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引用次数: 0

摘要

由于数字数据收集技术的迅速兴起,大量的数据已经成为可用的。非结构化和不饱和数据占现有数据的85%以上。从大量数据中找到可接受的趋势和模式来解释文本文档是一个主要挑战。从大量文本文档中提取有价值和重要模式的过程称为文本挖掘。有各种各样的策略和工具来挖掘文本,为未来的预测和决策提供有用的信息。为了提高速度,减少获取重要数据所需的时间和精力,采用了一种适当的文本挖掘方法。本文讨论和分析了文本挖掘技术及其在许多生活领域中的适用性。此外,还发现了文本挖掘领域的挑战,这些挑战影响了结果的准确性和相关性。
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Review on Text Mining: Techniques, Applications and Issues
Due to the rapid rise of digital data collection techniques, a vast amount of data has become available. Unstructured and unsaturated data account for more than 85 percent of present data. Finding acceptable trends and patterns to interpret text documents from huge amounts of data is a major challenge. The process of extracting valuable and nontrivial patterns from large amounts of text documents is known as text mining. There are a variety of strategies and tools for mining text for useful information for future forecasting and decision-making. To boost the speed and reduce the time and effort required to obtain important data, an appropriate and proper text mining methodology is applied. This paper discusses and analyses text mining techniques and their applicability in numerous areas of life. Furthermore, challenges in the field of text mining have been discovered, which have an impact on the accuracy and relevance of the results.
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