[Feature] - Ranking
Description
In today's digital landscape, users are constantly seeking relevant and high-quality content to satisfy their information needs. However, without a ranking system, search results can be overwhelming and time-consuming to navigate. To address this challenge, we propose the implementation of a ranking component that scores audio/video files based on their relevance to user queries using tags, summaries, and metadata. This innovative feature will significantly improve content discovery by ordering results according to their match quality, ensuring that users can quickly find the most relevant content.
Motivation
The need for a ranking system is driven by the user's desire to see the most relevant content first when searching. Without ranking, search results are not prioritized, making it harder for users to find useful content quickly. This can lead to frustration, decreased user engagement, and ultimately, a negative impact on the overall user experience. By implementing a ranking component, we can provide users with a more efficient and effective way to discover relevant content, thereby enhancing their overall experience.
Proposed Solution
To address the need for a ranking system, we propose the addition of a client-side scoring algorithm that ranks search results based on keyword overlap between the user query and file tags, title, and summary. This algorithm will assign a score to each search result based on the relevance of its metadata to the user's query. The score weightings can be adjusted to prioritize certain fields, such as tags over summary or title. For instance, if a user searches for a specific keyword, the algorithm can prioritize files with matching tags over those with matching summaries or titles. This flexibility in scoring allows us to tailor the ranking system to specific use cases and user preferences.
Acceptance Criteria
To ensure the success of this feature, we have established the following acceptance criteria:
- Feature is clearly defined: The ranking component is well-defined, and its purpose is clearly understood.
- Meets proposed solution: The implemented solution meets the proposed requirements, including the client-side scoring algorithm and adjustable score weightings.
- Tests considered: Thorough testing has been conducted to ensure the ranking component functions as intended and provides accurate results.
Additional Info
To further enhance the ranking system, we propose exposing scoring factors as constants or settings to allow easy tuning. This will enable developers to adjust the scoring algorithm to suit specific use cases or user preferences without requiring significant changes to the underlying code. Additionally, this feature can be extended later with AI relevance scoring, which will further improve the accuracy and effectiveness of the ranking system.
Implementation Details
To implement the ranking component, we will follow these steps:
- Design the scoring algorithm: We will design a client-side scoring algorithm that ranks search results based on keyword overlap between the user query and file tags, title, and summary.
- Implement the algorithm: We will implement the scoring algorithm using a programming language such as JavaScript or Python, depending on the chosen framework or library.
- Adjust score weightings: We will adjust the score weightings to prioritize certain fields, such as tags over summary or title.
- Test the implementation: We will thoroughly test the ranking component to ensure it functions as intended and provides accurate results.
- Expose scoring factors: We will expose scoring factors as constants or settings to allow easy tuning and adjustment of the scoring algorithm.
Benefits and Advantages
The ranking component will provide several benefits and advantages, including:
- Improved content discovery: The ranking system will enable users to quickly find relevant content, improving their overall experience and engagement.
- Increased user satisfaction: By providing users with the most relevant content first, we can increase user satisfaction and reduce frustration.
- Enhanced user experience: The ranking component will enhance the overall user experience by providing a more efficient and effective way to discover relevant content.
- Flexibility and customization: The adjustable score weightings will allow developers to tailor the ranking system to specific use cases and user preferences.
Conclusion
Frequently Asked Questions
We've compiled a list of frequently asked questions to provide further clarification on the ranking component and its implementation.
Q: What is the purpose of the ranking component?
A: The purpose of the ranking component is to improve content discovery by ordering search results according to their match quality. This will enable users to quickly find relevant content, improving their overall experience and engagement.
Q: How does the ranking component work?
A: The ranking component uses a client-side scoring algorithm that ranks search results based on keyword overlap between the user query and file tags, title, and summary. The score weightings can be adjusted to prioritize certain fields, such as tags over summary or title.
Q: What are the benefits of the ranking component?
A: The ranking component provides several benefits, including improved content discovery, increased user satisfaction, enhanced user experience, and flexibility and customization options.
Q: How can the scoring algorithm be adjusted?
A: The scoring algorithm can be adjusted by changing the score weightings to prioritize certain fields, such as tags over summary or title. This can be done by exposing scoring factors as constants or settings to allow easy tuning.
Q: Can the ranking component be extended with AI relevance scoring?
A: Yes, the ranking component can be extended with AI relevance scoring in the future. This will further improve the accuracy and effectiveness of the ranking system.
Q: How will the ranking component be tested?
A: The ranking component will be thoroughly tested to ensure it functions as intended and provides accurate results. This will include testing the scoring algorithm, adjusting score weightings, and exposing scoring factors.
Q: What are the acceptance criteria for the ranking component?
A: The acceptance criteria for the ranking component include:
- Feature is clearly defined: The ranking component is well-defined, and its purpose is clearly understood.
- Meets proposed solution: The implemented solution meets the proposed requirements, including the client-side scoring algorithm and adjustable score weightings.
- Tests considered: Thorough testing has been conducted to ensure the ranking component functions as intended and provides accurate results.
Q: How will the ranking component be implemented?
A: The ranking component will be implemented by following these steps:
- Design the scoring algorithm: We will design a client-side scoring algorithm that ranks search results based on keyword overlap between the user query and file tags, title, and summary.
- Implement the algorithm: We will implement the scoring algorithm using a programming language such as JavaScript or Python, depending on the chosen framework or library.
- Adjust score weightings: We will adjust the score weightings to prioritize certain fields, such as tags over summary or title.
- Test the implementation: We will thoroughly test the ranking component to ensure it functions as intended and provides accurate results.
- Expose scoring factors: We will expose scoring factors as constants or settings to allow easy tuning and adjustment of the scoring algorithm.
Q: What are the next steps for the ranking component?
A: The next steps for the ranking component include:
- Implementation: We will implement the ranking component by following the steps outlined above.
- Testing: We will thoroughly test the ranking component to ensure it functions as intended and provides accurate results.
- Deployment: We will deploy the ranking component to ensure it is available to users.
- Maintenance: We will maintain the ranking component to ensure it continues to function as intended and provides accurate results.
Conclusion
The ranking component is a crucial feature that will significantly improve content discovery by ordering results according to their match quality. By implementing a client-side scoring algorithm that ranks search results based on keyword overlap between the user query and file tags, title, and summary, we can provide users with a more efficient and effective way to discover relevant content. With its flexibility and customization options, the ranking component will enhance the overall user experience and provide a competitive edge in the digital landscape.