CONSOLIDATING PERSONAL BILL
    23.
    发明申请

    公开(公告)号:US20220027876A1

    公开(公告)日:2022-01-27

    申请号:US16939695

    申请日:2020-07-27

    Abstract: Aspects of the present invention disclose a method for consolidating of a plurality of personal bills from diverse financial sources to reflect the payments, expenses, and balances without duplication. The method includes one or more processors parsing a plurality of bills of a user, the plurality of bills including bills with varying formats. The method further includes identifying a set of bills of the plurality of bills of the user, the set of bills including related bills based at least in part on a prebuilt rule. The method further includes determining a correlation of one or more items of respective bills of the set of bills of the user based at least in part on a machine learning algorithm. The method further includes generating a consolidated bill, from the set of bills of the user, based at least in part on the determined correlation of the one or more items.

    DYNAMICALLY OPTIMIZED INQUIRY PROCESS FOR INTELLIGENT HEALTH PRE-DIAGNOSIS

    公开(公告)号:US20200152338A1

    公开(公告)日:2020-05-14

    申请号:US16190691

    申请日:2018-11-14

    Abstract: A system is provided for facilitating medical conversation. The system includes a user interface, having a Natural Language Processing (NLP) system and an Automatic Speech Recognition (ASR) system, for processing user utterances to extract symptoms, attribute types and attribute values from a user. The system further includes a memory for storing program code. The system also includes a processor for running the program code to transform the symptoms, the attribute types, and the attribute values into a graph and extract relative entities and relationships of the relative entities from the graph. The processor further runs the program code to calculate an Inquiry Efficiency Index (IEI) of each candidate inquiry path based on the relative entities and the relationships of the relative entities. The processor additionally runs the program code to calculate a recommended inquiry path from among the candidate inquiry paths based on the IEI of each candidate inquiry path.

    Facilitation of automatic adjustment of a braking system

    公开(公告)号:US10328913B2

    公开(公告)日:2019-06-25

    申请号:US15355724

    申请日:2016-11-18

    Abstract: Systems and methods for facilitating an automatic adjustment of a braking system is provided. In one example, a computer-implemented method can comprise generating, by a system operatively coupled to a processor, a braking curve model based on braking usage pattern data corresponding to one or more vehicles. The computer-implemented method can also comprise adjusting, by the system, a supplemental braking component of the first vehicle based on a simulation of one or more braking components corresponding to the one or more vehicles, wherein the one or more braking components is represented by the braking curve model.

    Conversational Problem Determination based on Bipartite Graph

    公开(公告)号:US20190188067A1

    公开(公告)日:2019-06-20

    申请号:US15844434

    申请日:2017-12-15

    CPC classification number: G06F11/079 G06F11/0709 G06F11/0751 G06F11/0775

    Abstract: A cognitive conversation system that generates effective diagnostic questions is provided. The cognitive conversation system receives a set of currently known symptoms (or currently available answers to diagnostic questions) of a reported problem or fault. The system identifies (i) a set of possible root causes of the reported problem based on the currently known symptoms and (ii) probabilities for the set of possible root causes by using a bipartite graph data structure that links possible symptoms with possible root causes. Upon determining that at least one possible root cause has a probability that is higher than a threshold, the system presents an explanation or solution associated with the at least one possible root cause. Upon determining that none of the possible root causes in the set of possible root causes has a probability higher than the threshold, the system presents a question based on information entropy that is computed based on probabilities of the identified possible root causes.

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