公开(公告)号：US11334564B2

公开(公告)日：2022-05-17

申请号：US16942511

申请日：2020-07-29

Applicant: Microsoft Technology Licensing, LLC

Inventor： Saurabh Kataria ,  Ada Cheuk Ying Yu ,  Dhruv Arya ,  Swanand Wakankar

IPC: G06F16/2452 ,  G06F16/9537 ,  G06F16/242 ,  G06F16/9535 ,  G06F16/2457 ,  G06F16/248 ,  G06Q10/10 ,  G06N3/04

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.

公开(公告)号：US20190171728A1

公开(公告)日：2019-06-06

申请号：US15922043

申请日：2018-03-15

Applicant: Microsoft Technology Licensing, LLC

Inventor： Swanand Wakankar ,  Dhruv Arya ,  Saurabh Kataria ,  Ada Cheuk Ying Yu

IPC: G06F17/30 ,  G06F9/451

Abstract: In some embodiments, the disclosed subject matter involves techniques for generating type-ahead 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. 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.

公开(公告)号：US20200311568A1

公开(公告)日：2020-10-01

申请号：US16365050

申请日：2019-03-26

Applicant: Microsoft Technology Licensing, LLC

Inventor： Huichao Xue ,  Girish Kathalagiri Somashekariah ,  Ye Yuan ,  Varun Mithal ,  Junrui Xu ,  Ada Cheuk Ying Yu

IPC: G06N5/04 ,  G06F16/9535 ,  G06F16/9536 ,  G06N20/00 ,  G06F16/901

Abstract: In some embodiments, a computer system selects a first subset of candidate content items based on their filter scores that are generated based on a partial generalized linear mixed model comprising a baseline model and a user-based model, with the baseline model being a generalized linear model, and the user-based model being a random effects model based on user actions by the target user directed towards reference content items related to the candidate content items. In some embodiments, the computer system then selects a second subset from the first subset based on recommendation scores that are generated based on a full generalized linear mixed model comprising the baseline model, the user-based model, and an item-based model, with the item-based model being a random effects model based on user actions directed towards the candidate online content item by reference users related to the target user.

公开(公告)号：US20200151586A1

公开(公告)日：2020-05-14

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

IPC: G06N5/04 ,  G06N99/00

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.

公开(公告)号：US20190130023A1

公开(公告)日：2019-05-02

申请号：US15908467

申请日：2018-02-28

Applicant: Microsoft Technology Licensing, LLC

Inventor： Saurabh Kataria ,  Lin Guo ,  Ada Cheuk Ying Yu ,  Dhruv Arya

IPC: G06F17/30

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for expanding search queries. A search system determines a set of candidate alternate search terms based on historical search logs that include records of previously submitted search terms, corresponding search results that were presented to users, and corresponding search results that were selected by the users. The set of candidate alternate search terms is selected from titles of the corresponding search results that were selected by the users. The search system ranks the set of candidate alternate search terms based on determined probabilities that each of the alternate candidate search terms will be selected if presented to a user, and selects a first candidate alternate search term from the set of candidate alternate search terms based on the ranking. The search system generates an expanded search term based on the first candidate alternate search term.

公开(公告)号：US20190129995A1

公开(公告)日：2019-05-02

申请号：US15907496

申请日：2018-02-28

Applicant: Microsoft Technology Licensing, LLC

Inventor： Saurabh Kataria ,  Yiqun Liu ,  Ada Cheuk Ying Yu ,  Dhruv Arya

IPC: G06F17/30 ,  G06Q10/10

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for expanding search queries. A search system identifies, based on search parameters received from a client device, a target company identified in the search parameters. The search parameters include a search term comprising at least two keywords, a first one of the at least two keyword identifying the target company, and the second one of the at least two keywords identifying an employment position. The search system identifies a second company based on a set of peer scores indicating a probability of employees transitioning between companies. The peer scores are calculated based on historical movement data indicating employee transitions between companies. The search system generates an expanded search term comprising a new keyword identifying the second company and the second keyword identifying the employment position.

公开(公告)号：US10769141B2

公开(公告)日：2020-09-08

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: G06F16/2452 ,  G06F16/242 ,  G06F16/9535 ,  G06F16/2457 ,  G06F16/248 ,  G06Q10/10 ,  G06N3/04 ,  G06F16/9537

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.

公开(公告)号：US10747793B2

公开(公告)日：2020-08-18

申请号：US15908467

申请日：2018-02-28

Applicant: Microsoft Technology Licensing, LLC

Inventor： Saurabh Kataria ,  Lin Guo ,  Ada Cheuk Ying Yu ,  Dhruv Arya

IPC: G06F16/338 ,  G06N3/04 ,  G06F16/33 ,  G06F16/332

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for expanding search queries. A search system determines a set of candidate alternate search terms based on historical search logs that include records of previously submitted search terms, corresponding search results that were presented to users, and corresponding search results that were selected by the users. The set of candidate alternate search terms is selected from titles of the corresponding search results that were selected by the users. The search system ranks the set of candidate alternate search terms based on determined probabilities that each of the alternate candidate search terms will be selected if presented to a user, and selects a first candidate alternate search term from the set of candidate alternate search terms based on the ranking. The search system generates an expanded search term based on the first candidate alternate search term.

公开(公告)号：US20200151672A1

公开(公告)日：2020-05-14

申请号：US16185262

申请日：2018-11-09

Applicant: Microsoft Technology Licensing, LLC

Inventor： Huichao Xue ,  Ye Yuan ,  Girish Kathalagiri Somashekariah ,  Ada Cheuk Ying Yu

IPC: G06Q10/10 ,  G06Q50/00 ,  G06N99/00 ,  G06N5/04

Abstract: The disclosed embodiments provide a system that ranks job recommendations based on title preferences. During operation, the system determines features related to applications for jobs by a candidate, wherein the features include a title preference for the candidate and a similarity between a first set of attribute values for the candidate and a second set of attribute values for a job. Next, the system applies a machine learning model to the features to produce scores representing likelihoods of the candidate applying to the jobs. The system then generates a ranking of the jobs by the scores. Finally, the system outputs, to the candidate, at least a portion of the ranking as a set of recommendations.

公开(公告)号：US20200311112A1

公开(公告)日：2020-10-01

申请号：US16367820

申请日：2019-03-28

Applicant: Microsoft Technology Licensing, LLC

Inventor： Meng Meng ,  Gheorghe Muresan ,  Ada Cheuk Ying Yu

IPC: G06F16/33 ,  G06F16/31 ,  G06F16/9535 ,  G06N20/00 ,  G06Q10/06

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.