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Word2vec is a group of related models that are used to produce word embeddings.These models are shallow, two-layer neural networks that are trained to reconstruct linguistic contexts of words.
Record linkage (also known as data matching, data linkage, entity resolution, and many other terms) is the task of finding records in a data set that refer to the same entity across different data sources (e.g., data files, books, websites, and databases).
Database name Language implemented in Notes Apache Doris Java & C++ Open source (since 2017), database for high-concurrency point queries and high-throughput analysis. Apache Druid: Java Started in 2011 for low-latency massive ingestion and queries. Support and extensions available from Imply Data. Apache Kudu: C++
MapReduce is a programming model and an associated implementation for processing and generating big data sets with a parallel and distributed algorithm on a cluster. [1] [2] [3]A MapReduce program is composed of a map procedure, which performs filtering and sorting (such as sorting students by first name into queues, one queue for each name), and a reduce method, which performs a summary ...
A vector database, vector store or vector search engine is a database that can store vectors (fixed-length lists of numbers) along with other data items. Vector databases typically implement one or more Approximate Nearest Neighbor algorithms, [1] [2] [3] so that one can search the database with a query vector to retrieve the closest matching database records.
Names such as LAST_UPDATE, LAST_MODIFIED, etc. are common. Any row in any table that has a timestamp in that column that is more recent than the last time data was captured is considered to have changed. Timestamps on rows are also frequently used for opened locking so this column is often available.
To get a similar behavior, toSorted may be used. But in this particular case, sort operates on the new array returned from filter and therefore does not change the original array. See also
The average silhouette of the data is another useful criterion for assessing the natural number of clusters. The silhouette of a data instance is a measure of how closely it is matched to data within its cluster and how loosely it is matched to data of the neighboring cluster, i.e., the cluster whose average distance from the datum is lowest. [8]