Update document_scene_information_extraction_en.md

docs/pipeline_usage/tutorials/information_extration_pipelines/document_scene_information_extraction_en.md

@@ -69,7 +69,7 @@ You can [experience online](https://aistudio.baidu.com/community/app/182491/webU
 If you are satisfied with the pipeline's performance, you can directly integrate and deploy it. If not, you can also use your private data to **fine-tune the models in the pipeline online**.
 
 ### 2.2 Local Experience
-Before using the Document Scene Information Extraction v3 pipeline locally, please ensure you have installed the PaddleX wheel package following the [PaddleX Local Installation Guide](https://ku.baidu-int.com/knowledge/HFVrC7hq1Q/pKzJfZczuc/GvMbk70MZz/dF1VvOPZmZXXzn?t=mention&mt=doc&dt=doc).
+Before using the Document Scene Information Extraction v3 pipeline locally, please ensure you have installed the PaddleX wheel package following the [PaddleX Local Installation Guide](../../../installation/installation_en.md).
 
 A few lines of code are all you need to complete the quick inference of the pipeline. Using the [test file](https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/contract.pdf), taking the PP-ChatOCRv3-doc pipeline as an example:
 
@@ -443,8 +443,8 @@ You can analyze images with poor recognition results and follow the guidelines b
 * Misplaced layout elements (e.g., incorrect positioning of tables or seals) may suggest issues with the layout detection module. Consult the **Customization** section in the [Layout Detection Module Development Tutorial](../../../module_usage/tutorials/ocr_modules/layout_detection_en.md) and fine-tune the layout detection model with your private dataset.
 * Frequent undetected text (i.e., text leakage) may indicate limitations in the text detection model. Refer to the **Customization** section in the [Text Detection Module Development Tutorial](../../../module_usage/tutorials/ocr_modules/text_detection_en.md) and fine-tune the text detection model using your private dataset.
 * High text recognition errors (i.e., recognized text content does not match the actual text) suggest that the text recognition model requires improvement. Follow the **Customization** section in the [Text Recognition Module Development Tutorial](../../../module_usage/tutorials/ocr_modules/text_recognition_en.md) to fine-tune the text recognition model.
-* Frequent recognition errors in detected seal text indicate that the seal text detection model needs further refinement. Consult the **Customization** section in the [Seal Text Detection Module Development Tutorials](../../../module_usage/tutorials/ocr_modules/) to fine-tune the seal text detection model.
-* Frequent misidentifications of document or certificate orientations with text regions suggest that the document image orientation classification model requires improvement. Refer to the **Customization** section in the [Document Image Orientation Classification Module Development Tutorial](https://ku.baidu-int.com/knowledge/HFVrC7hq1Q/yKeL8Lljko/y0mmii50BW/J5-rNhRB_xfhDZ?t=mention&mt=doc&dt=doc) to fine-tune the document image orientation classification model.
+* Frequent recognition errors in detected seal text indicate that the seal text detection model needs further refinement. Consult the **Customization** section in the [Seal Text Detection Module Development Tutorials](../../../module_usage/tutorials/ocr_modules/text_detection_en.md) to fine-tune the seal text detection model.
+* Frequent misidentifications of document or certificate orientations with text regions suggest that the document image orientation classification model requires improvement. Refer to the **Customization** section in the [Document Image Orientation Classification Module Development Tutorial](../../../module_usage/tutorials/ocr_modules/doc_img_orientation_classification_en.md) to fine-tune the document image orientation classification model.
 
 ### 4.2 Model Deployment
 After fine-tuning your models using your private dataset, you will obtain local model weights files.