Document Categorization Engine Based on Machine Learning Techniques

Jamal Alhiyafi; Asmaa Alnahwi; Rawan Alkhurissi; Masha’er Bayomi; Manar Bayoumi; Mona Altassan; Alaa Alahmadi; Sunday O. Olatunji; Ahmed A. Maarouf

doi:10.1109/ICCISci.2019.8716398

Document Categorization Engine Based on Machine Learning Techniques

Jamal Alhiyafi, Asmaa Alnahwi, Rawan Alkhurissi, Masha’er Bayomi, Manar Bayoumi, Mona Altassan, Alaa Alahmadi, Sunday O. Olatunji, Ahmed A. Maarouf

Kettering University

Research output: Contribution to conference › Presentation

Abstract

Analysts, researchers, and other users from different fields may spend a lot of time recognizing their work-related documents and organizing them in a way that allows them to make the best use of their content. In this regard, we propose a Document Categorization Engine (DCE) that utilizes concepts of machine learning techniques and data mining. The project aims to develop a system that is capable of classifying documents based on user defined criteria.

Original language	American English
DOIs	https://doi.org/10.1109/ICCISci.2019.8716398
State	Published - Apr 3 2019
Event	2019 International Conference on Computer and Information Sciences (ICCIS) - Duration: Apr 3 2019 → …

Conference

Conference	2019 International Conference on Computer and Information Sciences (ICCIS)
Period	4/3/19 → …

Disciplines

Computer Sciences

Access to Document

10.1109/ICCISci.2019.8716398License: Unspecified

Cite this

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title = "Document Categorization Engine Based on Machine Learning Techniques",

abstract = " Analysts, researchers, and other users from different fields may spend a lot of time recognizing their work-related documents and organizing them in a way that allows them to make the best use of their content. In this regard, we propose a Document Categorization Engine (DCE) that utilizes concepts of machine learning techniques and data mining. The project aims to develop a system that is capable of classifying documents based on user defined criteria. ",

author = "Jamal Alhiyafi and Asmaa Alnahwi and Rawan Alkhurissi and Masha{\textquoteright}er Bayomi and Manar Bayoumi and Mona Altassan and Alaa Alahmadi and Olatunji, \{Sunday O.\} and Maarouf, \{Ahmed A.\}",

note = "Analysts, researchers, and other users from different fields may spend a lot of time recognizing their work-related documents and organizing them in a way that allows them to make the best use of their content. In this regard, we propose a Document Categorization Engine (DCE) that utilizes concepts of machine learning techniques and data mining.; 2019 International Conference on Computer and Information Sciences (ICCIS) ; Conference date: 03-04-2019",

year = "2019",

month = apr,

day = "3",

doi = "10.1109/ICCISci.2019.8716398",

language = "American English",

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TY - CONF

T1 - Document Categorization Engine Based on Machine Learning Techniques

AU - Alhiyafi, Jamal

AU - Alnahwi, Asmaa

AU - Alkhurissi, Rawan

AU - Bayomi, Masha’er

AU - Bayoumi, Manar

AU - Altassan, Mona

AU - Alahmadi, Alaa

AU - Olatunji, Sunday O.

AU - Maarouf, Ahmed A.

N1 - Analysts, researchers, and other users from different fields may spend a lot of time recognizing their work-related documents and organizing them in a way that allows them to make the best use of their content. In this regard, we propose a Document Categorization Engine (DCE) that utilizes concepts of machine learning techniques and data mining.

PY - 2019/4/3

Y1 - 2019/4/3

N2 - Analysts, researchers, and other users from different fields may spend a lot of time recognizing their work-related documents and organizing them in a way that allows them to make the best use of their content. In this regard, we propose a Document Categorization Engine (DCE) that utilizes concepts of machine learning techniques and data mining. The project aims to develop a system that is capable of classifying documents based on user defined criteria.

AB - Analysts, researchers, and other users from different fields may spend a lot of time recognizing their work-related documents and organizing them in a way that allows them to make the best use of their content. In this regard, we propose a Document Categorization Engine (DCE) that utilizes concepts of machine learning techniques and data mining. The project aims to develop a system that is capable of classifying documents based on user defined criteria.

UR - https://ieeexplore.ieee.org/abstract/document/8716398

U2 - 10.1109/ICCISci.2019.8716398

DO - 10.1109/ICCISci.2019.8716398

M3 - Presentation

T2 - 2019 International Conference on Computer and Information Sciences (ICCIS)

Y2 - 3 April 2019

ER -

Document Categorization Engine Based on Machine Learning Techniques

Abstract

Conference

Disciplines

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