Time series is an important class of temporal data objects and it can be easily obtained from
scientific and financial applications. A time series is a collection of observations made …

Protecting rights over relational data is of ever increasing interest, especially considering
areas where sensitive, valuable content is to be outsourced. A good example is a data …

A novel metric for time series, called Move-Split-Merge (MSM), is proposed. This metric uses
as building blocks three fundamental operations: Move, Split, and Merge, which can be …

Time-series data naturally arise in countless domains, such as meteorology, astrophysics,
geology, multimedia, and economics. Similarity search is very popular, and DTW (Dynamic …

A Query by Humming system allows the user to find a song by humming part of the tune. No
musical training is needed. Previous query by humming systems have not provided …

Monitoring predefined patterns in streaming time series is useful to applications such as
trend-related analysis, sensor networks and video surveillance. Most current studies on such …

To effectively maintain and analyze a large amount of real-time sensor data, one often uses
a filtering technique that reflects characteristics of original data well. This paper proposes a …

In this paper, we describe an efficient indexing method for a shape-based similarity search
of the trajectory of dynamically changing locations of people and mobile objects. In order to …

Subsequence similarity matching in time series databases is an important research area for
many applications. This paper presents a new approximate approach for automatic online …

Time-series data—data arriving in time order, or a data stream—can be found in fields such
as physics, finance, music, networking, and medical instrumentation. Designing fast …