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SEOTraffic

Extract Info From 3 URLs

Extract knowledge about 1 - 4 keywords based on the knowledge of 3 URL

SEOTraffic automates content & repetitive SEO tasks.
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Prompt: <<Step1>> {{url}} <<Step2>> {{url}} <<Step3>> {{url}} <<Step4>> Given the following keywords: "{{Enter keyword or a group of a few keywords}}" Extract the parts from the received parts which are relevant to the keywords and summarise them in {{How many sentences do you need}} sentences.


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SEOTraffic.ai
Last update:
June 22, 2023



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Reflexion With Self-Improvement :
Take a given text; Let ChatGPT
criticize the text using a
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again and again (while scoring it
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TAB Reflexion With Self-Improvement
<<Step1>> Context = Extract the 9 main topics and keywords as a comma separated list from {{tab}} <<Step2>> I want you to act as an expert chatbot called "BeBetter", which is based on the GPT-4 model and designed to self-reflect on the SUBJECT and improve its responses. BeBetter is an expert in these fields: 1. Machine Learning 2. Natural Language Processing 3. Artificial Intelligence 4. Computer Vision 5. Robotics 6. Neural Networks 7. Data Science 8. Deep Learning 9. Data Mining 10. Algorithm Design 11. Cloud Computing 12. Web Development 13. Mobile App Development 15. Cyber Security 16. Blockchain 17. Augmented Reality 18. Virtual Reality 19. User Interface Design 20. Game Development BeBetter has the following built-in process: 1. You provide the initial response with an assumed score of 1. 2. BeBetter will critically analyze the response and explain why the response could be better. 3. BeBetter will rewrite the response to address the criticisms and improve the score. 4. BeBetter will continue iterating through steps 2-3, with each iteration improving the score by 1 or 2 points, until the score reaches 10 or a minimum of 5 iterations have been completed. 5. If BeBetter feels the final iteration could still be improved upon, regardless of the score, it will acknowledge the need for further work. Here is a layout example for each iteration: Iteration: # SUBJECT: text Score: value Criticisms: text Here is the initial response (Iteration 1) with an assumed score of 1, and BetterGPT will begin the self-improvement loop by generating its own criticism and subsequent iterations: SUBJECT = "{{Enter a text that you want ChatGPT to iteratively improve}}"
Create a taxonomy for a topic
based on query data from GSC
Taxonomy Creator
As an expert in taxonomy creation, we need your assistance in developing a clear, high-level website taxonomy based on a provided list of topics. These topics represent diverse categories that need to be neatly organized in a hierarchical manner. Subject of website: {{subject}} Important Topics: {{GSC query data}} The topics are a list of topic ngrams and their scores. The scores are based on the number of times the query appears in the dataset and the overall user interest in the topic. Generally, higher scoring queries are more important to include as top-level categories. Please adhere to the following dash-prefix format for your output. The taxonomy should be structured, as an example, as follows: - Category - Subcategory - Sub-subcategory - Subcategory - Category - Subcategory - Sub-subcategory - Sub-sub-subcategory - Sub-subcategory In order to effectively accomplish this task, you MUST follow the following guidelines: Brands: The Important Topics may mention these specific brands '{{brands}}'. When creating your taxonomy, please omit these brand terms. For example, if a topic is 'adidas shoes' and 'adidas' is in the specified brands, the taxonomy should include 'shoes' but not 'adidas'. No Guessing: AVOID inventing or speculating any subcategory subjects that are not directly reflected in the provided Important Topics. Miscellaneous: Some Important Topics are outliers, are too vague, or are not relevant to the products and services offered by the company. Assign these topics to a top-level category called 'Miscellaneous' e.g. Miscellaneous > Dogs (where all topics are related to shoes). Depth of Taxonomy: The taxonomy should be no more than four levels deep (i.e., Category > Subcategory > Sub-subcategory > Sub-sub-subcategory). Accuracy: Consider carefully the top-level categories to ensure that they are broad enough to effectively hold key sub-category subjects. Readability: Ensure that category names are concise yet descriptive. Duplication: Try not to assign a subject to multiple categories unless the provided Important Topics indicate it belongs in both. Output: Only output the taxonomy. DO NOT include commentary. Please read the guidelines and examples closely prior to beginning and double-check your work before submitting. Start!

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