Andere Kunden interessierten sich auch für
![Clustering. Die Clusteranalysen K-means und DBSCAN im Vergleich]( "Clustering. Die Clusteranalysen K-means und DBSCAN im Vergleich")
Clustering. Die Clusteranalysen K-means und DBSCAN im Vergleich17,95 €![Optimizing Binary Trees Grown With a Sorting Algorithm]( "Optimizing Binary Trees Grown With a Sorting Algorithm")
Optimizing Binary Trees Grown With a Sorting Algorithm32,99 €![Parallelization in Traditional Clustering Algorithms]( "Parallelization in Traditional Clustering Algorithms")
Parallelization in Traditional Clustering Algorithms26,99 €![Künstliche Intelligenz in den Ingenieurwissenschaften]( "Künstliche Intelligenz in den Ingenieurwissenschaften")
Künstliche Intelligenz in den Ingenieurwissenschaften44,99 €![La parallélisation dans les algorithmes de clustering traditionnels]( "La parallélisation dans les algorithmes de clustering traditionnels")
La parallélisation dans les algorithmes de clustering traditionnels26,99 €![Minería de Datos Distribuida usando Clustering k-means]( "Minería de Datos Distribuida usando Clustering k-means")
Minería de Datos Distribuida usando Clustering k-means32,99 €![Core Data Analysis: Summarization, Correlation, and Visualization]( "Core Data Analysis: Summarization, Correlation, and Visualization")
Core Data Analysis: Summarization, Correlation, and Visualization48,99 €
Academic Paper from the year 2020 in the subject Computer Science - Technical Computer Science, grade: 9.5, , language: English, abstract: This paper deals with a way to optimize the search results for image searches by proposing a K-means clustering algorithm. The proposed framework attempts to optimize image search results by adopting a vectorization method which involves textual features extraction and then applying a K-means clustering algorithm to group similar images into a cluster. Hence, the aim is to develop a method that can handle a query term in a reasonably short time and return the results with higher accuracy.With each passing day, the amount of visual information on the internet, such as videos and images, is growing rapidly at an alarming rate, thereby making it difficult for a user to search for the necessary content. Users need to spend vast amounts of time in shifting through an extensive list of search results until they can find the required relevant information. To resolve this problem and to provide better image retrieval results to a user, a clustering framework is suggested in this paper.Cluster Analysis or Clustering is a concept which defines the discipline of grouping similar objects or data items into clusters. A cluster is said to be a collection of data objects. These formed clusters of similar data items differ in characteristics and features. Hence, Clustering can be defined as a solution for classifying web search results effectively for searching data items. Clustering allows users to identify their required group at a glance by looking at the cluster labels. Hence, it saves time while searching on the internet.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.