BM25 is a sophisticated ranking function used in information retrieval. Acting like a highly efficient librarian, it excels in navigating through extensive collections of documents. Its effectiveness lies in:
Term Frequency: Evaluating how often search terms appear in each document. Document Length Normalization: Ensuring a fair chance for both short and long documents in search results. Bias-Free Information Retrieval: Ideal for large data sets where unbiased results are critical. About LanceDB (VectorDB) LanceDB extends our search capabilities beyond mere keyword matching. It brings in a layer of contextual understanding, interpreting the semantics of search queries to provide results that align with the intended meaning.
Our hybrid search system synergizes BM25's keyword-focused precision with LanceDB's semantic understanding. This duo delivers nuanced, comprehensive search results, perfect for complex and varied datasets.
BM25's Role: Quick identification of documents based on specific keywords. LanceDB's Magic: Deep semantic analysis to align search results with query intent. Combined Power: Harmonizing both methods for superior search accuracy and relevance.
also we provided Colab walkthrough for Hybrid search
Learn deeper in Our Blog For a deeper dive into the cutting-edge technologies of Hybrid search, and to access detailed technical knowledge, check out our Medium Blog.