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公开(公告)号:US10997560B2
公开(公告)日:2021-05-04
申请号:US15389681
申请日:2016-12-23
Applicant: Google Inc.
Inventor: Pei-Chun Chen , Christian Posse , Zhao Zhang , Xuejun Tao
Abstract: The present disclosure provides systems and methods that improve job posting structure and presentation by, for example, classifying portions of job postings into informative sections. As an example, given a job posting, a computing system implementing aspects of the present disclosure can separate the job posting into multiple portions. After separation into portions, the computing system can classify each portion into the most plausible job-posting-specific section. For example, the computing system can include and implement a machine-learned classification model to classify the portions into the sections. Following classification, the computing system can modify the job posting based on the classification of the portions. In particular, the structure and/or presentation of the job posting can be improved based on the classification of the portions into the sections.
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公开(公告)号:US10579968B2
公开(公告)日:2020-03-03
申请号:US15228662
申请日:2016-08-04
Applicant: Google Inc.
Inventor: Christian Posse , Pei-Chun Chen
IPC: G06Q10/10
Abstract: Methods, apparatus, systems, and computer-readable media are provided for increasing dimensionality of data structures associated with filling positions. In some implementations, a prediction of desired experience for a given position to be filled may be used to increase the dimensionality of a searchable data structure that represents the given position. For example, the predicted desired experience may be incorporated into a searchable field of the data structure. Among other things, increasing the dimensionality of the data structure may facilitate more granular searching of positions and guided creation of new positions to be filled. In some implementations, a predicted desired experience may be used to notify a user posting a new position whether a specified desired experience corresponds to a predicted desired experience.
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公开(公告)号:US20180107983A1
公开(公告)日:2018-04-19
申请号:US15296230
申请日:2016-10-18
Applicant: Google Inc.
Inventor: Seyed Reza Mir Ghaderi , Xuejun Tao , Ye Tian , Matthew Courtney , Pei-Chun Chen , Christian Posse
CPC classification number: G06Q10/1053 , G06F16/24578 , G06F16/9535 , G06N5/022 , G06N20/00
Abstract: Methods, systems, and apparatus, including computer programs encoded on storage devices, for performing a job opportunity search. In one aspect, a system includes a data processing apparatus, and a computer-readable storage device having stored thereon instructions that, when executed by the data processing apparatus, cause the data processing apparatus to perform operations. The operations include defining a vector vocabulary, defining an occupation taxonomy that includes multiple different occupations, obtaining multiple labeled training data items, wherein each labeled training data item is associated with at least (i) a job title, and (ii) an occupation, generating, for each of the respective labeled training data items, an occupation vector that includes a feature weight for each respective term in the vector vocabulary, and associating each respective occupation vector with an occupation in the occupation taxonomy based on the occupation of the labeled training data item used to generate the occupation vector.
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公开(公告)号:US20180181544A1
公开(公告)日:2018-06-28
申请号:US15391946
申请日:2016-12-28
Applicant: Google Inc.
Inventor: Zhao Zhang , Chao Chen , Christian Posse , Xuejun Tao , Pei-Chun Chen , Julie Park
CPC classification number: G06N7/005 , G06F17/277 , G06N3/0445 , G06N3/0454 , G06N3/084 , G06N20/00 , G06Q10/1053
Abstract: Systems and methods for extracting job skills from a job posting are provided. In one embodiment, a computer-implemented method includes obtaining data indicative of a job posting (including textual content associated with a job). The method includes identifying a portion of the textual content that is descriptive of one or more skills associated with the job. The portion of the textual content is in a first format. The method includes converting the portion of the textual content that is descriptive of the one or more skills associated with the job from the first format to a second format. The second format includes one or more text strings. The method includes determining the one or more skills associated with the job based at least in part on one or more of the text strings. The method includes providing an output indicative of the one or more skills associated with the job posting.
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公开(公告)号:US20180039945A1
公开(公告)日:2018-02-08
申请号:US15228662
申请日:2016-08-04
Applicant: Google Inc.
Inventor: Christian Posse , Pei-Chun Chen
CPC classification number: G06Q10/1053
Abstract: Methods, apparatus, systems, and computer-readable media are provided for increasing dimensionality of data structures associated with filling positions. In some implementations, a prediction of desired experience for a given position to be filled may be used to increase the dimensionality of a searchable data structure that represents the given position. For example, the predicted desired experience may be incorporated into a searchable field of the data structure. Among other things, increasing the dimensionality of the data structure may facilitate more granular searching of positions and guided creation of new positions to be filled. In some implementations, a predicted desired experience may be used to notify a user posting a new position whether a specified desired experience corresponds to a predicted desired experience.
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公开(公告)号:US20180181915A1
公开(公告)日:2018-06-28
申请号:US15389681
申请日:2016-12-23
Applicant: Google Inc.
Inventor: Pei-Chun Chen , Christian Posse , Zhao Zhang , Xuejun Tao
IPC: G06Q10/10
CPC classification number: G06Q10/1053 , G06F16/353
Abstract: The present disclosure provides systems and methods that improve job posting structure and presentation by, for example, classifying portions of job postings into informative sections. As an example, given a job posting, a computing system implementing aspects of the present disclosure can separate the job posting into multiple portions. After separation into portions, the computing system can classify each portion into the most plausible job-posting-specific section. For example, the computing system can include and implement a machine-learned classification model to classify the portions into the sections. Following classification, the computing system can modify the job posting based on the classification of the portions. In particular, the structure and/or presentation of the job posting can be improved based on the classification of the portions into the sections.
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