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To study and analyze Information Filtering approaches

for Emergency responders during Crisis Management

 

FEATURED PAPER

By Vedna Sharma

Institute of Technology Management
Defense Research & Development Organization

Mussoorie Uttarakhand, India

 



Abstract

Information filtering is a function to select useful information for the user among a large amount of information. Among Organizations major distinctive feature of information filtering is transition from the classical activity of Information Retrieval to organized information Filtering, then conversion of filtered information into Knowledge to help decision making. This function has become very important as network technology develops rapidly and to making fast decision with overcome cost of time with the increasing value of time among organization. This paper focuses on information filtering for emergency management. When a large-scale disaster happens, the problem of information flood can be very serious because a great deal of information occurs in a short time and is sent to a person or an organization that is responsible for managing the situation. Information filtering systems filter data items by correlating vector of terms that represents data items e.g. documents, emails.

In previous years, neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks on Information Filtering systems has received relatively less scrutiny. Many IF Systems have been developed in previous years for various application domains. Some examples of filtering applications are searching personal mails based on personal profiles or newsgroup filter for groups or individuals. In this paper we emphasis to study and analysis techniques for acquiring knowledge of user for information filtering, various concepts, approaches and components in IF System.

Keywords:  Information Filtering, Emergency Management, user profile, Deep Learning, Information filtering Types

  1. Introduction

Information filtering (IF) is one of the methods that are rapidly evolving to manage large information flows. It deals with the delivery of information that the user is likely to find interesting or useful. Because knowledge represents an important aspect for an organization and a way to compete more efficiently, strategic information systems. In front of the critical proliferation of electronic information and the underlying difficulty to manage this information in a relevant way, the usual answer is to reduce drastically the volume of documents available to the end users using abstracting or filtering process.

Information filtering combines tools from the field of Artificial Intelligence (AI), such as intelligent agents or software robots, with information retrieval approaches, indexing and retrieving of content [3].

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To read entire paper, click here

 

How to cite this paper: Sharma, V. (2018). To study and analyze Information Filtering approaches for Emergency Responders during Crisis Management; PM World Journal, Vol. VII, Issue VI – June. Retrieved from https://pmworldjournal.net/wp-content/uploads/2018/06/pmwj71-Jun2018-Sharma-information-filtering-for-emergency-responders-featured-paper.pdf



About the Author


Vedna Sharma

Mussoorie Uttarakhand, India

 

 

Ms Vedna Sharma received M.tech & B.tech degrees in Computer Science from Himachal Pradesh Technical University & HPU Shimla respectively. She is currently working as Junior Research Fellow (JRF) at the Institute of Technology Management, Mussoorie Ministry of Defense (DRDO), Landour Cantt. Mussoorie Uttarakhand, India. She can be contacted at [email protected]