Levels of competency in an online community

    公开(公告)号:US10389679B2

    公开(公告)日:2019-08-20

    申请号:US16152107

    申请日:2018-10-04

    Applicant: Adobe Inc.

    Abstract: Techniques and systems are described to determine levels of competency of users as part of an online community and control generation of subsequent digital content to be used interaction of the online community with the users based on this determination. In one example, determination of the level of competency is based on relevance to topics of the online community. In another example, a determination is made as to whether the topic of the online community is stable before using user competency scores to control generation of subsequent digital content. In a further example, users of the online community are identified as exhibiting dormant or non-dormant behavior and used as a basis to control generation of subsequent digital content. In yet another example, user competency scores are adjusted based on a decay factor to address dormancy of users over a period of time.

    DETERMINING BRAND EXCLUSIVENESS OF USERS
    4.
    发明申请

    公开(公告)号:US20190087838A1

    公开(公告)日:2019-03-21

    申请号:US16196784

    申请日:2018-11-20

    Applicant: ADOBE INC.

    Abstract: Embodiments of the present invention relate to a determination of a user's exclusiveness toward a particular brand. User-specific entities are extracted from social media content associated with a user. At least a portion of the user-specific entities are brand-related entities that are specifically relevant to a particular brand. These brand-related entities are analyzed with respect to the user-specific entities extracted from the social media content to determine a level of exclusivity of the user to the brand.

    Expanding input content utilizing previously-generated content

    公开(公告)号:US10733359B2

    公开(公告)日:2020-08-04

    申请号:US15248675

    申请日:2016-08-26

    Applicant: ADOBE INC.

    Abstract: Systems and methods provide for expanding user-provided content. User-provided input content is received via a user interface. Content that is relevant to the user-provided input content is identified from a repository of previously-generated content. The identified relevant content is divided into content sub-segments. From the content sub-segments, one or more pieces of candidate content are identified based on each content sub-segment's relevance to the received input content. At least one piece of identified candidate content is provided for display. A selection of one or more pieces of identified candidate content is received, such that the selected piece(s) of identified candidate content is appended to the received input content, thereby expanding the user-provided content.

    Automatic aggregation of online user profiles

    公开(公告)号:US10296546B2

    公开(公告)日:2019-05-21

    申请号:US14551365

    申请日:2014-11-24

    Applicant: Adobe Inc.

    Abstract: Techniques are disclosed for identifying the same online user across different communication networks, and further creating a unified profile for that user. The unified profile is an aggregation of publicly available user profile attributes across the different networks. In an embodiment, the techniques are implemented as a computer implemented methodology, including: (1) feature space analysis to identify relevant user features that allows for clusterization of the given target network(s), (2) unsupervised candidate selection to identify one or more candidate user profiles from each target network and that are likely belonging to a target user or so-called queried user, and (3) supervised user identification to identify a likely matching user profile for that target user from each target network. A unified user profile can then be built from data taken from all matched user profiles, and effectively allows a marketer to better understand that user and hence execute more informed targeting.

    BERT-BASED MACHINE-LEARNING TOOL FOR PREDICTING EMOTIONAL RESPONSE TO TEXT

    公开(公告)号:US20220129621A1

    公开(公告)日:2022-04-28

    申请号:US17079681

    申请日:2020-10-26

    Applicant: Adobe Inc.

    Abstract: Certain embodiments involve using machine-learning tools that include Bidirectional Encoder Representations from Transformers (“BERT”) language models for predicting emotional responses to text by, for example, target readers having certain demographics. For instance, a machine-learning model includes, at least, a BERT encoder and a classification module that is trained to predict demographically specific emotional responses. The BERT encoder encodes the input text into an input text vector. The classification module generates, from the input text vector and an input demographics vector representing a demographic profile of the reader, an emotional response score.

    Utilizing a genetic framework to generate enhanced digital layouts of digital fragments

    公开(公告)号:US10984172B2

    公开(公告)日:2021-04-20

    申请号:US17008570

    申请日:2020-08-31

    Applicant: Adobe Inc.

    Abstract: The present disclosure includes systems, methods, and non-transitory computer readable media that utilize a genetic framework to generate enhanced digital layouts from digital content fragments. In particular, in one or more embodiments, the disclosed systems iteratively generate a layout chromosome of digital content fragments, determine a fitness level of the layout chromosome, and mutate the layout chromosome until converging to an improved fitness level. The disclosed systems can efficiently utilize computing resources to generate a digital layout from a layout chromosome that is optimized to specified platforms, distribution audiences, and target optimization goals.

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