Salesforce Com, Inc.

Son Thanh Chang

Orjan Nils Kjellberg

George Hu

Chaitanya Malla

Carlos Enrique Mogollan Jimenez

Kristen Noriko Muramoto

Clement Jacques Antoine Tussoit

Melissa Hoang

Marc Brette

Pierre-Yves Chevalier

Na Cheng

Bruno Roustant

Weiping Peng

Ilan Ginzburg

Jacob Nathaniel Huffman

Francois Lopitaux

Khoa Le

Feifei Jiang

Pierre Salagnac

Ghislain Brun

Nandini Suresh Kumar

Christopher Larry

Jean-Baptiste Charlety

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.

Dynamic field value recommendation methods and systems

A method of training a predictive model to predict a likely field value for one or more user selected fields within an application. The method comprises providing a user interface for user selection of the one or more user selected fields within the application; analyzing a pre-existing, user provided data set of objects; training, based on the analysis, the predictive model; determining, for each user selected field based on the analysis, a confidence function for the predictive model that identifies the percentage of cases predicted correctly at different applied confidence levels, the percentage of cases predicted incorrectly at different applied confidence levels, and the percentage of cases in which the prediction model could not provide a prediction at different applied confidence levels; and providing a user interface for user review of the confidence functions for user selection of confidence threshold levels to be used with the predictive model.

System and method for field value recommendations based on confidence levels in analyzed dataset

A database system may generate a new case associated with a customer support query. The database system may initiate a search for other cases related to the new case and identify articles linked to the related cases. The database system may identify more relevant articles by finding the related cases that use a similar vocabulary for describing similar customer problems. The database system then identifies the articles used for resolving the prior problems. Thus, the database system may bridge the gap between vocabularies used by customers to describe problems and vocabularies used in articles to describe solutions to those problems.

Identifying relevant material for cases

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Oakland, CA, United States of America

Son Thanh Chang