Model Introduction

Word frequency and part-of-speech analysis leverages the natural language processing tool PyLTP, supplemented by our extensive lexicon developed over the years. It segments words and tags their parts of speech in the text user inputed, producing a specified number of high-frequency word statistics and part-of-speech distribution insights. Additionally, the system generates a visual word cloud based on the frequency of the words, allowing users to customize the word cloud to their preferences, including adjustments to its shape, word size, and spacing. This makes it easy to create visually appealing word clouds that meet professional standards.

To run this model, you need to perform simple parameter settings. Click on [Create Algorithm Task] to enter the model settings interface. Then, configure the parameters such as the data range to be analyzed and the number of output words, after which you can start executing the analysis task. The main parameters include the following:

Task name: Assign a name to the created task.

Database: Select the database that contains the data to be analyzed.

Analysis field: Choose the data field that needs to be analyzed.

Filtering conditions: Filter the data range to be analyzed based on specific conditions.

Word segmentation granularity: By default, only words with two or more characters are output, but you can also choose to include single characters.

Number of words: Indicate the number of high-frequency words to be output.

 Part-of-speech analysis: Decide whether to conduct part-of-speech analysis.