Similarity-based queries for time series data

On Similarity-Based Queries for Time Series Data

We study similarity queries for time series data where similarity is defined in terms of a set of linear transformations on the Fourier series representation of a sequence. We have shown in an earlier work that this set of transformations is rich enough to formulate operations such as moving average and time scaling. In this paper, we present a new algorithm for processing queries that define s...

Similarity Search on Time Series Based on Threshold Queries

Similarity search in time series data is required in many application fields. The most prominent work has focused on similarity search considering either complete time series or similarity according to subsequences of time series. For many domains like financial analysis, medicine, environmental meteorology, or environmental observation, the detection of temporal dependencies between different ...

Spatial Cone Tree: An Index Structure for Correlation-based Similarity Queries on Spatial Time Series Data

Time-Series Similarity Queries Employing a Feature-Based Approach

1. SUMMARY Time-series, or time-sequence, data show the value of a parameter over time. A common query with time-series data is to find all sequences which are similar to a given sequence. The most common technique for evaluating similarity between two sequences involves calculating the Euclidean distance between them. However, many examples can be given where two similar sequences are separate...

Similarity Range Queries in Streaming Time Series

Similarity search in time series databases is an important research direction. Several methods have been proposed in order to provide algorithms for efficient query processing in the case of static time series of fixed length. In streaming time series the similarity problem is more complex, since the dynamic nature of streaming data make these methods inappropriate. In this paper, we propose a ...