Identify search result relevance
using AI
Below is a free classifier to identify search result relevance. Just input your text, and our AI will predict the relevance of each search result category. - in just seconds.
API Access
import nyckel
credentials = nyckel.Credentials("YOUR_CLIENT_ID", "YOUR_CLIENT_SECRET")
nyckel.invoke("search-result-relevance", "your_text_here", credentials)
fetch('https://www.nyckel.com/v1/functions/search-result-relevance/invoke', {
method: 'POST',
headers: {
'Authorization': 'Bearer ' + 'YOUR_BEARER_TOKEN',
'Content-Type': 'application/json',
},
body: JSON.stringify(
{"data": "your_text_here"}
)
})
.then(response => response.json())
.then(data => console.log(data));
curl -X POST \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_BEARER_TOKEN" \
-d '{"data": "your_text_here"}' \
https://www.nyckel.com/v1/functions/search-result-relevance/invoke
How this classifier works
To start, input the text that you'd like analyzed. Our AI tool will then predict the relevance of each search result category..
This pretrained text model uses a Nyckel-created dataset and has 5 labels, including Highly Relevant, Irrelevant, Marginally Relevant, Relevant and Somewhat Relevant.
We'll also show a confidence score (the higher the number, the more confident the AI model is around the relevance of each search result category.).
Whether you're just curious or building search result relevance detection into your application, we hope our classifier proves helpful.
Recommended Classifiers
Need to identify search result relevance at scale?
Get API or Zapier access to this classifier for free. It's perfect for:
- Improved E-commerce Search: This function can enhance search result relevance in online retail platforms by filtering out irrelevant products. By classifying search inputs, the system can better match user queries with items, leading to higher conversion rates and customer satisfaction.
- Content Curation for News Aggregators: News aggregation services can implement this classification function to present users with the most relevant articles based on their interests. By accurately identifying irrelevant content, the platform can improve user engagement and retention.
- Enhanced Customer Support: Customer service platforms can use this function to classify inquiries and route them to the appropriate department or representative. By ensuring that only relevant queries are handled, the system can improve response times and overall customer experience.
- Targeted Marketing Campaigns: Marketing automation tools can leverage this functionality to filter potential leads based on relevant criteria. By ensuring that only suitable prospects receive targeted campaigns, businesses can increase their marketing effectiveness and ROI.
- Semantic Search in Knowledge Bases: Knowledge management systems can utilize this classifier to enhance the relevance of search results within large databases. By accurately identifying pertinent documents, users can find the information they need more quickly and efficiently.
- Video Recommendations in Streaming Services: Streaming platforms can employ this function to refine content recommendations based on user viewing habits. By filtering out irrelevant options, users are more likely to discover content that aligns with their preferences, enhancing user satisfaction.
- Academic Research Assistance: Research databases and libraries can apply this function to assist users in finding relevant scholarly articles. By improving the relevance of search results, researchers can save time and access pertinent information that directly relates to their work.