The best uses of deep learning for search relevance ranking is in Ecommerce field where it helps machines or computer systems to show the most relevant results while searching a product through online mode. Another best uses of deep learning for search relevance ranking for image searching are in the visual search technology. Search engines like Google uses the best search relevance metrics to give the most suitable results for searchers.
Actually, deep learning is part of machine learning methods based on learning data representations. And using the deep neural networks, computer vision and natural language processing, it helps to search the web, or a product catalog, or answer selection for a bot to assist a customer representative, or finding the answer to your search query, or finding a resume matching particular skills, and so on as per the different fields search algorithms.
Ecommerce or online shopping websites are benefiting most from the search relevance algorithms that obviously works on machine learning or deep structured learning process. Deep neural networks used in deep learning helps by automatically tweaking the end user query under the hood based on past user queries or based on the search engine contents.
Whatever the process of how deep learning or how it is used in search relevance doesn’t matters, instead the quality and amount of training data used to develop search relevance metrics to give the most suitable or relevant results to users is more important . The higher the quality of data sets the results would be better and deep learning helps to learn the search engine how to users find the results useful and in future improve their results accordingly.