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This article mainly explains "what is the concept of TF-IDF model". Interested friends may wish to have a look at it. The method introduced in this paper is simple, fast and practical. Let's let the editor take you to learn "what is the concept of TF-IDF model"?

1. The concept and algorithm of TF-IDF

In order to study the special commodity attributes of Xiaomi 10 mobile phone, explore the advantages and disadvantages of this mobile phone, continue to maintain the advantages of the phone, make up for the weakness of goods, and provide strategies for store operation, this paper uses the TF-IDF method to extract the attributes of goods.

TF-IDF 's method is suitable for the attribute extraction of goods in text mining. This method uses a weighted technique to count the importance of the statistical term to the document, and to indicate the importance of the commodity attribute by counting the response of the statistical term to the importance of the document.

Each feature word has different distinguishing ability for each category. The importance of feature words is reflected through feature selection. The class it belongs to is the class in the word set, which has the characteristics of this class. Feature words must be evenly distributed in each category document, if randomly distributed in a certain category document, it may appear that the feature word only appears in a certain document, resulting in inaccurate attribute extraction.

Information gain function IG and chi-square value CHI are commonly used to select features for the evaluation function, and chi-square value CHI is used to measure the importance of feature words. however, chi-square value CHI can not fully reflect the importance of feature words, so it is necessary to digitize the chi-square value CHI. Through digital processing, the efficiency of feature selection is improved, so as to avoid weight imbalance.

2. Extract commodity attributes by TF-IDF

Based on TF-IDF and improved TF-IDF algorithm, this paper uses ROSTCM6 tool to calculate the TF-IDF value of comment data of Xiaomi 10 mobile phone products. Realize the extraction of commodity attributes with the help of ROSTCM6 software, open the operation page of ROSTCM6 software, click the function menu of "TF/IDF batch word frequency analysis" in the "functional analysis" menu bar, import text data, and calculate the TF-IDF value.

Calculate the TF-IDF value of Xiaomi 10 mobile phone comments, and extract the first ten commodity attributes with the highest TF-IDF value, so as to extract the key attributes of Xiaomi 10 mobile phone goods, and make a column chart of Xiaomi 10 mobile phone TF-IDF value to extract commodity attributes intuitively. The calculated results are shown in the following table:

Fig. 1 the best commodity attribute of Xiaomi 10 mobile phone

At this point, I believe you have a deeper understanding of "what is the concept of the TF-IDF model". You might as well do it in practice. Here is the website, more related content can enter the relevant channels to inquire, follow us, continue to learn!

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