Organic Knowledge Management for Web-Based Customer Service

2011 ◽  
pp. 92-108
Author(s):  
Stephen D. Durbin ◽  
Doug Warner ◽  
J. Neal Richter ◽  
Zuzana Gedeon
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Knowledge Management ◽  
Customer Service ◽  
System Architecture ◽  
The Internet ◽  
Web Based ◽  
Information Navigation ◽  
Knowledge Processes ◽  
Meta Information

This chapter introduces practical issues of information navigation and organizational knowledge management involved in delivering customer service via the Internet. An adaptive, organic approach is presented that addresses these issues. This approach relies on both a system architecture that embodies effective knowledge processes, and a knowledge base that is supplemented with meta-information acquired automatically through various data mining and artificial intelligence techniques. An application implementing this approach, RightNow eService Center, and the algorithms supporting it are described. Case studies of the use of eService Center by commercial, governmental and other types of organizations are presented and discussed. It is suggested that the organic approach is effective in a variety of information-providing settings beyond conventional customer service.

Organic Knowledge Management for Web-Based Customer Service

2011 ◽  
pp. 1971-1986
Author(s):  
Stephen D. Durbin ◽  
Doug Warner ◽  
J. Neal Richter ◽  
Zuzana Gedeon
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Knowledge Management ◽  
Customer Service ◽  
System Architecture ◽  
The Internet ◽  
Web Based ◽  
Information Navigation ◽  
Knowledge Processes ◽  
Meta Information

This chapter introduces practical issues of information navigation and organizational knowledge management involved in delivering customer service via the Internet. An adaptive, organic approach is presented that addresses these issues. This approach relies on both a system architecture that embodies effective knowledge processes, and a knowledge base that is supplemented with meta-information acquired automatically through various data mining and artificial intelligence techniques. An application implementing this approach, RightNow eService Center, and the algorithms supporting it are described. Case studies of the use of eService Center by commercial, governmental and other types of organizations are presented and discussed. It is suggested that the organic approach is effective in a variety of information-providing settings beyond conventional customer service.

scholarly journals Sistem Informasi Pelayanan Jasa pada Lucky Photo

2021 ◽  
Vol 11 (1) ◽  
pp. 81-95
Author(s):  
T Pradita ◽  
A Mubarok
Keyword(s):  
Information System ◽  
Customer Service ◽  
Service System ◽  
The Internet ◽  
Application System ◽  
Web Based ◽  
Customer Data ◽  
Service Information ◽  
Internet Media ◽  
A Company

The development of services has developed into the internet media, to make it easier for customers and employees in managing a job. In the problem of Lucky Photo, which covers services including printing, sales, stock of goods, purchases, and reports are not effective properly. The researcher aims to develop a service system entitled Service Information Systems at Lucky Photo. By building a web-based application, a waterfall method is needed to become a benchmark for the creation of a service information system, so the results will be obtained on a web-based application system to demand progress in a company, including services that become easier, easier customer service in conduct transactions, generate reports, and process customer data. So it can be concluded that with the construction of a new Service Information System it will be easier to make transactions, make it easier for customers, create reports, and process customer data that is embedded in the Mysql database which will become a well-systemized report.

scholarly journals Data Mining as Support to Knowledge Management in Marketing

2015 ◽  
Vol 6 (2) ◽  
pp. 18-30 ◽  
Author(s):  
Marijana Zekić-Sušac ◽  
Adela Has
Keyword(s):  
Data Mining ◽  
Neural Networks ◽  
Knowledge Management ◽  
Association Rules ◽  
Marketing Strategies ◽  
Web Based ◽  
Data Mining Techniques ◽  
Data Mining Approach ◽  
Model Generalization ◽  
Retail Managers

Abstract Background: Previous research has shown success of data mining methods in marketing. However, their integration in a knowledge management system is still not investigated enough. Objectives: The purpose of this paper is to suggest an integration of two data mining techniques: neural networks and association rules in marketing modeling that could serve as an input to knowledge management and produce better marketing decisions. Methods/Approach: Association rules and artificial neural networks are combined in a data mining component to discover patterns and customers’ profiles in frequent item purchases. The results of data mining are used in a web-based knowledge management component to trigger ideas for new marketing strategies. The model is tested by an experimental research. Results: The results show that the suggested model could be efficiently used to recognize patterns in shopping behaviour and generate new marketing strategies. Conclusions: The scientific contribution lies in proposing an integrative data mining approach that could present support to knowledge management. The research could be useful to marketing and retail managers in improving the process of their decision making, as well as to researchers in the area of marketing modelling. Future studies should include more samples and other data mining techniques in order to test the model generalization ability.

scholarly journals E-Learning: A Milestone in the Research of Data Mining

2012 ◽  
pp. 82-86
Author(s):  
Sabyasachi Pattnaik ◽  
Jui Pattnayak ◽  
Priyaranjan Dash
Keyword(s):  
Data Mining ◽  
Web Service ◽  
Learning Environments ◽  
System Architecture ◽  
Functional Model ◽  
Application Domain ◽  
Service Architecture ◽  
Web Based ◽  
Web Based Learning ◽  
E Learning

Data Mining and Data Warehousing are two most important techniques for pattern discovery and centralized data management in today’s technology. ELearning is one of the most significant applications of data mining. The main objective is to provide a proposal for a functional model and service architecture. The standards and system architecture are analyzed here. This paper gives importance to the integration of Web Services on the e-Learning application domain, because Web Service is the most advanced choice for distance education now. The process of e-Learning can be possible more effectively with the help of Web usage mining. More advanced tools are developed for online customer’s behaviour to increase sales, and profit, but no such tools are developed to understand learner’s behaviour in e-Learning. In this paper, some data mining techniques are discussed that could be used to enhance web-based learning environments.

scholarly journals Sharing Video Emotional Information in the Web

2013 ◽  
Vol 5 (3) ◽  
pp. 19-39 ◽  
Author(s):  
Eva Oliveira ◽  
Teresa Chambel ◽  
Nuno Magalhães Ribeiro
Keyword(s):  
Video Compression ◽  
Recommendation System ◽  
Data Access ◽  
Multimedia Data ◽  
The Internet ◽  
Video Content ◽  
Emotional Information ◽  
Web Based ◽  
Affective Content ◽  
Meta Information

Video growth over the Internet changed the way users search, browse and view video content. Watching movies over the Internet is increasing and becoming a pastime. The possibility of streaming Internet content to TV, advances in video compression techniques and video streaming have turned this recent modality of watching movies easy and doable. Web portals as a worldwide mean of multimedia data access need to have their contents properly classified in order to meet users’ needs and expectations. The authors propose a set of semantic descriptors based on both user physiological signals, captured while watching videos, and on video low-level features extraction. These XML based descriptors contribute to the creation of automatic affective meta-information that will not only enhance a web-based video recommendation system based in emotional information, but also enhance search and retrieval of videos affective content from both users’ personal classifications and content classifications in the context of a web portal.

Letting the Computers Take Over: Using AI to Solve Marketing Problems

2019 ◽  
Vol 61 (4) ◽  
pp. 156-185 ◽  
Author(s):  
Gijs Overgoor ◽  
Manuel Chica ◽  
William Rand ◽  
Anthony Weishampel
Keyword(s):  
Artificial Intelligence ◽  
Data Mining ◽  
Customer Service ◽  
Cutting Edge ◽  
Standard Process ◽  
Industry Standard ◽  
Marketing Problems

Artificial intelligence (AI) has proven to be useful in many applications from automating cars to providing customer service responses. However, though many firms want to take advantage of AI to improve marketing, they lack a process by which to execute a Marketing AI project. This article discusses the use of AI to provide support for marketing decisions. Based on the established Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, it creates a process for managers to use when executing a Marketing AI project and discusses issues that might arise. It explores how this framework was used to develop three cutting-edge Marketing AI applications.

Financial Management, Strategic Management and Digital Accounting

2011 ◽  
pp. 293-317
Author(s):  
Ashutosh Deshmukh
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Supply Chain ◽  
Financial Management ◽  
The Internet ◽  
Web Based ◽  
Chain Management ◽  
Accounting Software ◽  
Tools And Techniques ◽  
Dot Com

A dominant trend in information technology is the convergence of different software functionalities. Even after the dot-com bust or, perhaps because of it, the convergence has gathered steam. Different tools and techniques get concentrated in one solution or software in a short duration. Distinct techniques and technologies, such as accounting software, Web-based businesses, supply chain management, data warehouses and artificial intelligence, are converging as the organizations move from ERP to ERP II, integration of internal functions to integration across supply chain, and the Internet to Internet 2. Today’s ERP software packs all applications into one monster package and offers tremendous functionalities.

scholarly journals The Role of Knowledge Management and Data Mining in Improving Educational Practices and the Learning Infrastructure

2020 ◽  
Vol 39 (2) ◽  
pp. 310-323
Author(s):  
Areej Fatemah Meghji ◽  
Naeem Ahmed Mahoto ◽  
Mukhtiar Ali Unar ◽  
Muhmmad Akram Shaikh
Keyword(s):  
Data Mining ◽  
Knowledge Management ◽  
Vital Role ◽  
Educational Practices ◽  
Student Management ◽  
Knowledge Processes ◽  
Higher Educational ◽  
And Performance ◽  
Improved Learning

Higher Educational Institutes hold a central and vital role in the knowledge economy. Knowledge generated by these institutes needs to be collected and disseminated to bring about improvement in not only student learning and performance, but also in educational practices, processes and the society in general. Sadly, in many institutes, this knowledge is rarely recognized, captured, analysed or utilized. Apart from the need for improved learning outcomes, rapid growth in educational data and technology has motivated several educational institutes to implement Knowledge Management (KM). KM is the key to enable educational institutes reach their goals and achieve their objectives. This paper explores the basic concept of KM and addresses the need of KM in higher educational institutes by proposing a framework to improve knowledge processes and practices in academia. This paper also highlights the role of data mining in facilitating KM in higher education through a case study that focuses on aspects of student management. Using data mining methods of pattern discovery and association rule mining, interesting patterns have been discovered from academic data that can be used for effective pedagogical decision making. The applications and challenges faced in the implementation of KM within higher educational institutes have also been briefly discussed.

scholarly journals Sharing, Evaluating and Organizing E-mail: The KM-Mail Approach Towards a Platform for Enterprise-Wide Knowledge Management

2017 ◽  
Vol 1 (1) ◽  
pp. 69-83
Author(s):  
K.G. Lim ◽  
Y.N. Cheah
Keyword(s):  
Knowledge Management ◽  
Knowledge Sharing ◽  
Significant Role ◽  
Knowledge Economy ◽  
Discussion Groups ◽  
The Internet ◽  
Alternative Strategies ◽  
Web Based ◽  
Management Platform ◽  
E Mail

Knowledge is gaining importance in the world's economy, and the Internet is playing a significant role in the knowledge economy especially with knowledge sharing tools such as web-based and e-mail discussion groups. Present discussion groups have weaknesses in their effectiveness in knowledge sharing and reuse in many enterprises. To address these weaknesses, alternative strategies can be employed to enhance the knowledge menagement capabilities of the Internet in general and e-mail in particular. We present a novel knowledge management-based e-mail (KM-Mail) framework that capitalizes on the ubiquitous utilization of e-mail for knowledge sharing and reuse. We will also outline a mechanism to allow the evaluation and organization of knowledge shared via e-mail. Finally, we discuss the incorporation of KM-Mail into a wider enterprise-wide knowledge management platform.

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