pgvector sparse-vector FTS full-text-search similarity-search hybrid-search analytics mpp View more waiting• 0.14.0 • 14 days ago • 1 dependents • MITpublished version 0.14.0, 14 days ago1 dependents licensed under $MIT 146
Sparse Vectors in Qdrant: Pure Vector-based Hybrid Searchhttps://qdrant.tech/articles/sparse-vectors/ BGE(BAAI General Embedding)解读https://zhuanlan.zhihu.com/p/690856333 关注作者 欢迎关注作者微信公众号, 一起交流软件开发:
Sparse Vectors in Qdrant: Pure Vector-based Hybrid Search https://qdrant.tech/articles/sparse-vectors/ BGE(BAAI General Embedding)解读 https://zhuanlan.zhihu.com/p/690856333 本文参与 腾讯云自媒体同步曝光计划,分享自作者个人站点/博客。 原始发表:2024-04-15,如有侵权请联系 cloudcommunity@tencent.com ...
« search_as_you_type(输入即搜索)数据类型Text datatype » 于7.6版本废弃。 sparse_vector类型已废弃,将在8.0中移除。 sparse_vector类型的字段存储浮点值的稀疏向量。 向量中的最大维数不应超过1024。 不同文档的维度的数量可以不同。sparse_vector字段是单值字段。
The AI-native database built for LLM applications, providing incredibly fast hybrid search of dense vector, sparse vector, tensor (multi-vector), and full-text - infiniflow/infinity
We propose a fast Sparse Vector Autoregressive Greedy Search (SVARGS) method that works well for high dimensional data, even when the number of time points is relatively low, by incorporating only statistically significant coefficients. In numerical experiments, our methods show high accuracy in ...
Compared to exhaustive search auto-tuning, our framework can be more than one order of magnitude faster.doi:10.1007/978-3-642-38750-0_12Walid Abu-SufahAsma Abdel-KarimSpringer, Berlin, HeidelbergW. Abu-Sufah and A. Abdel Karim. 2013. Auto-tuning of Sparse Matrix-Vector Multiplication on ...
# Embed the query and generate the corresponding vector representationquery_embeddings = embeddings.embed_documents([query]) # Set the top K result counttop_k = 5 # Get the top 5 docs related to the query # Define the parameters for the dense vector searchsearch_params_dense = { "metric_...
By adding an 1-type penalty to the loss function, common classification methods such as logistic regression or support vector machines (SVM) can perform variable selection. Existing penalized SVM methods all attempt to jointly solve all the parameters involved in the penalization problem altogether. ...
为了解决这个问题,引入一个非零的drop_ratio_search可以显著提高性能,同时只造成极小的精度损失。有关更多信息,请参阅稀疏向量(Sparse Vector)。发布于 2024-09-12 16:10・陕西 开源向量数据库Milvus 赞同1添加评论 分享喜欢收藏申请转载 ...