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Proficient Extraction and Management of Knowledge via Machine Intelligence

by Manjit Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 46 - Number 24
Year of Publication: 2012
Authors: Manjit Kaur
10.5120/7129-9777

Manjit Kaur . Proficient Extraction and Management of Knowledge via Machine Intelligence. International Journal of Computer Applications. 46, 24 ( May 2012), 33-36. DOI=10.5120/7129-9777

@article{ 10.5120/7129-9777,
author = { Manjit Kaur },
title = { Proficient Extraction and Management of Knowledge via Machine Intelligence },
journal = { International Journal of Computer Applications },
issue_date = { May 2012 },
volume = { 46 },
number = { 24 },
month = { May },
year = { 2012 },
issn = { 0975-8887 },
pages = { 33-36 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume46/number24/7129-9777/ },
doi = { 10.5120/7129-9777 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:40:32.078175+05:30
%A Manjit Kaur
%T Proficient Extraction and Management of Knowledge via Machine Intelligence
%J International Journal of Computer Applications
%@ 0975-8887
%V 46
%N 24
%P 33-36
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Artificial intelligence is the brainpower of machines. Due to the propagation of information knowledge and information systems increasingly have the ability to gather vast quantity of data in the various number of DB [3, 5]. A basic crisis in Artificial Intelligence (AI) is that no one be familiar with what intelligence is. The crisis is mainly sharp when a user want to think artificial systems which are appreciably diverse to humans [13]. In this paper, I approach the different ways such as a user take a number of familiar definitions of machine intelligence that have been specified by proficient, and extract their important aspects. In this paper, a study of the proposed model of the Machine Intelligence (MI) used for the knowledge extraction and Knowledge Management (KM) is presented. The system recognizes the regular attainment of knowledge. The research area also highlights how to systematize the extracted knowledge, selecting a method linked to the field of interest. It improves the reasoning aptitudes of expert systems with the facility of simplify and the management of knowledge in incomplete cases.

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Intelligence (ai) Expert Systems Knowledge Extraction (ke) Knowledge Management (km) Machine Intelligence (mi)

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