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公开(公告)号:US10769426B2
公开(公告)日:2020-09-08
申请号:US14929128
申请日:2015-10-30
Applicant: Microsoft Technology Licensing, LLC
Inventor: Songtao Guo , Ke Wang , Alex Ching Lai , Aarti Kumar , Keith Wai Kit Tsang , Rekha Thakur , Song Lin , Christopher Matthew Degiere
IPC: G06Q10/06 , G06Q30/02 , G06K9/00 , G06K9/62 , G06Q10/10 , G06N20/00 , G06F16/58 , G06F16/28 , G06F16/951 , G06F16/583 , G06F16/901 , G06F16/2453 , G06K9/46 , G06F16/215 , G06N5/00 , G06N20/20 , G06N7/00 , G06N7/02 , G06Q50/00 , H04L29/08
Abstract: In an example embodiment, a member profile corresponding to a member of a social networking service is obtained. Usage information for the member is then obtained, and one or more member metrics are calculated based on the member profile and usage information for the corresponding member. A plurality of features are extracted from the member profile and the one or more member metrics. The plurality of features is inserted into an organization name confidence score model to obtain a confidence score for an organization name in the member profile.
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公开(公告)号:US10242258B2
公开(公告)日:2019-03-26
申请号:US14929104
申请日:2015-10-30
Applicant: Microsoft Technology Licensing, LLC
Inventor: Songtao Guo , Christopher Matthew Degiere , Aarti Kumar , Alex Ching Lai , Xian Li
IPC: G06K9/46 , G06K9/00 , G06K9/62 , G06F17/30 , G06Q10/10 , G06N99/00 , G06N7/02 , G06Q10/06 , G06Q50/00 , H04L29/08
Abstract: In an example embodiment, a fuzzy join operation is performed by, for each pair of records, evaluating a first plurality of features for both records in the pair of records by calculating term frequency-inverse term frequency (TF-IDF) for each token of each field relevant to each feature and based on the calculated TF-IDF for each token of each field relevant to each feature, computing a similarity score based on the similarity function by adding a weight assigned to the TF-IDF for any token that appears in both records. Then a graph data structure is created, having a node for each record in the plurality of records and edges between each of the nodes, except, for each record pair having a similarity score that does not transgress a first threshold, causing no edge between the nodes for the record pair to appear in the graph data structure.
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公开(公告)号:US10127469B2
公开(公告)日:2018-11-13
申请号:US14841538
申请日:2015-08-31
Applicant: Microsoft Technology Licensing, LLC
Inventor: Alex Lai , Songtao Guo , Chris Degiere
Abstract: Techniques are provided for automatically creating online accounts based on digital images, such as digital images of business cards. In one technique, multiple data items that have been extracted from a digital image of a business card are identified. A particular data item is contact information of a user associated with (or identified by) the business card. A verification code is sent, based on the particular data item, to a computing device of the user. The verification code is received from the computing device of the user. In response to receiving the verification code an account is created for the user and the account is modified to include a least some of the multiple data items.
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公开(公告)号:US20220198264A1
公开(公告)日:2022-06-23
申请号:US17133259
申请日:2020-12-23
Applicant: Microsoft Technology Licensing, LLC
Inventor: Songtao Guo , Robert Perrin REEVES , Bo YANG , Wan Qi GAO , William TANG , Patrick Ryan DRISCOLL , Shan ZHOU , Taylor Shelby BURFIELD , Adriana Dominique MEZA
Abstract: In an example embodiment, a machine-learned model is trained to rank anomaly points in time series data. The model is capable of being applied in parallel to many different time series simultaneously, allowing for a scalable solution for large scale online networks. The model outputs a ranking score for an input anomaly and allows for ranking of anomalies not just in the same time series but anomalies across multiple time series as well. This ranking can then be used to determine how best to present the ranked anomalies to users in a graphical user interface.
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公开(公告)号:US11068848B2
公开(公告)日:2021-07-20
申请号:US14814403
申请日:2015-07-30
Applicant: Microsoft Technology Licensing, LLC
Inventor: Aman Grover , Siyu You , Krishnaram Kenthapadi , Parul Jain , Fedor Vladimirovich Borisyuk , Christopher Matthew Degiere , Songtao Guo
Abstract: A member profile including a vector containing a field for each of a plurality of skills and a rating of one or more of the skills in the vector for a member of a social networking service is obtained. A first distance indicating a vector distance between the vector of the member profile and a vector of a hypothetical member profile representing the perfect job candidate is obtained. A hypothetical member profile for the member is created by combining the vector of the member profile with the indication of how each of the one or more skills is improved through taking the course from course information. A second distance between the member and the hypothetical perfect candidate for the job is obtained, and the difference between the first distance and the second distance is calculated to determine an estimate of how much the course will increase the member's job chances.
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公开(公告)号:US10380701B2
公开(公告)日:2019-08-13
申请号:US14841495
申请日:2015-08-31
Applicant: Microsoft Technology Licensing, LLC
Inventor: Song Lin , Cindy Zhou , Songtao Guo
IPC: G06Q50/00
Abstract: Methods and systems for generating tailored user interface presentations based on skills clusters and automatically modified member profiles are presented. According to various embodiments, a set of skills are accessed and a skills matrix generated. A set of co-occurrences among the set of skills are identified. A set of skills clusters is automatically generated based on identifying of the co-occurrences and the skills clusters are automatically validated. A graphical representation of the validated skills cluster is presented with user interface elements for modifying the validated skills cluster and data representing member profiles is presented based on the validated skills cluster.
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公开(公告)号:US20180218207A1
公开(公告)日:2018-08-02
申请号:US15937051
申请日:2018-03-27
Applicant: MICROSOFT TECHNOLOGY LICENSING, LLC
Inventor: Songtao Guo , Christopher Matthew Degiere , Jingjing Huang , Aarti Kumar , Alex Ching Lai , Xian Li
IPC: G06K9/00 , H04L29/08 , G06F17/30 , G06Q50/00 , G06Q10/10 , G06Q10/06 , G06N99/00 , G06N7/02 , G06K9/62
CPC classification number: G06K9/00456 , G06F17/30256 , G06F17/30259 , G06F17/30265 , G06F17/30448 , G06F17/30466 , G06F17/30598 , G06F17/30864 , G06F17/30958 , G06K9/00469 , G06K9/46 , G06K9/6215 , G06K9/6256 , G06K9/6263 , G06K9/6276 , G06K2209/25 , G06N7/02 , G06N99/005 , G06Q10/06393 , G06Q10/10 , G06Q50/01 , H04L67/10 , H04L67/306
Abstract: In an example embodiment, a web page is obtained using a web page address stored in a first record and is parsed to extract one or more images from the web page along with a first plurality of features for each of the one or more images from the web page. Information about each image of the web page and the extracted first plurality of features for the web page are input into a supervised machine learning classifier to calculate a logo confidence score for each image of the web page, the logo confidence score indicating the probability that the image is an organization logo. In response to a particular image in the web page having a logo confidence score transgressing a first threshold, the particular image is injected into an organization logo field of the first record.
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公开(公告)号:US10002292B2
公开(公告)日:2018-06-19
申请号:US14929116
申请日:2015-10-30
Applicant: Microsoft Technology Licensing, LLC
Inventor: Songtao Guo , Christopher Matthew Degiere , Jingjing Huang , Aarti Kumar , Alex Ching Lai , Xian Li
IPC: G06K9/00 , G06N99/00 , G06F17/30 , G06Q10/10 , G06F17/27 , G06K9/62 , G06N7/02 , G06Q10/06 , G06Q50/00 , H04L29/08
CPC classification number: G06K9/00456 , G06F16/215 , G06F16/24534 , G06F16/24544 , G06F16/285 , G06F16/58 , G06F16/5838 , G06F16/5854 , G06F16/9024 , G06F16/951 , G06K9/00469 , G06K9/46 , G06K9/6215 , G06K9/6256 , G06K9/6263 , G06K9/6276 , G06K2209/25 , G06N5/003 , G06N7/005 , G06N7/02 , G06N20/00 , G06N20/20 , G06Q10/06393 , G06Q10/10 , G06Q50/01 , H04L67/10 , H04L67/306 , Y04S10/54
Abstract: In an example embodiment, a web page is obtained using a web page address stored in a first record and is parsed to extract one or more images from the web page along with a second plurality of features for each of the one or more images from the web page. Information about each image of the web page and the extracted second plurality of features for the web page are input into a supervised machine learning classifier to calculate a logo confidence score for each image of the web page, the logo confidence score indicating the probability that the image is an organization logo. In response to a particular image in the web page having a logo confidence score transgressing a first threshold, the particular image is injected into an organization logo field of the first record.
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公开(公告)号:US12112263B2
公开(公告)日:2024-10-08
申请号:US17116184
申请日:2020-12-09
Applicant: Microsoft Technology Licensing, LLC
Inventor: Bo Yang , Chaofan Huang , Songtao Guo , Robert Perrin Reeves , Wan Qi Gao , Patrick Ryan Driscoll , Kristina Caroline Ryan , Michael Mario Jennings , Jeremy Lwanga , Manzarul Azad Kazi
IPC: G06N3/08 , G06F18/20 , G06F18/21 , G06F18/2113 , G06F18/25
CPC classification number: G06N3/08 , G06F18/2113 , G06F18/2163 , G06F18/217 , G06F18/25 , G06F18/29
Abstract: In an example embodiment, a model is trained to specifically identify reversal points in data and then to rank these reversal points in order of importance. A reversal point shall be defined as a point in which a particular metric, specifically a first order derivative, crosses over from positive to negative or vice-versa. Users are more likely to be interested in abnormal and significant changes in data, and thus the machine-learned model is trained to evaluate a reversal point based on two dimensions: abnormality and significance.
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公开(公告)号:US11580099B2
公开(公告)日:2023-02-14
申请号:US17038395
申请日:2020-09-30
Applicant: Microsoft Technology Licensing, LLC
Inventor: Wenxiang Chen , William Tang , Runfang Zhou , Tanvi Sudarshan Motwani , Jeremy Lwanga , Sara Smoot Gerrard , Daniel Sairom Krishnan Hewlett , Alexandre Patry , Songtao Guo , Sai Krishna Bollam
IPC: G06F16/00 , G06F16/242 , G06K9/62 , G06F16/9032 , G06F16/9035
Abstract: Methods are presented for providing dynamic search filter suggestions that are updated and ranked based on the user filter selections. One method includes detecting a query received in a user interface (UI), calculating, by a search-candidate model, first search results, and calculating, by a suggestions model, first filter suggestions for filter categories to filter responses to the query. The suggestions model is obtained by training a machine-learning algorithm utilizing pairwise learning-to-rank modeling. The first search results and the first filter suggestions are presented in the UI. When a selection in the UI of a filter suggestion is detected, the search-candidate model calculates second search results for the filter categories based on the query and the selected filter suggestion, and the suggestions model calculates second first filter suggestions based on the query and the selected filter suggestion. The second search results and the second filter suggestions are presented in the UI.
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