Temporal information retrieval using bitwise operators

The plethora of available and stored temporal data necessitated the development of effective algorithms for information retrieval. The previous research on temporal information retrieval predominantly focused on the correctness of the retrieval results and supported wider types of temporal operators for retrieval. Many of these algorithmic approaches are based on high-level data structures and libraries supported by high-level programming languages, thus limiting the running time performance of these approaches. In this paper, we develop querying and information retrieval for temporal queries based on Allen’s interval algebra that provides a calculus for temporal reasoning by defining thirteen basic relations between two intervals. To increase the retrieval performance, we propose using bitmaps and bitwise operations to identify all of Allen’s thirteen relations between any two events across the entirety of the data where events are represented as bitmaps. The indexes in the bitmap represent various time instances in the data, and the values 1 and 0 correspond to the presence and absence of an event. Using bitwise operators such as AND, OR, and bit-shifts, in our compressed representation of the events, we establish expressions for each of Allen’s relations. Our experiments show that, for two events with roughly \(5 \times 10^6\) intervals in each, the bitwise operation-based methods are almost 42 times faster than conventional interval-based linear lookups and almost 21 times faster than conventional pattern-finding parallel techniques inherently available.