Table of contents
Advanced Natural Language Understanding
ZIR Semantic Search leverages sophisticated AI models to comprehend and interpret complex queries, offering more accurate and relevant search results as opposed to traditional keyword-based methods.
Contextual Relevance
The platform is designed to understand the context behind user queries, ensuring that search results align closely with user intent, leading to improved user satisfaction.
Improved Search Efficiency
By understanding the semantic meaning behind queries, ZIR can deliver precise results quickly, reducing the time users spend on searching for information.
Scalability
ZIR Semantic Search is built to scale with growing data volumes and demand, making it suitable for businesses of varying sizes and data requirements.
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Check the traffic stats of ZIR Semantic Search on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
Check the "Domain Rating" of ZIR Semantic Search on Ahrefs. The domain rating is a measure of the strength of a website's backlink profile on a scale from 0 to 100. It shows the strength of ZIR Semantic Search's backlink profile compared to the other websites. In most cases a domain rating of 60+ is considered good and 70+ is considered very good.
Check the "Domain Authority" of ZIR Semantic Search on MOZ. A website's domain authority (DA) is a search engine ranking score that predicts how well a website will rank on search engine result pages (SERPs). It is based on a 100-point logarithmic scale, with higher scores corresponding to a greater likelihood of ranking. This is another useful metric to check if a website is good.
The latest comments about ZIR Semantic Search on Reddit. This can help you find out how popualr the product is and what people think about it.
Hi Dmitry, I am cofounder of ZIR AI (https://zir-ai.com/). I researched neural information retrieval at Google, before starting ZIR in 2020. (Note: Vespa, who appear in your article, reference some of my work in [1]) To give you some historical perspective, embedding based retrieval on large text corpora became viable only after the introduction of transformers in 2017. Google Talk to Books... - Source: Hacker News / over 3 years ago
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