Sphinx PHP implements Chinese word segmentation and retrieval optimization for full-text search
Introduction: With the development of the Internet and the era of information explosion, full-text search engines have become the first choice for people to conduct information An important tool for retrieval. Traditional full-text search engines are mainly optimized for Western languages such as English. However, for a special language like Chinese, traditional full-text search engines have some problems. This article will introduce how to use Sphinx PHP to realize the process of Chinese word segmentation and retrieval optimization, and provide specific code examples.
1. Chinese word segmentation
Chinese word segmentation is the process of dividing a Chinese text into independent words. It is an important link in Chinese full-text search. Traditional full-text search engines usually use inverted indexes based on word frequency for search. In the Chinese language, a word is usually composed of multiple characters, so Chinese text needs to be segmented.
Sphinx PHP provides a Chinese word segmenter extension sphinxsegs, which can split Chinese text into independent words and supports custom lexicon. The following is an example code for using sphinxsegs for Chinese word segmentation:
<?php $seg = sphinxsegs_initial(); sphinxsegs_setencoding($seg, "utf-8"); sphinxsegs_setwordlist($seg, "path/to/wordlist.dic"); $text = "中文全文搜索引擎"; $result = sphinxsegs_segment($seg, $text); print_r($result); sphinxsegs_close($seg); ?>
In the above code, we first use the sphinxsegs_initial function to initialize the Chinese word segmentation, then use the sphinxsegs_setencoding function to set the text encoding method to utf-8, and then use the sphinxsegs_setwordlist function Specify a custom lexicon file. Then, we specify the text that needs to be segmented and use the sphinxsegs_segment function to segment the text. Finally, we use the sphinxsegs_close function to close the tokenizer.
2. Search Optimization
Chinese texts usually have some special problems, such as synonyms, word weights, etc. In order to improve the recall rate and accuracy of Chinese full-text search, we need to carry out some retrieval optimization work.
Sphinx PHP provides some functions for search optimization, including synonym replacement, weight control, etc. The following is a sample code that uses Sphinx PHP for retrieval optimization:
<?php require('sphinxapi.php'); $cl = new SphinxClient(); $cl->SetServer("localhost", 9312); $cl->SetMatchMode(SPH_MATCH_EXTENDED2); $cl->SetFieldWeights(array("title" => 10, "content" => 1)); $keywords = "中文全文搜索引擎"; $result = $cl->Query($keywords, "index_name"); print_r($result); if($result && $result['total'] > 0) { foreach($result['matches'] as $match) { echo "ID: " . $match['id'] . "; Weight: " . $match['weight'] . "; Attributes: " . $match['attrs']['title'] . PHP_EOL; } } ?>
In the above code, we first introduce the Sphinx PHP client library sphinxapi.php, and create a SphinxClient object, and then set the Sphinx server through the SetServer function The address and port number, use the SetMatchMode function to set the matching mode to SPH_MATCH_EXTENDED2, and then use the SetFieldWeights function to set the field weights. Next, we specify the keywords we need to search and use the Query function to search. Finally, we process the results returned by $result.
Conclusion: This article introduces how to use Sphinx PHP to implement Chinese word segmentation and retrieval optimization, and provides specific code examples. By using the Chinese word segmenter and retrieval optimization functions provided by Sphinx PHP, we can improve the effect of Chinese full-text search and improve the recall rate and accuracy of search. I hope this article will be helpful to Chinese application developers who need to implement full-text search.
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