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Multi-scale histograms for answering queries over time series data.
| Content Provider | CiteSeerX |
|---|---|
| Abstract | Similarity-based time series data retrieval has been used in many real world applications, such as stock data or weather data analysis. Two types of queries on time series data are generally studied: pattern existence queries and exact match queries. In pattern existence queries, users are interested in the general shape of time series data and ignore the specific details. For example, users may want to retrieve all the stock data of last month that have a head and shoulder pattern. As long as the time series data have the specified pattern, they will be retrieved, no matter when the pattern appears and how it appears. For exact match queries, the exact result of a query is defined in terms of specific values. The actual match results are the time series data that are within a specific threshold of the exact result. For example, users may ask for all the stock data of last |
| File Format | |
| Access Restriction | Open |
| Subject Keyword | Weather Data Analysis Stock Data Specific Detail Exact Match Query Actual Match Result Similarity-based Time Series Data Retrieval Pattern Existence Query Specific Value Answering Query Last Month Time Series Data Multi-scale Histogram Many Real World Application Exact Result General Shape Shoulder Pattern Specific Threshold |
| Content Type | Text |
