recent trends of knowledge extraction and decision-making process using web mining- tutorsindia.com


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Data Mining

01 Data information is classified in to two typesshallow web and deep web.

Data in the deep web are often inaccessible to thesearch engine and it can only accessed by website’sinterface while data in the shallow web can beaccessed by the search engines.

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In the data mining networks, there are three sorts ofmining: data mining, web mining and text mining.

Web mining lies in the middle of data mining and textmining, and adapts for the most part to semi-structureddata and/or unstructured data.

Web

Min

ing


Web content mining isperformed by extractingimportant informationfrom the content of awebpage/website.

Web mining is a pieceof both informationextraction andinformation retrieval.

Web mining supportsmachine learning sinceit improves theclassification of text.

Web mining is integration ofinformation that is accumulatedby customary data miningsystems with informationassembled over World Wide.

While extracting the data, hugedata has been generated sothere is a need for interesting techniques , algorithms andpatterns for mining such data.

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Web Structure Mining


The method toward discovering the structureddata from web is referred to as web structuremining.

This mining may be performed eitherdocument level or hyperlink level. Thehyperlinks offer a clear route and purposeto the pages.

This can be utilized to recover theimportant data in form ofstructure.

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Web Content Mining

Web content mining information could bestructured or unstructured/semi-structured even web is unstructured.

It's the method of retrieving information from webinto a more of structured forms and classifyingthe data to retrieve quickly or finding valuableinformation from online page or web documents.

Online page mining includes the onlinedocuments which contain text, HTML,multimedia documents, i.e., images, audio, videoand sound etc.

The search result mining contains onlinesearch results. It'd be structuredocuments or unstructured documents.

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WebContentMining

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Web Usage Mining

Web usage mining is employed to find the usage patterns type from theusage data. This includes server data (IP address), Application server(web logic), and Application level (events).

This can be otherwise a discovery of substantive patterns from datagenerated by client-server transactions on one or additional web localities.The source of the data is access logs, referrer logs, agent logs, andclient-side cookies.

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Web Challenges

Web usage mining essentially has numerous advantageswhich make this technology attractive to corporationsincluding the government agencies.

This technology has enabled e-commerce to dopersonalized marketing, which eventually results inhigher trade volume.

This technology is mostly criticized only for theirprivacy concern, and it is said that it is lost whenan individual involving in the web usage obtained isused.

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Future Works

In future usage of the data on the web growsrapidly, so research on the study is carriedout more on process mining, web mining,privacy and threat and fraud analysis.

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The self-made application of web mining forprophetical prefetching of pages by abrowser has been demonstrated.

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Web mining is often applied to perceive thebehaviour of those services, and also thedata extracted are often helpful for numerouskinds of optimizations.

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It's necessary to try and do analysis ofweblogs for web services performanceimprovement.

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Analysis is required in developing webmining techniques to boost numerousdifferent aspects of internet services.

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recent trends of knowledge extraction and decision-making process using web mining- tutorsindia.com

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