DOCUMENT OPTICAL CHARACTER RECOGNITION
    1.
    发明公开

    公开(公告)号:US20240127302A1

    公开(公告)日:2024-04-18

    申请号:US18392629

    申请日:2023-12-21

    Applicant: eBay Inc.

    Abstract: Vehicles and other items often have corresponding documentation, such as registration cards, that includes a significant amount of informative textual information that can be used in identifying the item. Traditional OCR may be unsuccessful when dealing with non-cooperative images. Accordingly, features such as dewarping, text alignment, and line identification and removal may aid in OCR of non-cooperative images. Dewarping involves determining curvature of a document depicted in an image and processing the image to dewarp the image of the document to make it more accurately conform to the ideal of a cooperative image. Text alignment involves determining an actual alignment of depicted text, even when the depicted text is not aligned with depicted visual cues. Line identification and removal involves identifying portions of the image that depict lines and removing those lines prior to OCR processing of the image.

    Document optical character recognition

    公开(公告)号:US10068132B2

    公开(公告)日:2018-09-04

    申请号:US15164594

    申请日:2016-05-25

    Applicant: eBay Inc.

    Abstract: Vehicles and other items often have corresponding documentation, such as registration cards, that includes a significant amount of informative textual information that can be used in identifying the item. Traditional OCR may be unsuccessful when dealing with non-cooperative images. Accordingly, features such as dewarping, text alignment, and line identification and removal may aid in OCR of non-cooperative images. Dewarping involves determining curvature of a document depicted in an image and processing the image to dewarp the image of the document to make it more accurately conform to the ideal of a cooperative image. Text alignment involves determining an actual alignment of depicted text, even when the depicted text is not aligned with depicted visual cues. Line identification and removal involves identifying portions of the image that depict lines and removing those lines prior to OCR processing of the image.

    GENERATING NEXT USER PROMPTS IN AN INTELLIGENT ONLINE PERSONAL ASSISTANT MULTI-TURN DIALOG

    公开(公告)号:US20180052885A1

    公开(公告)日:2018-02-22

    申请号:US15238660

    申请日:2016-08-16

    Applicant: eBay Inc.

    Abstract: Systems and methods for generating prompts for further data from a user in a multi-turn interactive dialog. Embodiments improve searches for the most relevant items available for purchase in an electronic marketplace via a processed sequence of user inputs and machine-generated prompts. Question type prompts, validating statement type prompts, and recommendation type prompts may be selectively generated based on whether a user query has been sufficiently specified, user intent is ambiguous, or a search mission has changed. Detection of a new dominant object denotes search mission change. Contextual associations between prompts and user replies are maintained, but a search mission change results in previous context data being disregarded. Prompts can be directed to unspecified knowledge graph dimensions based on data element association strength values, relative data element positions and depths in the knowledge graph, and generated following a predetermined order of data element knowledge graph dimension types.

    Selecting next user prompt types in an intelligent online personal assistant multi-turn dialog

    公开(公告)号:US12020174B2

    公开(公告)日:2024-06-25

    申请号:US15238666

    申请日:2016-08-16

    Applicant: eBay Inc.

    CPC classification number: G06N5/04 G06F16/3344 G06N5/02

    Abstract: Systems and methods for selecting types of generated prompts for further data from a user in a multi-turn interactive dialog. In one scenario, a processed sequence of user inputs and machine-generated prompts improves searches for the most relevant items available for purchase in an electronic marketplace. The number of prompts may be limited to a predetermined maximum value. Prompt generation is minimized by incorporating into a knowledge graph world knowledge that helps user intent inference. Prompt generation may be suppressed if a search indicates the reply to a prompt will not lead to any satisfactory search results. Prompts can provide suggestions for available search results that either meet all query constraints, or meet only some query constraints if a search indicates no search results are available that meet all query constraints. Prompts can provide suggested incisive reply phrasing likely to improve search results through an affirmation or negation reply.

    SELECTING NEXT USER PROMPT TYPES IN AN INTELLIGENT ONLINE PERSONAL ASSISTANT MULTI-TURN DIALOG

    公开(公告)号:US20180052913A1

    公开(公告)日:2018-02-22

    申请号:US15238666

    申请日:2016-08-16

    Applicant: eBay Inc.

    CPC classification number: G06F16/3344 G06F16/338 G06N5/02

    Abstract: Systems and methods for selecting types of generated prompts for further data from a user in a multi-turn interactive dialog. In one scenario, a processed sequence of user inputs and machine-generated prompts improves searches for the most relevant items available for purchase in an electronic marketplace. The number of prompts may be limited to a predetermined maximum value. Prompt generation is minimized by incorporating into a knowledge graph world knowledge that helps user intent inference. Prompt generation may be suppressed if a search indicates the reply to a prompt will not lead to any satisfactory search results. Prompts can provide suggestions for available search results that either meet all query constraints, or meet only some query constraints if a search indicates no search results are available that meet all query constraints. Prompts can provide suggested incisive reply phrasing likely to improve search results through an affirmation or negation reply.

    DOCUMENT OPTICAL CHARACTER RECOGNITION
    7.
    发明申请

    公开(公告)号:US20170344821A1

    公开(公告)日:2017-11-30

    申请号:US15164594

    申请日:2016-05-25

    Applicant: eBay Inc.

    Abstract: Vehicles and other items often have corresponding documentation, such as registration cards, that includes a significant amount of informative textual information that can be used in identifying the item. Traditional OCR may be unsuccessful when dealing with non-cooperative images. Accordingly, features such as dewarping, text alignment, and line identification and removal may aid in OCR of non-cooperative images. Dewarping involves determining curvature of a document depicted in an image and processing the image to dewarp the image of the document to make it more accurately conform to the ideal of a cooperative image. Text alignment involves determining an actual alignment of depicted text, even when the depicted text is not aligned with depicted visual cues. Line identification and removal involves identifying portions of the image that depict lines and removing those lines prior to OCR processing of the image.

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