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公开(公告)号：US20200151647A1
公开(公告)日：2020-05-14
申请号：US16185272
申请日：2018-11-09
Applicant: Microsoft Technology Licensing, LLC
Inventor： Girish Kathalagiri Somashekariah , Huichao Xue , Ye Yuan , Meng Meng , Ada Cheuk Ying Yu
Abstract: The disclosed embodiments provide a system for recommending jobs based on title transition embeddings. During operation, the system obtains a word embedding model of job histories of members of an online network. Next, the system applies the word embedding model to a first set of attributes associated with a title of a candidate to produce a first embedding. The system also applies the word embedding model to a second set of attributes associated with a job title of a job to produce a second embedding. The system then calculates a similarity between the first and second embeddings. Finally, the system outputs the similarity for use in recommending the job to the candidate.
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12.发明授权公开(公告)号：US11769165B2
公开(公告)日：2023-09-26
申请号：US17166190
申请日：2021-02-03
Applicant: Microsoft Technology Licensing, LLC
Inventor： Chunzhe Zhang , Satej Milind Wagle , Linda Fayad , Ada Cheuk Ying Yu
IPC: G06Q30/0204 , G06N3/08 , G06N3/04 , G06Q30/0201
CPC classification number: G06Q30/0204 , G06N3/04 , G06N3/08 , G06Q30/0201
Abstract: In an example embodiment, a specialized machine learned model, called a look-alike model, is trained using a machine learning algorithm to predict future job engagement for a user. This look-alike model is then used to create new segments on top of the segments provided by a rules-based approach. Specifically, the look-alike model is designed to take users who have been segmented by a rule-based approach into an “inactive job seeker” categorization (such as those assigned to the resting users and dormant users segments) and calculate a predicted job engagement score for these users. Based on the predicted job engagement score, a user may then be reassigned from one of the inactive job seeker categorizations to one of one or more new job seeker categorizations (such as predicted open job seekers or predicted opportunistic job seekers).
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Patent Agency Ranking
公开(公告)号：US11544308B2
公开(公告)日：2023-01-03
申请号：US16367820
申请日：2019-03-28
Applicant: Microsoft Technology Licensing, LLC
Inventor： Meng Meng , Gheorghe Muresan , Ada Cheuk Ying Yu
Abstract: The disclosed embodiments provide a system for processing data. During operation, the system obtains labels for entities found in portions of text in a first set of jobs. Next, the system inputs the portions of text and the labels as training data for a machine learning model. The system then applies the machine learning model to a second set of jobs to generate predictions of additional entities in additional portions of text in the second set of jobs. Finally, the system creates, based on the predictions, an index containing mappings of the additional entities to subsets of the second set of jobs in which the additional entities are found.
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公开(公告)号：US11443255B2
公开(公告)日：2022-09-13
申请号：US16185365
申请日：2018-11-09
Applicant: Microsoft Technology Licensing, LLC
Inventor： Ye Yuan , Girish Kathalagiri Somashekariah , Huichao Xue , Ada Cheuk Ying Yu
Abstract: The disclosed embodiments provide a system for performing activity-based inference of title preferences. During operation, the system determines features and labels related to first title preferences for jobs sought by a first set of candidates. Next, the system inputs the features and the labels as training data for a machine learning model. The system then applies the machine learning model to additional features for a second set of candidates to produce predictions of second title preferences for the second set of candidates. Finally, the system stores the predictions in association with the second set of candidates.
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公开(公告)号：US20200311162A1
公开(公告)日：2020-10-01
申请号：US16367716
申请日：2019-03-28
Applicant: Microsoft Technology Licensing, LLC
Inventor： Junrui Xu , Meng Meng , Girish Kathalagiri Somashekariah , Huichao Xue , Varun Mithal , Ada Cheuk Ying Yu
IPC: G06F16/9536 , G06F16/903 , G06N20/00
Abstract: The disclosed embodiments provide a system for selecting recommendations based on title transition embeddings. During operation, the system obtains a word embedding model of a set of job histories. Next, the system calculates similarities between pairs of the embeddings produced by the word embedding model from attributes associated with titles in the set of job histories. The system then identifies, based on the similarities, job titles with high similarity to a current title of the candidate. Finally, the system outputs the job titles for use in selecting job recommendations for the candidate.
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公开(公告)号：US20190171727A1
公开(公告)日：2019-06-06
申请号：US15922033
申请日：2018-03-15
Applicant: Microsoft Technology Licensing, LLC
Inventor： Swanand Wakankar , Dhruv Arya , Saurabh Kataria , Ada Cheuk Ying Yu
Abstract: In some embodiments, the disclosed subject matter involves techniques for generating personalized query suggestions for a user in a specific subject or application domain that are ranked using confidence levels and contextual scoring. Partial query strings may be parsed for literal matching and be processed for spell checks, acronym expansion, and other expansion and rewriting of the partial query to a known possible query suggestion. Possible query suggestions are weighted using global feature metrics and personalized metrics. Various weighting, confidence levels and merging based on scoring may be used to rank the suggestions. A machine learning model may be used to assist in assigning scores based on metrics on interaction in the search domain. Other embodiments are described and claimed.
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公开(公告)号：US20190129998A1
公开(公告)日：2019-05-02
申请号：US15907476
申请日：2018-02-28
Applicant: Microsoft Technology Licensing, LLC
Inventor： Saurabh Kataria , Ada Cheuk Ying Yu , Dhruv Arya , Swanand Wakankar
IPC: G06F17/30
Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for expanding search queries. A search system executes a search query based on a search term and the geographic indicator. In response to determining that a number of the search results is less than a threshold number, the search system determines, based on historical search logs from other users in the first geographic region, a likelihood value indicating a likelihood that the other users in the first geographic region expanded the geographic region of their search queries. The search system compares the likelihood value to a threshold likelihood value, and determines, based on the comparison, that the likelihood value meets or exceeds the threshold likelihood value. The search system then executes an expanded search based on the search term and an expanded geographic indicator that encompasses the first geographic region.
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