Search text processing method and device, equipment, storage medium and program product

Abstract

The invention relates to a search text processing method and device, computer equipment, a storage medium and a computer program product. The method comprises the following steps: acquiring a search text for searching commodities; the method comprises the following steps: performing error correction on commodity words extracted from a commodity corpus to obtain a commodity word bank, and performing word segmentation processing on a search text to obtain a word sequence; phrases formed by the independent words in the word sequence and the adjacent words of the independent words are used as potential wrongly-identified words in the search text; on the basis of the pinyin editing distance, candidate words used for correcting the potential wrongly-identified words are searched; using the commodity corpus after error correction to train the language model to obtain a commodity word language model, and determining statement smoothness of potential wrong words and candidate words; and when the statement smoothness of the potential wrong words and the target candidate words meets a replacement condition, replacing the potential wrong words in the search text with the target candidate words to obtain an error correction text. The method is suitable for a commodity search scene.

Description

technical field [0001] The present application relates to the field of computer technology, and in particular to a search text processing method, device, computer equipment, storage medium and computer program product. Background technique [0002] With the development of mobile Internet technology, online shopping has become more convenient, and users often search for products on e-commerce platforms for purchase. Limited by the user's knowledge and habits, or errors caused by the pinyin input method and handwriting input method in the Chinese scene, it is easy for users to enter search terms that contain typos. Without error correction, they will not be able to search for what they want to buy Products of. In the product search scenario, about 2.5% of the search terms contain typos. [0003] In recent years, deep learning has developed rapidly. Some deep learning models based on neural networks have achieved remarkable results in the field of text processing. However, in...

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Problems solved by technology

[0003] In recent years, deep learning has developed rapidly. Some deep learning models based on neural networks have achieved remarkable results in the field of text processing. However, in commodity search scenarios, search terms are usually short texts, and the lack of contextual information makes deep learning models unable to perform in commodity search scenarios. play a role in

In addition, due to the complexity of the error correction process of the deep learning model, it cannot well support real-time search scenarios

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