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Survey of Text Mining Technology

Yuan Jun-peng

Open publisher page 5 citations

Abstract

Text Mining,also known as intelligent text analysis,text data mining or Knowledge-Discovery in Text(KDT),is a rapidly emerging field concerned with the extraction of concepts,relations,and implicit knowledge from texts.As most information(over 80%) is stored as text,text mining is believed to have a high commercial potential value.Firstly,this review paper discusses the research status of text mining,then it lays out the framework of text mining and analyses techniques of text mining,such as feature selection,automatic abstracting,text categorization,text clustering,text association,data visualization.In the end, it shows the importance of text mining in knowledge discovery and highlights the upcoming challenges of text mining and the opportunities it offers.

About this research paper

What this paper is about

Text Mining,also known as intelligent text analysis,text data mining or Knowledge-Discovery in Text(KDT),is a rapidly emerging field concerned with the extraction of concepts,relations,and implicit knowledge from texts.As most information(over 80%) is stored as text,text mining is believed to have a high commercial potential value.Firstly,this review paper discusses the research status of text mining,then it lays out the framework of text mining and analyses techniques of text mining,such as feature selection,automatic abstracting,text categorization,text clustering,text association,data visualization.In the end, it shows the importance of text mining in knowledge discovery and highlights the upcoming challenges of text mining and the opportunities it offers.

Why it matters

OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Text Mining,also known as intelligent text analysis,text data mining or Knowledge-Discovery in Text(KDT),is a rapidly emerging field concerned with the extraction of concepts,relations,and implicit knowledge from texts.As most information(over 80%) is stored as text,text mining is believed to have a high commercial potential value.Firstly,this review paper discusses the research status of text mining,then it lays out the framework of text mining and analyses techniques of text mining,such as feature selection,automatic abstracting,text categorization,text clustering,text association,data visualization.In the end, it shows the importance of text mining in knowledge discovery and highlights the upcoming challenges of text mining and the opportunities it offers.

Key concepts: Computer science, Knowledge extraction, Concept mining, Biomedical text mining, Text mining, Text graph, Information retrieval, Noisy text analytics

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