DYNAMIC FIELD VALUE RECOMMENDATION METHODS AND SYSTEMS

    公开(公告)号:US20210149933A1

    公开(公告)日:2021-05-20

    申请号:US15929364

    申请日:2020-04-28

    Abstract: Computing systems, database systems, and related methods are provided for recommending values for fields of database objects and dynamically updating a recommended value for a field of a database record in response to updated auxiliary data associated with the database record. One method involves obtaining associated conversational data, segmenting the conversational data, converting each respective segment of conversational data into a numerical representation, generating a combined numerical representation of the conversational data based on the sequence of numerical representations using an aggregation model, generating the recommended value based on the combined numerical representation of the conversational data using a prediction model associated with the field, and autopopulating the field of the case database object with the recommended value.

    GENERATING OR UPDATING CROSS-COMMUNITY STREAMS

    公开(公告)号:US20210342039A1

    公开(公告)日:2021-11-04

    申请号:US17302989

    申请日:2021-05-18

    Abstract: Disclosed are examples of systems, apparatus, methods and computer program products for generating or updating cross-community streams. A plurality of communities can be maintained on behalf of a plurality of member organizations. Members of each community can have access to a corresponding set of records. One or more selections operable to assign one or more records to one or more cross-community streams can be displayed in a user interface on a display of a device of a first user. A first request from the first user to assign a first set of one or more records to a first cross-community stream can be processed. The first cross-community stream can be generated or updated.

    Omni-platform question answering system

    公开(公告)号:US11055354B2

    公开(公告)日:2021-07-06

    申请号:US15803698

    申请日:2017-11-03

    Abstract: Methods, systems, and devices for processing and answering a natural language query at a database server are described. An end user may submit a question in natural language over a communication platform. An answer engine running on the database server may receive the question, and may process the content of the question using natural language processing (NLP) techniques. The answer engine may construct a search query based on the NLP, and may retrieve a set of documents from a database using the search query. The answer engine may rank the documents, prune the number of documents, modify the documents for the given communication platform, or perform any combination of these functions. In some cases, an intermediate user may review the documents, and may select one or more documents for publication. The answer engine may send the selected documents to the end user as answers in response to the question.

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