Generating predictive models for authoring short messages

    公开(公告)号:US10528652B2

    公开(公告)日:2020-01-07

    申请号:US16049384

    申请日:2018-07-30

    Abstract: A method for generating predictive insights for authoring messages is provided. The method includes receiving a message to be sent as an input. Key performance indicator (KPI) whose value is to be predicted for the message is identified from the input or marketing tool configuration. A plurality of feature vectors of the message are generated. KPI contributions for the plurality of feature vectors are determined using feature vectors of messages sent in past and tracked KPI values of the messages sent in past. The KPI contribution is a measure of contribution of feature vector to value of the KPI. Value of the KPI for the message is predicted by applying determined KPI contributions to the plurality of feature vectors. Apparatus for substantially performing the method as described herein is also provided.

    PREDICTION OF TONE OF INTERPERSONAL TEXT COMMUNICATIONS

    公开(公告)号:US20190311035A1

    公开(公告)日:2019-10-10

    申请号:US15945996

    申请日:2018-04-05

    Applicant: Adobe Inc.

    Abstract: Techniques are disclosed for predicting a tone of a text communication using psycholinguistic features of the text communication. In some examples, a method may include generating a feature vector for a text communication using features, including psycholinguistic features, extracted from the text communication, and predicting a tone of the text communication based on the feature vector. The tone is predicted by a trained prediction module that is trained using psycholinguistic features of text communications in a training set used to train the trained prediction module. The predicted tone is at least one of a predicted measure of frustration, a predicted measure of formality, and a predicted measure of politeness.

    Prediction of tone of interpersonal text communications

    公开(公告)号:US10796095B2

    公开(公告)日:2020-10-06

    申请号:US15945996

    申请日:2018-04-05

    Applicant: Adobe Inc.

    Abstract: Techniques are disclosed for predicting a tone of a text communication using psycholinguistic features of the text communication. In some examples, a method may include generating a feature vector for a text communication using features, including psycholinguistic features, extracted from the text communication, and predicting a tone of the text communication based on the feature vector. The tone is predicted by a trained prediction module that is trained using psycholinguistic features of text communications in a training set used to train the trained prediction module. The predicted tone is at least one of a predicted measure of frustration, a predicted measure of formality, and a predicted measure of politeness.

    Classifying and ranking changes between document versions

    公开(公告)号:US10713432B2

    公开(公告)日:2020-07-14

    申请号:US15476640

    申请日:2017-03-31

    Applicant: Adobe Inc.

    Abstract: This disclosure generally covers systems and methods that identify and differentiate types of changes made from one version of a document to another version of the document. In particular, the disclosed systems and methods identify changes between different document versions as factual changes or paraphrasing changes or (in some embodiments) as changes of a more specific revision category. Moreover, in some embodiments, the disclosed systems and methods also generate a comparison of the first and second versions that identifies changes as factual changes or paraphrasing changes or (in some embodiments) as changes of a more specific revision category. The disclosed systems and methods, in some embodiments, further rank sentences that include changes made between different document versions or group similar (or the same) type of changes within a comparison of document versions.

    Constructing enterprise-specific knowledge graphs

    公开(公告)号:US10915577B2

    公开(公告)日:2021-02-09

    申请号:US15928288

    申请日:2018-03-22

    Applicant: ADOBE INC.

    Abstract: A framework is provided for constructing enterprise-specific knowledge bases from enterprise-specific data that includes structured and unstructured data. Relationships between entities that match known relationships are identified for each of a plurality of tuples included in the structured data. Where possible, relationships between entities that match known relationships also are identified for tuples included in the unstructured data. If matching relationships between entities that cannot be identified for tuples in the unstructured data, extracted relationships are sequentially clustered to similar relationships and a relationship is assigned to the clustered tuples. An enterprise-specific knowledge graph is constructed from the structured-data-tuples and their identified relationships, the unstructured-data-tuples where the relationships could be mapped to a known relationship and their identified relationships, and the unstructured-data-tuples that could not be mapped to a known relationship and their assigned relationships. The knowledge graph is enriched with any information determined to be missing therefrom.

    Tagging documents with security policies

    公开(公告)号:US10783262B2

    公开(公告)日:2020-09-22

    申请号:US15424527

    申请日:2017-02-03

    Applicant: ADOBE INC.

    Abstract: Embodiments of the present invention provide systems, methods, and computer storage media directed to facilitate identification of security policies for documents. In one embodiment, content features are identified from a set of documents having assigned security policies. The content features and corresponding security policies are analyzed to generate a security policy prediction model. Such a security policy prediction model can then be used to identify a security policy relevant to a document.

    Content optimization for audiences

    公开(公告)号:US10922492B2

    公开(公告)日:2021-02-16

    申请号:US16024131

    申请日:2018-06-29

    Applicant: Adobe Inc.

    Abstract: Techniques are disclosed to assist an author in creating content variations of a given input text to better suit the mood or the affect preferences of the target audience. Affect distribution in the content is utilized to capture these psycholinguistic preferences. According to one embodiment, in a first phase the optimal/idea psycholinguistic preference for text content aimed at a particular audience segment is determined. In a second phase, a given text content is modified to align to a target language distribution, which was determined in the first phase. In one example case, word level replacement, insertions and deletions are executed to generate a modified and coherent version of the input text. The output text thus reflects the psycholinguistic requirements of the audience.

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