Manage custom text libraries

Text types

The text in custom text libraries consists of terms and text patterns.

• Terms

  Terms are designed to moderate words in text. If a sentence or a piece of text contains a certain term, the term is hit. You can add different terms for different business scenarios.

  In Content Moderation, you can apply term-based moderation to ad violation detection and text anti-spam. For more information about relevant parameters, see the parameter description of moderation operations in different scenarios.

  You can add the AND (&) and NOT (~) logical operators in Chinese terms. For example:

  • The term "A&B" is added. If a piece of text contains both A and B, the term is hit.
  • The term "A~B" is added. If a piece of text contains A but does not contain B, the term is hit.

  Note If you add both logical operators in a term, the AND (&) operator must be added before the NOT (~) operator. For example, you can add "A&B~C" as a term, but cannot add "A~C&B" as a term.
• Text patterns

  Text patterns are designed to compare the similarity between sentences or text. If two sentences or two pieces of text are partially different but express the same meaning, the two sentences or two pieces of text show a close similarity. Content Moderation can determine whether a piece of text has a close similarity to a text pattern in text pattern libraries. If the similarity reaches a certain degree, the text pattern is hit.

  You can apply text pattern libraries to text anti-spam. Content Moderation allows you to customize a blacklist, a whitelist, and a review list for text pattern libraries based on your business needs. The review list contains the text that needs human review. You can manage text patterns related to your business in text pattern libraries. In this case, the content that hits text patterns can be filtered out in text anti-spam.

Limits

Manage feedback-based text libraries

1. Log on to the Alibaba Cloud Content Moderation console.
2. In the left-side navigation pane, choose Moderation API > Risk library management. The Text Library tab of the Risk library management page appears.
   The Text Library tab lists all custom text libraries. The libraries marked with System and named in SCENARIO_FEEDBACK_WHITE or SCENARIO_FEEDBACK_BLACK format are feedback-based text libraries. For example, the ANTISPAM_FEEDBACK_BLACK library is a blacklist that consists of text patterns added by the system and is used for text anti-spam.
3. Find the target feedback-based text library and click Manage in the Operations column.
   The Manage Text Library page appears. This page lists all text patterns added to the library and displays the number of times that each text pattern is hit in the last seven days in the Detected Last 7 Days column, excluding the statistics on the current day.
4. On the Manage Text Library page, manage text patterns in the library.
   Note You can add and delete text patterns. The operations take effect in 15 minutes.

   • Click Add Text or Import and add text patterns as prompted.
   • Select text patterns that you do not need and click Delete Selected at the bottom of the page. Alternatively, find a text pattern that you do not need and click Delete in the Operations column.

Create and manage custom text libraries

1. Log on to the Alibaba Cloud Content Moderation console.
2. In the left-side navigation pane, choose Moderation API > Risk library management. The Text Library tab of the Risk library management page appears.
3. On the Text Library tab, click New.
4. In the Create Text Library dialog box that appears, set relevant parameters and click OK. The following table describes the parameters.

   Parameter	Description
   Name	The name of the custom text library. You can set the same name for multiple text libraries. However, we recommend that you set a unique name for each text library.
   Scene	The moderation scenario to which the custom text library applies. Valid values: Text Antispam: text anti-spam where the value of the scenes parameter contains antispam in API requests Ad: image moderation where the value of the scenes parameter contains ad in API requests
   Type	The type of text in the custom text library. Valid values: Keyword: matches the text to be moderated that contains terms. You can detect more risky text through terms. Similar Text: matches the text to be moderated that is similar to text patterns at a certain probability. You can detect risky text more accurately through text patterns. Note You can set this parameter to Similar Text only when the Scene parameter is set to Text Antispam.
   Match Mode	The match mode applied to the custom text library. This parameter is required when the Type parameter is set to Keyword. Valid values: Precise: matches the text to be moderated that contains the same terms in the text library. Fuzzy: preprocesses the text to be moderated and terms, and then matches the preprocessed text to be moderated that hits the preprocessed terms. The text to be moderated and terms are preprocessed in the following ways: Convert uppercase letters to lowercase letters. For example, if the text to be moderated is "bitCoin", the term "bitcoin" is hit. Convert traditional Chinese characters to simplified Chinese characters. Convert similar words. For example, if the text to be moderated is "(2)", the term "2" is hit. Note The fuzzy mode is selected by default for text pattern libraries.
   Category	The category of moderation results returned based on the custom text library. Select Keyword for Type. Valid values: Black: If the text to be moderated hits terms in the text library, the machine-assisted moderation result returns the suggestion parameter with a value of block. Review: If the text to be moderated hits terms in the text library, the machine-assisted moderation result returns the suggestion parameter with a value of review. Ignore: If the text to be moderated hits terms in the text library, the text is ignored and the machine-assisted moderation result returns the suggestion parameter with a value of pass. Select Similar Text for Type. Valid values: Black: If the text to be moderated hits text patterns in the text library, the machine-assisted moderation result returns the suggestion parameter with a value of block. Review: If the text to be moderated hits text patterns in the text library, the machine-assisted moderation result returns the suggestion parameter with a value of review. White: If the text to be moderated hits text patterns in the text library, the machine-assisted moderation result returns the suggestion parameter with a value of pass.
   bizType	The business scenario to which the custom text library applies. You can specify different text libraries in API operations to meet business needs. For example, you can use the bizType parameter to specify the text library to be applied in a specific moderation scenario. The bizType parameter takes effect in the following ways: If the bizType parameter in a moderation request is set to A, the text libraries of which the bizType parameter is set to A are used for moderation. These text libraries must be enabled. In other cases, all enabled text libraries are used for moderation. Set this parameter as needed. We recommend that you submit a ticket to Alibaba Cloud to seek technical support.

   
   The custom text library is created. You can view the created text library on the Text Library tab.
5. Optional: If the text type of the created text library is term, follow these steps to manage terms. For more information about how to manage text patterns if the text type of the created text library is text pattern, see Manage feedback-based text libraries.
   1. Find the target text library whose text type is term and click Manage in the Operations column.
      The Manage Text Library page appears. This page lists all terms added to the library and displays the number of times that each term is hit in the last seven days in the Detected Last 7 Days column, excluding the statistics on the current day.
   2. On the Manage Text Library page, manage terms in the library.
      Note You can add and delete terms. The operations take effect in 15 minutes.

      • Click Add Keyword or Import and add terms as prompted.
      • Select terms that you do not need and click Delete Selected at the bottom of the page. Alternatively, find a term that you do not need and click Delete in the Operations column.
6. Delete, modify, or disable a custom text library. Return to the Text Library tab. Select the target text library and click Delete, Modify, or Disable in the Operations column to perform the corresponding operation.