What is TILDEv2?
Have you ever searched something on Google and not found what you were looking for? TILDEv2 is a new method that improves the way search results are ranked, making it easier for people to find the information they need. TILDEv2 is a re-ranking method that improves on TILDE, which had limitations. It uses a technique called contextualized exact term matching with expanded passages to improve search results.
How does TILDEv2 Work?
TILDEv2 is based on an algorithm called BERT. BERT is a powerful algorithm that can understand the context of words in a sentence. TILDEv2 uses BERT to match search queries to relevant passages. TILDEv2 then expands the passages containing the relevant information to improve the accuracy of the search results. This technique means that TILDEv2 only needs to store the score of tokens that appear in the expanded passages, making it more efficient than other search algorithms.
Limitations of TILDE:
TILDE was the original algorithm that TILDEv2 is based on. TILDE relied on query likelihood matching, which expands passages into the BERT vocabulary size. This resulted in large indexes that made search results slower to process. TILDEv2 overcomes this issue by using contextualized exact term matching, which indexes only tokens present in the passage, reducing the index size by 99%.
Improvements of TILDEv2 over TILDE:
TILDEv2 uses contextualized exact term matching and noise contrastive estimation (NCE) loss functions to improve the quality of search results. NCE loss functions help better leverage negative training samples, improving the accuracy of TILDEv2. In addition to this, TILDEv2 uses deep language models to expand passages in the collection, meaning that it only needs to index a few extra tokens in addition to the original passages, improving efficiency.
Advantages of TILDEv2:
TILDEv2 has several benefits over traditional search algorithms:
- Improved accuracy: TILDEv2 is more accurate at matching search queries to relevant passages, resulting in better search results.
- Efficiency: TILDEv2 only needs to store the score of tokens that appear in the expanded passages, making it more efficient than other search algorithms.
- Contextualized matching: TILDEv2 uses BERT to understand the context of words, improving the quality of search results.
- Noise contrastive estimation loss functions: TILDEv2 uses NCE loss functions to better leverage negative training samples, improving the accuracy of the algorithm.
Conclusion:
TILDEv2 is a powerful new search algorithm that improves on previous search methods by using contextualized exact term matching with expanded passages. This technique improves the accuracy and efficiency of search results, making it easier for people to find the information they need. By only storing the score of tokens that appear in the expanded passages, TILDEv2 is more efficient than other search algorithms. With its improved accuracy and efficiency, TILDEv2 is set to revolutionize the search industry, making it easier for people to find what they are looking for online.
