Customer Relationship Management in Social and Semantic Web Environments

2012 ◽  
pp. 83-92
Author(s):  
Ángel García-Crespo ◽  
Ricardo Colomo-Palacios ◽  
Juan Miguel Gómez-Berbís ◽  
Fernando Paniagua Martín
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Dynamic Environment ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Web 3.0 ◽  
Web Technologies ◽  
The Social ◽  
The Web

The growing influence of the Internet in current 21st-century everyday life has implied a paradigm shift in terms of relationships between customers and companies. New interaction means in the Web 1.0 have undergone a dramatic change in quantity and quality with the advent of the so-called Web 2.0, the Social Web. The upcoming Web 3.0, the Semantic Web will also impact tremendously in how companies understand Customer Relationship Management (CRM). In this dynamic environment, the present work presents a combination of both Social and Semantic Web Technologies and their application in the particular field of CRM. Tool and technology analysis both prove the challenging opportunities for these cutting-edge innovation trends in the CRM domain.

Customer Relationship Management in Social and Semantic Web Environments

2010 ◽  
Vol 1 (2) ◽  
pp. 1-10 ◽  
Author(s):  
Ángel García-Crespo ◽  
Ricardo Colomo-Palacios ◽  
Juan Miguel Gómez-Berbís ◽  
Fernando Paniagua Martín
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Paradigm Shift ◽  
Dynamic Environment ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Web 3.0 ◽  
Web Technologies ◽  
The Social

The growing influence of the Internet in current 21st-century everyday life has implied a paradigm shift in terms of relationships between customers and companies. New interaction means in the Web 1.0 have undergone a dramatic change in quantity and quality with the advent of the so-called Web 2.0, the Social Web. The upcoming Web 3.0, the Semantic Web will also impact tremendously in how companies understand Customer Relationship Management (CRM). In this dynamic environment, the present work presents a combination of both Social and Semantic Web Technologies and their application in the particular field of CRM. Tool and technology analysis both prove the challenging opportunities for these cutting-edge innovation trends in the CRM domain.

Customer Relationship Management as an Imperative for Academic Libraries

2015 ◽  
pp. 44-77
Author(s):  
Amanda Xu ◽  
Sharon Q. Yang
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Academic Libraries ◽  
Linked Data ◽  
Trust Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Customer Group

This chapter proposes a conceptual model, the 121 e-Agent Framework, for Customer Relationship Management (CRM) in academic libraries. Linked data and Semantic Web are the core components of this model. The implementation of the Framework will enable the participating U.S. academic libraries to reach out to their user communities through systematic customer group identification, differentiation, and interaction. The main contributions of the chapter are 1) applying Semantic Web technologies for CRM in academic libraries using the 121 e-Agent Framework, 2) defining the relevance challenges of CRM for academic libraries, 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications, and 4) making the approach extensible to address the challenges of CRM in other fields.

Applying Semantic Web Technologies to Meet the Relevant Challenge of Customer Relationship Management for the U.S. Academic Libraries in the 21st Century Using 121 e-Agent Framework

2011 ◽  
pp. 284-311
Author(s):  
Sharon Q. Yang ◽  
Amanda Xu
Keyword(s):  
Semantic Web ◽  
21St Century ◽  
Academic Libraries ◽  
Trust Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Web Technologies ◽  
Social Semantic Web ◽  
The Web

The main contributions of the chapter are 1) defining relevance challenge of CRM for U.S. academic libraries in the 21st century and applying social Semantic Web technologies to address the relevance challenge of CRM using 121 e-Agent framework in the Web as an infrastructure; 2) binding OLTP, OLAP, and Online Ontological Processing to social Semantic Web applications in CRM; 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications; 4) making the approach extensible to address relevance challenge of CRM in other fields.

A URI is Worth a Thousand Tags

2011 ◽  
pp. 279-302 ◽  
Author(s):  
Alexandre Passant ◽  
Philippe Laublet ◽  
John G. Breslin ◽  
Stefan Decker
Keyword(s):  
Semantic Web ◽  
User Generated Content ◽  
Social Web ◽  
Enterprise 2.0 ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
The Social ◽  
Web Of Data ◽  
Accepted Practice ◽  
The Web

Although tagging is a widely accepted practice on the Social Web, it raises various issues like tags ambiguity and heterogeneity, as well as the lack of organization between tags. We believe that Semantic Web technologies can help solve many of these issues, especially considering the use of formal resources from the Web of Data in support of existing tagging systems and practices. In this article, we present the MOAT—Meaning Of A Tag—ontology and framework, which aims to achieve this goal. We will detail some motivations and benefits of the approach, both in an Enterprise 2.0 ecosystem and on the Web. As we will detail, our proposal is twofold: It helps solve the problems mentioned previously, and weaves user-generated content into the Web of Data, making it more efficiently interoperable and retrievable.

Customer Relationship Management as an Imperative for Academic Libraries

2016 ◽  
pp. 1641-1674
Author(s):  
Amanda Xu ◽  
Sharon Q. Yang
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Academic Libraries ◽  
Linked Data ◽  
Trust Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Customer Group

This chapter proposes a conceptual model, the 121 e-Agent Framework, for Customer Relationship Management (CRM) in academic libraries. Linked data and Semantic Web are the core components of this model. The implementation of the Framework will enable the participating U.S. academic libraries to reach out to their user communities through systematic customer group identification, differentiation, and interaction. The main contributions of the chapter are 1) applying Semantic Web technologies for CRM in academic libraries using the 121 e-Agent Framework, 2) defining the relevance challenges of CRM for academic libraries, 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications, and 4) making the approach extensible to address the challenges of CRM in other fields.

Customer Relationship Management as an Imperative for Academic Libraries

2016 ◽  
pp. 395-428
Author(s):  
Amanda Xu ◽  
Sharon Q. Yang
Keyword(s):  
Semantic Web ◽  
Customer Relationship Management ◽  
Academic Libraries ◽  
Linked Data ◽  
Trust Management ◽  
Relationship Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Customer Group

This chapter proposes a conceptual model, the 121 e-Agent Framework, for Customer Relationship Management (CRM) in academic libraries. Linked data and Semantic Web are the core components of this model. The implementation of the Framework will enable the participating U.S. academic libraries to reach out to their user communities through systematic customer group identification, differentiation, and interaction. The main contributions of the chapter are 1) applying Semantic Web technologies for CRM in academic libraries using the 121 e-Agent Framework, 2) defining the relevance challenges of CRM for academic libraries, 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications, and 4) making the approach extensible to address the challenges of CRM in other fields.

Applying Semantic Web Technologies to Meet the Relevant Challenge of Customer Relationship Management for the U.S. Academic Libraries in the 21st Century Using 121 e-Agent Framework

2013 ◽  
pp. 737-764
Author(s):  
Sharon Q. Yang ◽  
Amanda Xu
Keyword(s):  
Semantic Web ◽  
21St Century ◽  
Academic Libraries ◽  
Trust Management ◽  
Customer Relationship ◽  
Semantic Web Technologies ◽  
Customer Data ◽  
Web Technologies ◽  
Social Semantic Web ◽  
The Web

The main contributions of the chapter are 1) defining relevance challenge of CRM for U.S. academic libraries in the 21st century and applying social Semantic Web technologies to address the relevance challenge of CRM using 121 e-Agent framework in the Web as an infrastructure; 2) binding OLTP, OLAP, and Online Ontological Processing to social Semantic Web applications in CRM; 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications; 4) making the approach extensible to address relevance challenge of CRM in other fields.

A URI is Worth a Thousand Tags

2009 ◽  
Vol 5 (3) ◽  
pp. 71-94 ◽  
Author(s):  
Alexandre Passant ◽  
Philippe Laublet ◽  
John G. Breslin ◽  
Stefan Decker
Keyword(s):  
Semantic Web ◽  
User Generated Content ◽  
Social Web ◽  
Enterprise 2.0 ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
The Social ◽  
Web Of Data ◽  
Accepted Practice ◽  
The Web

Although tagging is a widely accepted practice on the Social Web, it raises various issues like tags ambiguity and heterogeneity, as well as the lack of organization between tags. We believe that Semantic Web technologies can help solve many of these issues, especially considering the use of formal resources from the Web of Data in support of existing tagging systems and practices. In this article, we present the MOAT—Meaning Of A Tag—ontology and framework, which aims to achieve this goal. We will detail some motivations and benefits of the approach, both in an Enterprise 2.0 ecosystem and on the Web. As we will detail, our proposal is twofold: It helps solve the problems mentioned previously, and weaves user-generated content into the Web of Data, making it more efficiently interoperable and retrievable.

Towards Web 3.0

2010 ◽  
pp. 192-205 ◽  
Author(s):  
Tzanetos Pomonis ◽  
Dimitrios A. Koutsomitropoulos ◽  
Sotiris P. Christodoulou ◽  
Theodore S. Papatheodorou
Keyword(s):  
Semantic Web ◽  
Web 2.0 ◽  
Web Applications ◽  
Current Trend ◽  
Semantic Web Technologies ◽  
Web 3.0 ◽  
Web Technologies ◽  
Technological Limitations ◽  
Near Future ◽  
The Web

While the term Web 2.0 is used to describe the current trend in the use of Web technologies, the term Web 3.0 is used to describe the next generation Web, which will combine Semantic Web technologies, Web 2.0 principles, and artificial intelligence. Towards this perspective, in this work we introduce a 3-tier architecture for Web applications that will fit into the Web 3.0 definition. We present the fundamental features of this architecture, its components, and their interaction, as well as the current technological limitations. Furthermore, some indicative application scenarios are outlined in order to illustrate the features of the proposed architecture. The aim of this architecture is to be a step towards supporting the development of intelligent Semantic Web applications of the near future, as well as supporting the user collaboration and community-driven evolution of these applications.

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