Journal of Computer Engineering & Information TechnologyISSN : 2324-9307

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Opinion Article, J Comput Eng Inf Technol Vol: 12 Issue: 2

Knowledge Management and Retrieval of Information

Mario Ramos*

Department of Business Administration, University of Castilla-La Mancha, Toledo, Spain

*Corresponding Author: Mario Ramos
Department of Business Administration, University of Castilla-La Mancha, Toledo, Spain

Received date: 28 February, 2023, Manuscript No. JCEIT-23-96413;

Editor assigned date: 03 March, 2023, Pre QC No. JCEIT-23-96413(PQ);

Reviewed date: 17 March, 2023, QC No JCEIT-23-96413;

Revised date: 24 March, 2023, Manuscript No. JCEIT-23-96413(R);

Published date: 31 March, 2023, DOI: 10.4172/2324-9307.1000268

Citation: Ramos M (2023) Knowledge Management and Retrieval of Information. J Comput Eng Inf Technol 12:2.


Information Retrieval (IR) and Knowledge Management (KM) are two closely related fields that deal with the organization, storage, retrieval, and dissemination of information. They share many common goals and techniques, but also have some key differences.

Information Retrieval (IR) is the process of obtaining relevant information from a collection of unstructured or semi-structured data sources, such as documents, web pages, images, videos, and audio files. The primary goal of IR is to provide users with access to the information they need in a timely and efficient manner. The process typically involves the following steps.


IR systems first index the content of the data sources to provide a searchable database. This involves extracting relevant features from the data, such as keywords, concepts, and metadata, and assigning them to index terms.


Users enter queries in the form of keywords, phrases, or natural language questions, which are then matched against the indexed content to retrieve relevant documents. IR systems use various ranking algorithms to sort the results by relevance and present them to the user.


IR systems are evaluated based on various performance metrics, such as precision, recall, and F-measure, which measure the system's effectiveness in retrieving relevant information.


IR systems can also incorporate user feedback to improve their performance over time. For example, users can provide relevance feedback by indicating which results are relevant and which are not.

Knowledge Management (KM) is the process of capturing, producing, organizing, sharing, and using knowledge and expertise within an organization to achieve its strategic objectives. The primary goal of KM is to enable individuals and teams to learn from past experiences, leverage best practices, and make better decisions based on insights derived from data and information. The process typically involves the following steps:

KM systems capture knowledge from various sources, such as documents, reports, databases, and people's expertise. This involves identifying and extracting relevant information, and storing it in a structured format. These systems encourage knowledge creation by fostering collaboration, innovation, and continuous learning. This involves providing tools and platforms for sharing ideas, insights, and feedback, and encouraging experimentation and exploration.

Systems organize knowledge by categorizing, classifying, and tagging it based on its relevance, context, and purpose. This involves producing taxonomies, ontologies, and metadata schemas to facilitate retrieval and reuse.

KM systems enable knowledge sharing by providing access to knowledge assets and encouraging reuse and adaptation. This involves providing knowledge repositories, wikis, forums, and other communication channels to enable individuals and teams to access and contribute to the knowledge base. These systems support knowledge application by providing tools and frameworks for analyzing, synthesizing, and applying knowledge to solve problems and make decisions. This involves providng knowledge maps, decision support systems, and other analytical tools to enable individuals and teams to leverage the knowledge base.

IR and KM are closely related fields, as they both deal with information and knowledge. However, they have some key differences. IR focuses on retrieving information from a large, unstructured data set, whereas KM focuses on managing and leveraging knowledge within an organization. IR is mainly concerned with efficiency and relevance, whereas KM is concerned with effectiveness and value creation. IR is often used for information discovery, whereas KM is used for knowledge sharing and collaboration. Finally, IR is mainly a technical field, whereas KM is a multidisciplinary field that encompasses technical, social, and organizational aspects. Both Information Retrieval and Knowledge Management play an important role in managing and leveraging information and knowledge. IR focuses on retrieving relevant information from unstructured data sources, while KM focuses on capturing, prducing, organizing.

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