Position Calculating Method, Distance Calculating Method, and Beacon

    公开(公告)号:US20190208492A1

    公开(公告)日:2019-07-04

    申请号:US16331598

    申请日:2017-09-25

    IPC分类号: H04W64/00 H04B17/318 G01S5/02

    摘要: In a position calculating method performed by a system including beacons, and a control device capable of communicating with the beacons: at least one of the plurality of beacons receives, from a terminal present in the radio wave reaching distance of the beacon, a first signal including terminal identification information identifying the terminal, measures the reception strength of the received signal, and transmits a second signal which includes the terminal identification information, the reception strength and beacon identification information identifying the beacon; and the control device receives the second signal from one of the plurality of beacons, and, on the basis of the position information of the beacon corresponding to the beacon identification information included in the second signal, and on the basis of the reception strength included in the second signal, calculates the position of the terminal corresponding to the terminal identification information included in the second signal.

    PREDICTOR INTERACTIVE LEARNING SYSTEM, PREDICTOR INTERACTIVE LEARNING METHOD, AND PROGRAM

    公开(公告)号:US20230004838A1

    公开(公告)日:2023-01-05

    申请号:US17781987

    申请日:2021-01-05

    IPC分类号: G06N5/04 G06F40/279 G06N20/00

    摘要: A predictor interactive learning system of the present invention includes machine learning unit configured to perform machine learning of a predictor that outputs a predicted value indicating a likelihood of being a predetermined intrinsic expression, by using teacher data and teacher labels, an interest score calculation unit configured tip obtain an interest score according to statistical data of a corresponding word in a corpus including the predicted value of the predictor for each of words of the corpus, an interactive learning frame unit configured to extract the word serving as the teacher data used in next learning of the predictor according to the interest score, and a question-response unit configured to output a question of whether the extracted teacher data is an intrinsic expression of which the likelihood is predicted by the predictor, and to acquire a teacher label corresponding to the teacher data, as a response to the question, in which the machine learning unit performs machine learning of the predictor using teacher data extracted by a teacher word extraction unit and a teacher label acquired by an interaction unit.