This work was sponsored by enioka.
Given a finite set of objects pool, and an object query. Look, which ever comes first, within approximately t time, or at most n objects subset of pool that are near query according to the metric m, call that subset candidates.
Extra: Add support for continuation. A continuation may produce objects that are more near query than the previous continuation’s candidates.
Transderivational search is a psychological and cybernetics term, meaning when a search is being conducted for a fuzzy match across a broad field. In computing the equivalent function can be performed using content-addressable memory. Unlike usual searches, which look for literal (i.e. exact, logical, or regular expression) matches, a transderivational search is a search for a possible meaning or possible match as part of communication, and without which an incoming communication cannot be made any sense of whatsoever. It is thus an integral part of processing language, and of attaching meaning to communication.
In computer science, beam search is a heuristic search algorithm that explores a graph by expanding the most promising node in a limited set. Beam search is an optimization of best-first search that reduces its memory requirements. Best-first search is a graph search which orders all partial solutions (states) according to some heuristic. But in beam search, only a predetermined number of best partial solutions are kept as candidates. It is thus a greedy algorithm.
Follow up the exact brute force appraoch
