The function of automatically adding pictures to articles, what kind of content is not suitable for it is manual selection

The automatic image matching feature is not as good as manual selection in what kind of content - any content where 'the image must be responsible for the facts' is not. The task of automatically matching images based on title content is undertaken by automatic image matching in AnQiCMS, which is good at large quantities, frequent updates, and regular news that the image only plays a guiding role in reading; once the image itself carries information, such as product appearance, operation steps, and data charts, the automatically assigned image does not match the text, and the reader sees the wrong one. The criteria are simple: if the image is misplaced, will it mislead the reader, and if so, don't hand it over to automatic allocation.

What rules does the automatic image matching use to select images

The title automatically matches a picture based on the content features in the title, and allocates a matching picture from the library accordingly. It does not read the factual content of the text or judge whether the details in the picture are consistent with the description in the article, so it is suitable for scenarios where pictures are only used for visual guidance. Understanding this, you can sort the picture library by theme when configuring, making the allocation results more stable; when the picture library is disorganized or the styles of pictures with the same theme vary greatly, the effect of automatic allocation will be significantly reduced.

What type of content is suitable to use it directly

Daily news, industry trends, reposted summaries, column weekly reports and such content, the main body carries information in text, images are part of the page visual, and the quantity is large, the cost of manually selecting images one by one is not cost-effective. On multilingual sites, the entire page HTML is translated after translation, and images also need to be matched, as long as the visual consistency of the same translation with the original text, it is convenient to allocate according to the title at this time. In the scenario of scheduling batch releases at regular intervals, automatic image matching allows the articles that are queued to not need to open one by one to fill in images, which is the actual value aspect of it.

What type of content must be manually selected for images

Three categories must be manually processed. The first category is product and physical diagrams: the model, interface location, and color must be consistent with the text. A wrong diagram directly affects the transaction and return. The second category is tutorial and step diagrams: the screenshots must be consistent with the current version of the interface, and the automatically allocated general diagrams will point to non-existent buttons. The third category is charts and data: the numbers in the diagram must be consistent with the text, which falls under the scope of fact checking and cannot be entrusted to matching algorithms.

Content involving people, events, and time also requires manual processing. A wrong illustration may cause compliance issues. Materials with copyright requirements also need to be manually confirmed for the source and scope of use.

After the illustration is added, what else needs to be done

The image description text is often overlooked. After the automatic image is provided, the description, alternative text, and source annotation still need to be written manually: the description explains the relationship between the image and the text, the source explains the origin of the image. Readers and search engines rely on this text to understand the image. This step is similar to the logic of AI tags and TDK generation - AI tags provide candidate tags when building articles, TDK automatically generates titles, keywords, and descriptions, and editors check them before publication. If the automatically generated content is disconnected from the main theme of the text, it needs to be manually overwritten.

The suggested order for falling into the publishing process is as follows: write the main text, generate TDK and candidate tags, automatically generate images or manually select images, supplement image descriptions, and publish after inspection. When the volume is large, assign the first few steps to automatic capabilities, and leave the last two steps for humans. Historical articles imported in bulk should also be supplemented according to this chain, and old articles with missing images should be processed in one go.

Common questions

Could the automatic image generation be completely unrelated to the main text?The relevance depends on the quality of the image library and the title writing. When the title is vague, the matching deviation is greater, and categorizing the image library by theme can significantly reduce deviation.

Can AI painting replace product images?Cannot. AI painting is suitable for illustrations of visual atmosphere, product entities, interface screenshots, and data charts require real sources, the generated images will be distorted in detail.

Can TDK and tags be generated automatically together?Yes, when creating articles, AI can automatically generate tags and TDK candidates, and the editor only needs to change the parts that do not match the text, without having to fill in from scratch.

Do you need to add images to the old articles imported in bulk?It is recommended to fill according to the priority of the column. First fill the text commonly used on the list page and recommended positions, and the rest will be processed in batches according to the number of visits, to avoid making too many changes at once that are difficult to verify.