Temporal data are ubiquitous nowadays and efficient management of temporal data is of
key importance. A temporal data typically describes the evolution of an object over time. One …

This paper studies the problem of finding objects with durable quality over time in historical
time series databases. For example, a sociologist may be interested in the top 10 web …

Many datasets have a temporal dimension and contain a wealth of historical information.
When using such data to make decisions, we often want to examine not only the current …

Temporal data is ubiquitous in our everyday life, but tends to be noisy and often exhibits
transient patterns. To make better decisions with data, we must avoid jumping to conclusions …

A way of finding interesting or exceptional records from instant-stamped temporal data is to
consider their" durability," or, intuitively speaking, how well they compare with other records …

This paper studies efficient processing of durable top-k queries on historical time series
databases. Durable top-k queries, obtained as an extension of snapshot top-k queries …

Top-k queries have been well-studied in snapshot databases and data streams. We observe
that decision-makers are often interested in a set of objects that exhibit a certain degree of …

We study a particular kind of join, coined Ranked Temporal Join (RTJ), featuring predicates
that compare time intervals and a scoring function associated with each predicate to quantify …

With advancements in Internet of Things (IoT) and performance monitoring, time-series
database have garnered significant attention. Time-series consists of two components …

With the massive amount of data generated, a data engineering method is needed to
process the data to obtain new information, which can later be used for further …