Ontology-Based Users and Requests Clustering in Customer Service Management System

Smirnov, Alexander; Pashkin, Mikhail; Chilov, Nikolai; Levashova, Tatiana; Krizhanovsky, Andrew; Kashevnik, Alexey

doi:10.1007/11492870_19

Cited by 14 publications

(9 citation statements)

References 9 publications

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“…The research results showed that the approach makes it possible to obtain an ontologybased model of a disaster situation that embeds models for problems requiring solutions in this situation. Application of disaster relief operation members' profiles allows the Webservices to take into account specific information about the members as well as their tacit and explicit preferences (e.g., [22]). As a result, the Web-services become capable to efficiently organize themselves in a service network for a common purpose.…”

Section: Discussionmentioning

confidence: 99%

Ubiquitous computing in emergency: Role-based situation response based on self-organizing resource network

Smirnov

Levashova

Shilov

2011

2011 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA

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Smart environment is defined here as a number of devices that can share information and services independently of their physical location. Smart environments based on ubiquitous computing open new possibilities to various aspects of human activities. The paper proposes an approach to emergency situation response that benefits of the ubiquitous computing. The approach is based on utilizing role profiles to facilitate the coordination of the activities of the emergency response operation members.Emergency response operations usually involve different people and organizations with different subordination. As a result, the centralized control is often impossible. The idea behind the approach is to self-organize resources of the smart environment according to the state of the situation caused by the accident. The resources self-organize a collaborative network that comprises physical devices, software services, organizations, and persons to undertake joint actions for accident response. The accident response system intended for operating in smart environments has a service-oriented architecture. Some of Webservices making up the architecture are intended to model the accident situations; others model resource functionalities or bear supporting functions. Web-services that model resource functionalities are aligned against the emergency situation management ontology. This alignment ensures semantic interoperability of the heterogeneous resources. A case study illustrates main ideas presented in the paper.

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Section: Discussionmentioning

confidence: 99%

Ubiquitous computing in emergency: Role-based situation response based on self-organizing resource network

Smirnov

Levashova

Shilov

2011

2011 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA

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“…Since an ontology is a description of the concepts and relationships that can well represent background knowledge, it has been applied to various clustering methods for improving their performance [3,4,7,9,11,14,24,48,57,68]. Cheng et al [9] used the graph-based structure of Gene Ontology (GO) [4] to infer the degree of similarity between genes.…”

Section: Related Workmentioning

confidence: 99%

“…Hotho et al [24] proposed two preprocessing strategies, TES (TErm Selection) and COSA (COncept Selection and Aggregation), which apply ontologies as background knowledge to improve clustering results. Smirnov et al [57] presented a method for clustering users and their requests, which uses ontologies to improve the semantic inter-operability between companies and customers. Corsi et al [11] developed the BioPrompt-box, which is an ontology-based clustering tool for searching in biological databases.…”

Section: Related Workmentioning

confidence: 99%

“…In recent work, since an ontology is a formal, explicit specification of a shared conceptualization for a domain of interest, it has been applied to various clustering methods for improving their performance [3,4,7,9,11,14,24,48,57,68]. As a comprehensive semantic lexical ontology for the English language, WordNet [39] has been widely used for document clustering [13,16,17,22,23,25,26,40,50,54,55].…”

Section: Introductionmentioning

confidence: 99%

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Exploiting noun phrases and semantic relationships for text document clustering

Zheng

Kang

Kim

2009

Information Sciences

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“…Many studies used ontology to facilitate customer needs management (e.g., Baida et al, 2005;Bock et al, 2010;Lin et al, 1996;Smirnov et al, 2005). Among the first such reports, Lin et al (1996) used ontology to support customer needs management and suggested that ontology should provide a uniform terminology shared by all the designers and engineers involved.…”

Section: Ontological Methods For Customer Needs Representationmentioning

confidence: 99%

Customer needs management for product innovation : segmentation modeling and ontology-based approaches

Chen¹

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Customer satisfaction has always been important for a product. Attaining customer satisfaction requires identifying genuine customer needs and establishing the relationship between customer needs and product features. Involving innovative customers in the product development process has been considered an effective way for customer needs management. However, previous studies are limited in innovative customer identification. In particular, they ignore the mismatching problems in customer needs representation between customer needs and intangible product characteristics. To address these limitations, there is a need for an integrated framework that is able to cover both the customer domain and product design domain at the stages of customer needs identification and product specification establishment in product development life cycle.

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Ontology-Based Users and Requests Clustering in Customer Service Management System

Cited by 14 publications

References 9 publications

Ubiquitous computing in emergency: Role-based situation response based on self-organizing resource network

Ubiquitous computing in emergency: Role-based situation response based on self-organizing resource network

Exploiting noun phrases and semantic relationships for text document clustering

Customer needs management for product innovation : segmentation modeling and ontology-based approaches

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