Home > Article > Backend Development > The practice of using cache to accelerate the text summary extraction process in Golang.
With the growth of large amounts of data in the information age, text summary technology has gradually become an important research direction in the field of text processing. Text summary is to extract the most important and representative information from the text to form a concise summary, which can reduce people's time and energy when processing information. In practical applications, due to the increasing amount of text data, the requirements for the speed and efficiency of text summary extraction are also getting higher and higher. This article introduces the practice of using caching to accelerate the text summary extraction process in Golang.
Text summary extraction refers to extracting the most important text information from a large amount of text data to minimize readers' reading of the text time and labor consumption. The principles of text summary extraction are usually divided into the following methods:
(1) Traditional method: by analyzing the linguistic structure of the text, understanding the contextual information, and selecting representative content including important words and clauses , thus forming a text summary.
(2) Statistical method: By analyzing the text and calculating the weight of each word, phrase and sentence, and then extracting the content with the highest weight, a text summary is formed.
(3) Machine learning method: Automatically learn the characteristics of text data by training a machine learning model to effectively extract representative content in the text.
(4) Method based on deep learning: By using neural networks to train the model, the representative content in the text can be effectively extracted.
Golang is a very popular open source programming language favored by developers for its efficiency, simplicity and intuitiveness. In Golang, there are many open source text summary extraction libraries, including textacy, gensim, spacy, etc. These libraries can help developers quickly extract representative content from text. The most commonly used technology is the keyword extraction method based on TF-IDF. The principle is that each word is given a weight value, and the weight value is determined by word frequency and document frequency. However, in the process of processing large amounts of text data, it is often necessary to improve the efficiency and speed of text summary extraction.
Caching is a common technical method that can effectively improve the efficiency and speed of the system. In text summary extraction, it is often necessary to read and write the same text multiple times, which requires the use of caching technology to speed up the reading and writing process. The methods of using caching technology in Golang can be divided into the following two types:
(1) Memory cache: Store text data in a cache in memory, which can quickly read and write data.
(2) Disk cache: Store text data in a cache on the disk, and the data can be quickly read and written when needed.
In order to speed up text summary extraction, we can use caching technology in Golang. The following are specific practical methods:
(1) Use memory cache: We can use the cache library in Golang, such as BigCache or Gocache, to quickly read and write text data in memory. When using a cache library, you need to pay attention to factors such as cache size and data cleaning strategies to ensure cache stability and consistency.
(2) Use disk cache: We can use technologies such as file systems or databases in Golang to cache text data on the hard disk. When using disk cache, you need to consider file system optimization, I/O performance and other factors to ensure data reading and writing speed and stability.
(3) Combine memory and disk cache: We can store text data in memory and disk at the same time, use memory cache to improve read and write speed, and use disk cache to improve data persistence and security.
In large-scale text data processing, it is required to improve the speed and efficiency of text summary extraction. In order to solve this problem, this article introduces the practical method of using caching technology to accelerate text summary extraction in Golang. Caching technology can effectively improve the reading and writing speed and consistency of text data and improve work efficiency. Of course, how to choose the appropriate caching technology needs to be based on specific issues.
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