like location and past searches. Similar to the idea behind semantic searches, contextual searches focus on understanding the meaning and intent behind a user's query. Where semantic search uses NLP and machine learning to understand user intent, contextual search uses different available...
A method for semantic and contextual searching over a knowledge repository. The method includes creating a search query for each concept related to the target concept to form a search context, wherein
Semantic diversity refers to the diversity of contexts in which a word is used (e.g., chamber orchestra vs. judge's chamber). Semantic context search involves searching semantic memory for different contextual usages of a prompt word. Supporting the facilitative role of semantic context search, ...
The strength of semantic search lies in contextual comprehension. It usesNLPto identify the main intent of a query, then searches for documents that align with that intent. If you ask, “How do I fix a leaking faucet?” semantic search pinpoints “leaking faucet” as the core problem, rathe...
Semantic search is a data searching technique in a which a search query aims to not only find keywords, but to determine the intent and contextual meaning of the the words a person is using for search. Advertisements Semantic search provides more meaningful search results by evaluating and un...
We trace the history of semantic search and share some thoughts on its future — a combination of keyword and vector-based search.
Search engines are crazy about semantic search which helps them to process natural language and understand query's search intent to provide relevant, personalized results. Read on our guide to learn about 4 efficient ways of semantic search optimization.
We developed a technical workflow that integrates a vector database, Sentence Transformers, a Gaussian Mixture Model (GMM), Retrieval Agent, and Large Language Models (LLMs) to enable contextual search, topic ranking, and characterization of research using customized prompt templates. A pilot study ...
However, on the contextual search side, performance slows down significantly with an individual search from a Large (1mn) index taking up to 8sec. This seems definitely a significant slowdown compared to say the midsized index of 100k taking up still significantly less than 1sec ...
Hybrid search performs two parallel searches on a vector database. The union of the results of these two searches are then returned to callers with a combined rank, based on the rankings from each of the constituent sear... Semantic Kernel.NET Apr 9, 2025 Post comments count0 Post ...