How to use PHP bloom filter for sensitive word filtering

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Release: 2023-07-08 06:14:02
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How to use PHP bloom filter to filter sensitive words

With the rapid development of the Internet, people often encounter some unpleasant things when using various social platforms, forums and chat tools. Speech and Inappropriate Content. In order to protect the user experience and maintain the health and order of the online environment, many websites and applications use sensitive word filtering technology.

Sensitive word filtering is a method of using known sensitive lexicon to check the text entered by the user to find and filter out the sensitive content. The traditional sensitive word filtering method mainly uses string matching to find whether sensitive words exist in the sensitive vocabulary database. However, as the sensitive vocabulary continues to increase, the efficiency of string matching becomes increasingly low.

In order to solve this problem, Bloom Filter came into being. Bloom filter is an efficient data structure proposed by Bloom et al. in 1970. It is mainly used to determine whether an element belongs to a certain set. In sensitive word filtering, we can use Bloom filters to quickly determine whether a word belongs to the word in the sensitive vocabulary.

Next, we will use PHP to implement a simple sensitive word filter and demonstrate how to use Bloom filters for sensitive word filtering.

First, we need to install a PHP bloom filter extension package. Here, we will use the "php-bloomfilter" package, which is a powerful and easy-to-use bloom filter extension.

Use the following command to install the "php-bloomfilter" package:

composer require bloomfilter/bloomfilter
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After the installation is complete, we can start writing the code for the sensitive word filter. First, we need to create a Bloom filter object and specify the capacity and false positive rate of the Bloom filter. The capacity refers to the number of words that the Bloom filter can store, and the false positive rate refers to the accuracy of judging whether a word belongs to the words in the Bloom filter.

use BloomFilterBloomFilter; // 创建布隆过滤器对象 $filter = new BloomFilter(100000, 0.01);
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Next, we need to load the sensitive vocabulary library and add sensitive words to the Bloom filter.

// 加载敏感词库 $sensitiveWords = file("sensitive_words.txt", FILE_IGNORE_NEW_LINES); // 将敏感词添加到布隆过滤器中 foreach ($sensitiveWords as $word) { $filter->add($word); }
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In the above code, we use the file functionfile()to read the sensitive vocabulary library. Please make sure to name the sensitive word database filesensitive_words.txt, with each sensitive word occupying one line.

Now, we can use Bloom filter to filter sensitive words.

// 检查文本是否包含敏感词 function checkSensitiveWords($text) { global $filter; $words = explode(" ", $text); foreach ($words as $word) { // 判断词是否在布隆过滤器中 if ($filter->has($word)) { return true; } } return false; } // 测试敏感词过滤 $text1 = "我爱母亲大人"; $text2 = "我讨厌坏人"; if (checkSensitiveWords($text1)) { echo "存在敏感词"; } else { echo "没有敏感词"; } if (checkSensitiveWords($text2)) { echo "存在敏感词"; } else { echo "没有敏感词"; }
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In the above code, we define acheckSensitiveWords()function to check whether the text contains sensitive words. This function splits the text into words by spaces and uses thehas()method of the Bloom filter to determine whether the word is in the Bloom filter.

Finally, we can take appropriate actions based on the inspection results, such as giving warnings or filtering out sensitive words.

Although the Bloom filter has efficient sensitive word filtering capabilities, we should also pay attention to its shortcomings. The Bloom filter has a certain misjudgment rate, that is, it may judge normal words as sensitive words. Therefore, when using Bloom filters for sensitive word filtering, we should weigh the accuracy and false positive rate according to the actual situation.

Through the above steps, we successfully implemented the sensitive word filtering function using PHP Bloom filter. I hope this article helps you understand how to use Bloom filters for sensitive word filtering!

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