SemanticSimilarityExampleSelector 只考虑相关性,不考虑多样性: 1. 计算所有示例与输入查询的语义相似度 2. 简单地选择相似度最高的前k个示例 这种方法确保选择的示例与输入查询最相关,但可能会导致选择的示例彼此之间非常相似。 适用场景比较 MaxMarginalRelevanceExampleSelector适用场景: 1. 希望提供多样化的示例以覆...
string>[], embeddings: Embeddings, vectorStoreCls: C, options: { k?: number; inputKeys?: string[]; } & Parameters<C["fromTexts"]>[3] = {} ): Promise<SemanticSimilarityExampleSelector> { const inputKeys = options.input
Using the kernelContextalong with Semantic Kernel’sChatHistoryobject, debugging Semantic Kernel invocations is much easier to do. In the following example response, you can see everything theContextprovides as well as the additional details returned fromChatHistorysuch as tokens used or any prompt sa...
Interpretable Semantic Textual Similarity Using Lexical and Cosine Similarity G Majumder, P Pakray, DEP Avendaño –… of the Computer Society of India, 2018 – Springer… This work is related to the field of NLU, which gives an explanatory layer is important, with applications in dialogue syst...
For example Wang et al. in- troduced a similarity measure combining the structure of the GO graph with the IC values, integrating the con- tribution of all terms in a GO subgraph, including all the ancestors [21]. Comparing genes or gene products Genes are normally annotated using several ...
"similarity":"cosine" } ] }, name="vector_index", type="vectorSearch" ) collection.create_search_index(model=search_index_model) The index definition indexes theembeddingfield as thevectortype. Theembeddingfield contains the embeddings created using OpenAI'stext-embedding-ada-002embedding model. ...
Give an example of Ogilvy’s work <- good answer Ogilvy may also want to reference past customers scenarios to show how they solved problems in the past What was Ogilvy's campaign for Fanta? When was Fanta discovered? Without Semantic search query terms are analyzed via similarity algorithms,...
into classes according to their similarities. Its second role is to return only relevant services to\(S_{R}\)from the registry. This module contains four main components which are: Service Projector, Service Description Extractor, Service Similarity Calculator, and Relevant Service Selector. ...
During supervision, the CE loss calculates the pixel-wise similarity between the prediction map and ground truth (Farabet et al., 2012, Zhang et al., 2019, Borse et al., 2021), and RMI loss measures the similarity of region-wise distribution between the prediction and ground truth, where ...
making use of biomedical domain-specific knowledge bases; AgreementMaker propagates similarity measures determined for ancestors and siblings in the hierarchy; and Silk provides measures of taxonomic distance, as well as a bespoke selector language that allows the description of arbitrary structural relati...