Knowledge Map Management System for Virtual Communities: A Review

This literature review examines Knowledge Map Management Systems, focusing on their application in sharing, creating, managing, and presenting knowledge data. It explores the use of data mining and information retrieval techniques to manage dynamic knowledge within online communities. The review analyzes previous research, particularly in information retrieval and data clustering, for extracting document concepts and performing cluster analysis on textual data. The research methodology employed recall and precision methods, along with information retrieval techniques for assessing document relevancy. Strategies such as Deep, Wide, and Mix strategies were implemented for research. The analysis highlights the proposal of a Knowledge Map Management System with features like Knowledge Navigation, Advisory Learning, and Knowledge Seeking, evaluating knowledge flow patterns and knowledge representation. The reviewed research effectively manages, shares, and represents data, making the best use of available knowledge.

KNOWLEDGE MANAGEMENT
KNOWLEDGE MAP MANAGEMENT SYSTEM

INTRODUCTION:
• Share, Create, Manage and present
the Knowledge data or Information.
• Uses techniques of Data Mining and
Information Retrieval to develop
this system.
• Aiming to manage the dynamic
knowledge of various communities
on the internet.

LITERATURE REVIEW:
• Implemented for gathering knowledge from the previous
researches done on the Knowledge Map Management
System.
• Two literatures used of Information Retrieval and Data
Clustering.
• Extraction of the document’s concept done by the
Information Retrieval.
• Cluster analysis of the textual data done by the Document
Clustering.

RESEARCH METHODOLOGY:
• Recall and Precision method used for developing the system.
• Methods of Information Retrieval is used for document
relevancy.
• Three strategies has been implemented for conducting the
research which are Deep Strategy, Wide Strategy and Mix
Strategy.

RESEARCH ANALYSIS:
• Authors tried to propose a Knowledge Map Management
System.
• The authors tried included features like Knowledge
Navigation, Advisory Learning and Knowledge Seeking.
• This research is not related with some prior domain of
knowledge.
• Learning Advisory technique introduced but not
implemented.

RELATIONSHIP WITH KNOWLEDGE
MANAGEMENT:
• Evaluates Knowledge flow patterns of data.
• Best use of Knowledge has been made in this research.
• This research present the knowledge among others.
• With representation also effectively manage and share data.

REFERENCES:
• Forsati R, Keikha A & Shamsfard M. An improved bee colony optimization algorithm
with an application to document clustering. Neurocomputing. 2015 Jul 2;159:9-26.
• Hislop D, Bosua R & Helms R. Knowledge management in organizations: A critical
introduction. Oxford University Press; 2018 Mar 29.
• Lin, F, & C Hsueh, "Knowledge map creation and maintenance for virtual
communities of practice.". in Information Processing & Management, 42, 2006, 551-
568.
• Witten IH, Frank E, Hall MA & Pal CJ. Data Mining: Practical machine learning tools
and techniques. Morgan Kaufmann; 2016 Oct 1.