We review the major paradigms for approximate similarity queries and propose a
classification schema that easily allows existing approaches to be compared along several …

Similarity search in high-dimensional metric spaces is a key operation in many applications,
such as multimedia databases, image retrieval, object recognition, and others. The high …

This work is about speeding up retrieval in Case-Based Reasoning (CBR) for large-scale
case bases (CBs) comprised of temporally related cases in metric spaces. A typical example …

Web search engines incorporate results from structured data sources to answer semantically
rich user queries, ie Samsung 50 inch led tv can be answered from a table of television data …

This paper presents the Cascaded Metric Tree (CMT) for efficient satisfaction of metric
search queries over a dataset of N objects. It provides extra information that permits query …

Objectives: To propose a method to handle large number of user and to improve the
accuracy and quality of recommendation system. Methods/Statistical Analysis: This paper …

Electrical power demand is increasing cumulatively with the increase in population.
Economic and environmental impacts restrict the expansion of conventional generation but …

The k-Nearest Neighbor Classifier (k-NN) is a widely used classification technique used in
data streams. However, traditional k-NN-based stream classification algorithms can't handle …

L'enfocament de la metodologia Casi-Based Reasoning (CBR) per a la resolució de
problemes que" problemes similars tenen solucions similars" ha demostrat ser bastant …

Efficient time series similarity search is a fundamental operation for data exploration and
analysis. While previous work has focused on indexing progressively larger datasets and …