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

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.

Author(s):  
Sharon Q. Yang ◽  
Amanda Xu

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.


Author(s):  
Amanda Xu ◽  
Sharon Q. Yang

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.


2016 ◽  
pp. 1641-1674
Author(s):  
Amanda Xu ◽  
Sharon Q. Yang

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.


Author(s):  
Amanda Xu ◽  
Sharon Q. Yang

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.


Author(s):  
Ángel García-Crespo ◽  
Ricardo Colomo-Palacios ◽  
Juan Miguel Gómez-Berbís ◽  
Fernando Paniagua Martín

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.


Web Services ◽  
2019 ◽  
pp. 1068-1076
Author(s):  
Vudattu Kiran Kumar

The World Wide Web (WWW) is global information medium, where users can read and write using computers over internet. Web is one of the services available on internet. The Web was created in 1989 by Sir Tim Berners-Lee. Since then a great refinement has done in the web usage and development of its applications. Semantic Web Technologies enable machines to interpret data published in a machine-interpretable form on the web. Semantic web is not a separate web it is an extension to the current web with additional semantics. Semantic technologies play a crucial role to provide data understandable to machines. To achieve machine understandable, we should add semantics to existing websites. With additional semantics, we can achieve next level web where knowledge repositories are available for better understanding of web data. This facilitates better search, accurate filtering and intelligent retrieval of data. This paper discusses about the Semantic Web and languages involved in describing documents in machine understandable format.


Author(s):  
Vudattu Kiran Kumar

The World Wide Web (WWW) is global information medium, where users can read and write using computers over internet. Web is one of the services available on internet. The Web was created in 1989 by Sir Tim Berners-Lee. Since then a great refinement has done in the web usage and development of its applications. Semantic Web Technologies enable machines to interpret data published in a machine-interpretable form on the web. Semantic web is not a separate web it is an extension to the current web with additional semantics. Semantic technologies play a crucial role to provide data understandable to machines. To achieve machine understandable, we should add semantics to existing websites. With additional semantics, we can achieve next level web where knowledge repositories are available for better understanding of web data. This facilitates better search, accurate filtering and intelligent retrieval of data. This paper discusses about the Semantic Web and languages involved in describing documents in machine understandable format.


Author(s):  
Amrapali Zaveri ◽  
Andrea Maurino ◽  
Laure-Berti Equille

The standardization and adoption of Semantic Web technologies has resulted in an unprecedented volume of data being published as Linked Data (LD). However, the “publish first, refine later” philosophy leads to various quality problems arising in the underlying data such as incompleteness, inconsistency and semantic ambiguities. In this article, we describe the current state of Data Quality in the Web of Data along with details of the three papers accepted for the International Journal on Semantic Web and Information Systems' (IJSWIS) Special Issue on Web Data Quality. Additionally, we identify new challenges that are specific to the Web of Data and provide insights into the current progress and future directions for each of those challenges.


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