customer complaint information semantically as well as express implied axiom, facts, judgments and rules relevant to customer complaint knowledge already existed in the information system [2]. As a result the structured information inferred from knowledge base or other information sources is unavailable as yet. Of course some new and useful knowledge about complaint can hardly produced or induced. More important, information sharing not based on semantic relations often leads to people confused by same conception with different name or title in same or different context when discussing something about business [3]. In order that complaint information could be understood and processed by machine automatically, more semantic descriptions are needed. Ontology has become a promising technology to express semantics [4]. As a substitute for the mode of information sharing, ontology based on semantic relation has gained more attention from researchers [5]. Ontology is a concept in philosophy. In the fields of artificial intelligence and Web, ontology is the description about concepts and their relations. Ontology is the theory about objects and their ties. It provides standards for differentiating kinds of objects (concrete and abstract, existent and non-existent, realistic and ideal, independent and dependent) and their ties (relations and dependency). Ontology is formal structure to support knowledge sharing and reusing. It could be used to express explicitly the semantics of structured and semi-structured information in order to support information acquiring, maintaining and accessing automatically. Ontology provides methods to solve the heterogeneous expression of Web resource. The model hidden in ontology could be regarded as providing a general semantic structure for information. Since this mode of information sharing can provide a uniform communication platform as well as avoid the mistake to the same concepts with different name or title in different context much efforts have been made to design this effective tool to mediate information sharing in terms of this mode within or beyond one company. Applying ontology on the Web facilitates the development of Semantic Web. Building complaint ontology on the Semantic Web would facilitate machine to process and share complaint information automatically without human interference. OWL (Ontology Web Language) has the ability to express semantic relations in building complaint ontology. 2 Web Ontology Languages XML (extensible Markup Language) has brought hope to Semantic Web. XML plus XML Schema specifies the syntax, structure and data type, but lacks semantic constraints. Tim Berners-Lee, creator of Semantic Web, considers the objective of Semantic Web as creating representative languages and describing information in the machine understandable form. He summarizes the functional framework of Semantic Web as metadata layer, schema layer and logical layer [6]. In metadata layer, data model only includes resources and properties, and RDF (Resource Description Framework) is regarded as the popular data model in this layer. RDF is a language for representing information about resources in the World Wide Web. It represents metadata of Web resource, such as title, author, modifying date of Web content, copyright and register information of Web documents, language, format, content items, and etc [7]. RDF is intended for situations in which this information needs to be processed by applications, rather than being only displayed to people. RDF provides a common framework for expressing this information so it can be exchanged between applications without loss of meaning. Since it is a common framework, application designers can leverage the availability of common RDF parsers and processing tools. The ability to exchange information between different applications means that the information may be made available to applications other than those for which it was originally created [8]. In schema layer, Web ontology language is introduced, used to describe concepts and properties. RDF Schema is regarded as the best candidate. RDF Schema does not provide a vocabulary of application-specific classes and properties. Instead, it provides the facilities needed to describe such classes and properties, and indicates which classes and properties are expected to use together. RDF Schema could be regarded as a light weighted Web ontology language. The RDF Schema facilities are 434

3 themselves provided in the form of an RDF vocabulary; that is, as a specialized set of predefined RDF resources with their own special meanings [9]. In logical layer, more powerful Web ontology languages are introduced. These languages provide richer modeling sets mapping to the influential expressive logics. OIL(Ontology Inference Layer,2000) and DAML-OIL(Darpa Agent Markup Language-Ontology Inference Layer,2001) were once popular languages in logical layer. At present, OWL is widely accepted. OWL is designed to apply in not only presenting information but also processing the content of information. OWL facilitates machine interpretability of Web content more greatly than that supported by XML Schema and RDF Schema by providing additional vocabulary along with a formal semantics such as classes stated to be disjoint from each other, cardinality, properties stated to be symmetric, two properties stated to be equivalent, enumerated classes [10][11]. Building ontology on the Web is the core drive to push the development of Semantic Web. XML Schema, RDF Schema and OWL could be regarded as Web ontology languages with increasing capabilities to express semantics, meeting the needs of knowledge processing and knowledge management in different periods. 3 A Framework of Customer Complaint Ontology hascity {China, America, haszipcode France, Germany, hascountry England, Australia, has Contact Japan, Korea} owl:oneof owl:equivalentclass hasname Country hascontact Economic_Compensation hasnumber Logistic_Service Customer madeby hasresolution Resolution Problem hasproblem Improving_Service Complaint Attitude Quality No_Response Post_Sale_Service Light_Complaint Strong_Complaint hasproblem hasresolution hasproblem hasresolution allvaluesfrom Logistics_Service Post_Sale_Service Improving_Service Economic_Compensation owl:intersectionof Attitude Quality No_Response owl:intersectionof Figure 1 A framework of customer complaint ontology In Figure 1, we put forward a framework of customer complaint ontology. We would not hope to put this ontology as a standard ontology in complaint management, since the standardization of complaint ontology relies on the cooperation and endeavors of many groups. In CRM, there exist many semantic relations that need to be expressed so that machine could understand and process. How to change statements expressed in natural languages to statements of formal descriptive logic is the key task in ontology building [12]. In the framework of complaint ontology, we have considered capabilities 435

4 to express semantic relations provided by OWL. OWL classes are interpreted as sets that contain individuals. They are described using formal (mathematical) descriptions that state precisely the requirements for membership of the class. Properties are binary relations on individuals, i.e. properties link two individuals together. Individuals represent objects in the that we are interested in. In Figure 1, classes are illustrated in ellipses and properties in rectangles. OWL is property-centricity. Each property has and. Complaint is defined as a class. It has two subclasses: Light_Complaint and Strong_Complaint. The of the four properties (hasnumber, hasproblem, hasresolution, madeby) is the class Complaint. The of the property hasproblem is the class Problem. The of the property hasresolution is the class Resolution. The of the property madeby is the class Customer. The class Problem has four subclasses: Logistic_Service, Post_Sale_Service, Attitude, Quality. The class Resolution has three subclasses: Economic_Compensation, Improving_Service, No_Response. The of the property hascontact is the class Customer. The of hascontact is the class Contact. The of the five properties (hasname, has , haszipcode, hascity, hascountry) is the class Contact. The of the property hascountry is the class Country. Class Country is the equivalent class of an enumeration class having individuals of China, America, France, Germany, England, Australia, Japan, and Korea. The restriction allvaluesfrom is stated on a property with respect to a class. It means that this property on this particular class has a local restriction associated with it. Thus if an instance of the class is related by the property to a second individual, then the second individual can be inferred to be an instance of the local restriction class. The restriction is stated on a property with respect to a class. A particular class may have a restriction on a property that at least one value for that property is of a certain type [10]. In Figure 1, the class Light_Complaint has the property hasproblem restricted to have the class Logistic_Service and Post_Sale_Service. It also has the property hasresolution restricted to have the class Improving_Service and Economic_Compensation. Then, the two property restrictions intersect. The class Strong_Complaint has the property hasproblem restricted to have the class Attitude. Its also has the property hasresolution restricted to have allvaluesfrom the class No_Response. Then, the two property restrictions intersect. Moreover, the class Strong_Complaint has the property hasproblem restricted to have the class Quality and this restriction and the result of upper intersection forms the Boolean combination of unionof. 4 Using OWL to Express Semantic Relations of Customer Complaint Ontology Protégé-2000 is an integrated software tool used by system developers and experts to develop knowledge-based systems. Applications developed with Protégé-2000 are used in problem solving and decision-making in a particular. Protégé is a free, open-source platform that provides a growing user community with a suite of tools to construct models and knowledge-based applications with ontologies. The Protégé platform supports two main ways of modeling ontologies: Protégé-Frames editor and Protégé-OWL editor. The Protégé-OWL editor enables users to build OWL ontologies for the Semantic Web [13]. In the environment of Protégé-2000, we have built OWL ontology of customer complaint based on Figure 1. OWL provides additional vocabulary along with a formal semantics such as disjointwith, intersectionof, unionof, complementof, oneof, allvaluesfrom,, mincardinality, maxcardinality and cardinality for the purpose of expressing more semantic relations and restrictions such as disjoint, intersection, union, complement, enumeration, property restrictions, and cardinality. For example, OWL allows arbitrary Boolean combinations of classes and restrictions, such as property restriction based on unionof and property restriction based on intersectionof. In OWL, class could be described by enumerating all the individuals composing the class. Classes could be stated to be disjointing with each other. In OWL representations of customer complaint ontology, the above examples are used. 436

5 5 Conclusions At present, Web ontology languages have been standardized. However, building ontology based on OWL just begins and has a long way to go. In building ontology, people should explore the rationality in expressing concepts and relations between the concepts, considering the capabilities of OWL (not the capability of natural languages). This is not an easy thing. Indeed, OWL has the feature and capability to express semantic relations. But, the standard of OWL is general, not oriented to any specific. People who are responsible for building given ontology should have a process to recognize the capability of OWL in their application. In this paper, we put forward a framework of customer complaint ontology and make some analyses. Our exploration might not standardize customer complaint ontology. We explore with an intention to help people better understand the rationality in expressing concepts and relations between the concepts in customer complaint management in order that OWL customer complaint ontology and other ontology are improved and standardized as soon as possible. Thus, machine could understand, share and process customer complaint information, and make some reasoning without human interference. Acknowledgements This paper is supported by the great project of Philosophy and Social Science Research of Ministry of Education of China under grant 05JZD This paper is also supported by Postdoctoral Science Foundation of Huazhong University of Science and Technology. References [1] Filman, R.E., Korsmeyer, D.J andlee, D.D. A CORBA extension for intelligent software environments. Advances in Engineering Software, Eng., vol. 31, no. 8, pp , 2000 [2] Hou Liwen, Xiao Min, Jiang Fu. Research on Modelling Customer Ontology under CRM Framework. Available in: file/2004/s pdf [3] Liliana Ardissono, Marco Botta, Luca Di Costa, et al. Customer Information Sharing between E-commerce Applications. Available in: liliana/ec/woa04.pdf [4] Mustafa Jarrar, Ruben Verlinden, Robert Meersman. Ontology-based Customer Complaint Management. Available in: %5BJDM03%5D.WORM03.OntoBasedCustComplaint.v1.1.AfPublished.pdf [5] Gruber T. Towards principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies, vol. 43, no.5, pp , 1995 [6] Tim Berners-Lee, Hendler, Lassila. The Semantic Web. Available in: articleid= d2-1c70-84a9809ec588ef21 [7] Graham Klyne, et al. Resource Description Framework (RDF): Concepts and Abstract Syntax(W3C Recommendation 10 February 2004). Available in: -rdf-concepts / [8] Frank Manola, et al. RDF Primer(W3C Recommendation 10 February 2004). Available in: [9] Dan Brickley, et al. RDF Vocabulary Description Language 1.0: RDF Schema(W3C Recommendation 10 February 2004). Available in: TR/2004/REC-rdf-schema / [10] Deborah L. McGuinness, et al. OWL Web Ontology Language Overview (W3C Recommendation 10 February 2004). Available in: TR/2004/REC-owl-features / [11] Peter F. Patel-Schneider, et al. OWL Web Ontology Language Semantics and Abstract Syntax (W3C Recommendation 10 February 2004). Available in: TR/2004/REC-owl-semantics / [12] Yves Pigneur. Ontology for e-business models. Available in: slides/oesseo2001.pdf [13] html 437