Contextualizing knowledge panels
The patent describes a system designed by Google that provides users with a “knowledge panel” when they search for entities, like singers, actors, writers, etc. This knowledge panel provides relevant read more
Combining content with a search result
The primary aim of this patent is to enhance user experience by providing more comprehensive and contextually relevant information in search results. By integrating and augmenting search results with related read more
Mapping images to search queries
The patent revolves around a method and system that allows users to input a query in the form of an image. The system then identifies entities associated with the image, read more
Search Result Ranking and Presentation
The patent focuses on advanced methods and systems for ranking search results and generating their presentation. In summary, the patent outlines a sophisticated approach to search result ranking and presentation, read more
Resource scoring adjustment based on entity selections
The Patent addresses the challenges and mechanisms involved in digital information retrieval, particularly in the context of search engines. The ranking process involves scoring resources using factors such as information read more
Natural language processing based search
The provided patent outlines a series of methods, systems, and non-transitory computer-readable media implementations focused on enhancing search functionalities through natural language processing (NLP) and the utilization of knowledge graphs.
Leveraging Semantic and Lexical Matching to Improve the Recall of Document Retrieval Systems: A Hybrid Approach
The paper proposes a hybrid document retrieval approach that combines deep neural network models with traditional lexical models. This approach aims to enhance the initial retrieval stage, which is usually read more
Regression Compatible Listwise Objectives for Calibrated Ranking with Binary Relevance
The document introduces a new approach called Regression Compatible Ranking (RCR) that aims to optimize listwise ranking while maintaining scale-calibrated scores. This method is designed to improve the alignment of read more
End-to-End Query Term Weighting (TW-BERT)
The document discusses a new model called Term Weighting BERT (TW-BERT) aimed at improving the effectiveness of lexical retrieval systems by predicting weights for query terms such as unigrams and read more
Towards Disentangling Relevance and Bias in Unbiased Learning to Rank
The paper is titled “Towards Disentangling Relevance and Bias in Unbiased Learning to Rank” by authors affiliated with various institutions including the University of Illinois and Google Research. The study read more