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公开(公告)号：US20240144356A1
公开(公告)日：2024-05-02
申请号：US17981252
申请日：2022-11-04
申请人： WEVO, INC.
发明人： Dustin Garvey , Shannon Walsh , Frank Chiang , Janet Muto , Nitzan Shaer , Charlie Hoang , Hannah Sieber , Nick Montaquila , Jessica Yau , Joseph Gibson , Mary McMurray , Laurie Delaney , Andrea Paola Aguilera García , Alexa Stewart
CPC分类号： G06Q30/0641 , G06Q30/0201 , G06Q30/0203
摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system receives input defining or modifying a theme schema for classifying results of user experience tests. Responsive to receiving the input, the system trains a themer model based at least in part on example classifications in a training dataset, where the classifications map results to themes within the theme schema. When a new set of results for a user experience test is received, the trained machine learning model may generate a set of predicted themes to classify the test results. The output of the model may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.
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公开(公告)号：US11972442B1
公开(公告)日：2024-04-30
申请号：US18111444
申请日：2023-02-17
申请人： Wevo, Inc.
发明人： Dustin Garvey , Shannon Walsh , Frank Chiang , Janet Muto , Nitzan Shaer , Hannah Sieber , Charlie Hoang , Alexa Stewart , Keith Horvath , Marshall McCready , Laurie Delaney , Jon Andrews
IPC分类号： G06Q30/018 , G06F9/451
CPC分类号： G06Q30/0185 , G06F9/451
摘要： Techniques and embodiments are described herein for detecting and mitigating fraudulent activity within user experience (UX) test applications. In some embodiments, a system applies a set of rules and/or machine learning (ML) models to each respondent of an online survey or UX test. Different ML models may be trained to learn domain-specific patterns indicative of fraudulent activity. The system may then select the ML models based on attributes of the UX test and/or respondent. The selected rules and/or ML models may generate a probabilistic score representing a likelihood that the respondent is currently engaging in or will engage in fraudulent activity with respect to a UX test. If the score exceeds a threshold, then the system may take action to mitigate the fraudulent activity, such as triggering the removal of the user from an accepted respondent pool, halting further engagement between the respondent and the UX test, and generating alerts.
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公开(公告)号：US20240144107A1
公开(公告)日：2024-05-02
申请号：US17979230
申请日：2022-11-02
申请人： WEVO, INC.
发明人： Dustin Garvey , Shannon Walsh , Frank Chiang , Janet Muto , Nitzan Shaer , Charlie Hoang , Hannah Sieber , Nick Montaquila , Jessica Yau , Joseph Gibson , Mary McMurray , Laurie Delaney , Andrea Paola Aguilera García, I , Alexa Stewart
摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system identifies a set of expectation elements associated with one or more UX tests. An expectation element may specify, using unstructured data that does not conform to a schema, an expectation for a user experience and a respective outcome for the user experience. A themer model may generate predictions that map the respective expectation elements to a theme from a theme schema, which may include a plurality of themes. A selector model may generate selection scores for the expectation elements. The predicted themes and selection scores may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.
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公开(公告)号：US20240144297A1
公开(公告)日：2024-05-02
申请号：US17979231
申请日：2022-11-02
申请人： WEVO, INC.
发明人： Dustin Garvey , Shannon Walsh , Frank Chiang , Janet Muto , Nitzan Shaer , Charlie Hoang , Hannah Sieber , Nick Montaquila , Jessica Yau , Joseph Gibson , Mary McMurray , Laurie Delaney , Andrea Paola Aguilera García, I , Alexa Stewart
IPC分类号： G06Q30/02
CPC分类号： G06Q30/0201 , G06Q30/0203
摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system receives input defining or modifying a theme schema for classifying results of user experience tests. Responsive to receiving the input, the system trains a themer model based at least in part on example classifications in a training dataset, where the classifications map results to themes within the theme schema. When a new set of results for a user experience test is received, the trained machine learning model may generate a set of predicted themes to classify the test results. The output of the model may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.
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公开(公告)号：US11748248B1
公开(公告)日：2023-09-05
申请号：US17981249
申请日：2022-11-04
申请人： WEVO, INC.
发明人： Dustin Garvey , Shannon Walsh , Frank Chiang , Janet Muto , Nitzan Shaer , Charlie Hoang , Hannah Sieber , Nick Montaquila , Jessica Yau , Joseph Gibson , Mary McMurray , Laurie Delaney , Andrea Paola Aguilera García , Alexa Stewart
CPC分类号： G06F11/3692
摘要： Techniques are described herein for selecting, curating, normalizing, enriching, and synthesizing the results of user experience (UX) tests. In some embodiments, a system identifies a set of expectation elements associated with one or more UX tests. An expectation element may specify, using unstructured data that does not conform to a schema, an expectation for a user experience and a respective outcome for the user experience. A themer model may generate predictions that map the respective expectation elements to a theme from a theme schema, which may include a plurality of themes. A selector model may generate selection scores for the expectation elements. The predicted themes and selection scores may be used to render user interfaces and/or trigger other actions directed to optimizing a product's design.
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