一种基于nlp学习的自定义方法,用于自动阻止分散注意力的网站

Yulin Zhang, Yu Sun
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引用次数: 0

摘要

在过去的几十年里,注意力分散的问题及其伴随的副作用已经深深扎根于我们日常生活的方方面面,并对年轻一代的影响越来越大[2]。除了其惊人的普遍性外,分心的另一个最令人担忧的特点是,当我们使用电子设备作为解决问题的手段时,很容易从手头的任务中分心[3]。本文试图通过一种智能检测、分析和屏蔽网站的技术方法,彻底解决这一社会普遍存在的问题。我们的设计突出了机器学习和自然语言处理的应用,并且完全使用Python, Javascript和其他几种web开发语言实现。在通过网页抓取过程从目标网站检索到网页内容后,通过使用NLP将数据汇总为一些简短的段落,我们能够对结果进行数据分析,并最终相应地屏蔽网站[4]。在这个扩展的帮助下,学生和那些希望提高工作集中力的人将能够把更多的注意力放在手头的任务上,从而提高他们在任何工作条件下的工作效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A NLP-learning Powered Customizable Approach Towards Auto-blocking Distracting Websites
Over the past few decades, the problem of distraction and its accompanying side effects has taken its root deeply in all parts of our daily life and extended its ever-increasing influences among young generations [2]. In addition to its alarming prevalence, another characteristic of distraction that raises most concerns is how easily we can get distracted from our tasks at hand while using the electronic devices as a means of solving problems [3]. This paper attempts to address this society-wide problem thoroughly and universally through a technical approach of detecting, analyzing, and blocking the websites intelligently. Our design highlights the applications of machine learning and natural language processing, and is implemented purely in Python, Javascript, and several other web development languages. After retrieving the web content from the target websites through the web scraping process, summarizing the data to a number of short paragraphs via the use of NLP, we were able to perform data analysis on the result and finally block the websites accordingly [4]. With the help of this extension, students and those who wish to improve their concentration in work will be able to put more focus on the tasks at hand and thus boost their work efficiency under any working conditions.
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