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ISSN 1004-9037
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Edited by: Editorial Board of Journal of Data Acquisition and Processing
P.O. Box 2704, Beijing 100190, P.R. China
Sponsored by: Institute of Computing Technology, CAS & China Computer Federation
Undertaken by: Institute of Computing Technology, CAS
Published by: SCIENCE PRESS, BEIJING, CHINA
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      09 May 2023, Volume 38 Issue 3
    Article

    A STUDY ON TECHNIQUES AND TOOLS ASSOCIATE WITH WEB CONTENT
    M. Karthica 1, Dr. K. Meenakshi Sundaram2
    Journal of Data Acquisition and Processing, 2023, 38 (3): 898-909 . 

    Abstract

    Machine learning, as well as data mining are research areas of computer technology whose quick development is due to the advances in data analysis research, growth in the database industry as well as the resulting market needs for methods that are capable of extracting valuable knowledge from large data stores. It is a powerful platform that stores as well as retrieves mass information and it becomes a time-consuming uncomfortable task to search the information due to the unstructured as well as heterogeneous nature of data on the web development. In the recent past, the advancement in computer and multimedia technologies has led to the production of digital images and cheap large image depositories. The size of image collections has increased fleetly due to this, comprising digital libraries, medical images, etc. To attack this rapid-fire growth, it's needed to develop an image reclamation system that operates on a large scale. The primary end is to make a robust system that creates, manages, and query image databases in an accurate manner. The World Wide Web delivers a great platform that stores and retrieves mass information. It becomes a time-consuming and uncomfortable assignment to search the information due to its unstructured and heterogeneous nature of data on the World Wide Web. Web mining is one of the widespread techniques of data mining that is used to determine and extract useful information from web documents and their facilities. Web usage mining, web structure, and web content are three different types of web data mining. Each of these categories has numerous methods, tools, and approaches to excerpt data from the volume of information over the web. This review paper states various issues while encountering information from the web and also states several problems that occurred while finding appropriate information from the web.

    Keyword

    Text mining, Web Usage Mining, Summarization, Clustering, Information retrieval.


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ISSN 1004-9037

         

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