公开(公告)号：US20220261555A1

公开(公告)日：2022-08-18

申请号：US17177372

申请日：2021-02-17

Applicant: ADOBE INC.

Inventor： Logan Lebanoff ,  Franck Dernoncourt ,  Doo Soon Kim ,  Lidan Wang ,  Walter Chang

IPC: G06F40/40 ,  G06F40/284 ,  G06F40/166 ,  G06N3/04 ,  G06N3/08

Abstract: Systems and methods for sentence fusion are described. Embodiments receive coreference information for a first sentence and a second sentence, wherein the coreference information identifies entities associated with both a term of the first sentence and a term of the second sentence, apply an entity constraint to an attention head of a sentence fusion network, wherein the entity constraint limits attention weights of the attention head to terms that correspond to a same entity of the coreference information, and predict a fused sentence using the sentence fusion network based on the entity constraint, wherein the fused sentence combines information from the first sentence and the second sentence.

公开(公告)号：US20220138185A1

公开(公告)日：2022-05-05

申请号：US17087943

申请日：2020-11-03

Applicant: Adobe Inc.

Inventor： Quan Tran ,  Zhe Lin ,  Xuanli He ,  Walter Chang ,  Trung Bui ,  Franck Dernoncourt

IPC: G06F16/242 ,  G06F40/56 ,  G06N3/08 ,  G06N3/04

Abstract: Systems and methods for natural language processing are described. Embodiments are configured to receive a structured representation of a search query, wherein the structured representation comprises a plurality of nodes and at least one edge connecting two of the nodes, receive a modification expression for the search query, wherein the modification expression comprises a natural language expression, generate a modified structured representation based on the structured representation and the modification expression using a neural network configured to combine structured representation features and natural language expression features, and perform a search based on the modified structured representation.

公开(公告)号：US11232255B2

公开(公告)日：2022-01-25

申请号：US16007632

申请日：2018-06-13

Applicant: Adobe Inc.

Inventor： Franck Dernoncourt ,  Walter Chang ,  Trung Bui ,  Sean Fitzgerald ,  Sasha Spala ,  Kishore Aradhya ,  Carl Dockhorn

IPC: G06F40/169

Abstract: Systems, methods, and non-transitory computer-readable media are disclosed that collect and analyze annotation performance data to generate digital annotations for evaluating and training automatic electronic document annotation models. In particular, in one or more embodiments, the disclosed systems provide electronic documents to annotators based on annotator topic preferences. The disclosed systems then identify digital annotations and annotation performance data such as a time period spent by an annotator in generating digital annotations and annotator responses to digital annotation questions. Furthermore, in one or more embodiments, the disclosed systems utilize the identified digital annotations and the annotation performance data to generate a final set of reliable digital annotations. Additionally, in one or more embodiments, the disclosed systems provide the final set of digital annotations for utilization in training a machine learning model to generate annotations for electronic documents.

公开(公告)号：US10817713B2

公开(公告)日：2020-10-27

申请号：US16192573

申请日：2018-11-15

Applicant: Adobe Inc.

Inventor： Trung Bui ,  Zhe Lin ,  Walter Chang ,  Nham Le ,  Franck Dernoncourt

IPC: G06K9/00 ,  G06N3/04 ,  G10L15/26 ,  G10L15/25

Abstract: The present disclosure relates to systems, methods, and non-transitory computer readable media for generating modified digital images based on verbal and/or gesture input by utilizing a natural language processing neural network and one or more computer vision neural networks. The disclosed systems can receive verbal input together with gesture input. The disclosed systems can further utilize a natural language processing neural network to generate a verbal command based on verbal input. The disclosed systems can select a particular computer vision neural network based on the verbal input and/or the gesture input. The disclosed systems can apply the selected computer vision neural network to identify pixels within a digital image that correspond to an object indicated by the verbal input and/or gesture input. Utilizing the identified pixels, the disclosed systems can generate a modified digital image by performing one or more editing actions indicated by the verbal input and/or gesture input.

公开(公告)号：US10372821B2

公开(公告)日：2019-08-06

申请号：US15462684

申请日：2017-03-17

Applicant: Adobe Inc.

Inventor： Walter Chang ,  Trung Bui ,  Pranjal Daga ,  Michael Kraley ,  Hung Bui

IPC: G06F17/22 ,  G06F17/27 ,  G06K9/00

Abstract: Certain embodiments identify a correct structured reading-order sequence of text segments extracted from a file. A probabilistic language model is generated from a large text corpus to comprise observed word sequence patterns for a given language. The language model measures whether splicing together a first text segment with another continuation text segment results in a phrase that is more likely than a phrase resulting from splicing together the first text segment with other continuation text segments. Sets of text segments, which include a first set with a first text segment and a first continuation text segment as well as a second set with the first text segment and a second continuation text segment, are provided to the probabilistic model. A score indicative of a likelihood of the set providing a correct structured reading-order sequence is obtained for each set of text segments.

公开(公告)号：US11544456B2

公开(公告)日：2023-01-03

申请号：US16810345

申请日：2020-03-05

Applicant: ADOBE INC.

Inventor： Khalil Mrini ,  Walter Chang ,  Trung Bui ,  Quan Tran ,  Franck Dernoncourt

IPC: G06F40/211 ,  G06N3/04 ,  G06N3/08

Abstract: Systems and methods for parsing natural language sentences using an artificial neural network (ANN) are described. Embodiments of the described systems and methods may generate a plurality of word representation matrices for an input sentence, wherein each of the word representation matrices is based on an input matrix of word vectors, a query vector, a matrix of key vectors, and a matrix of value vectors, and wherein a number of the word representation matrices is based on a number of syntactic categories, compress each of the plurality of word representation matrices to produce a plurality of compressed word representation matrices, concatenate the plurality of compressed word representation matrices to produce an output matrix of word vectors, and identify at least one word from the input sentence corresponding to a syntactic category based on the output matrix of word vectors.

公开(公告)号：US11080295B2

公开(公告)日：2021-08-03

申请号：US14538393

申请日：2014-11-11

Applicant: Adobe Inc.

Inventor： Walter Chang ,  Nicholas Digiuseppe

IPC: G06F16/25 ,  G06F16/11 ,  G06F16/33 ,  G06F16/2457 ,  G06F16/9032 ,  G06F16/242 ,  G06F16/901 ,  G06F40/30

Abstract: Techniques for organizing knowledge about a dataset storing data from or about multiple sources may be provided. For example, the data can be accessed from the multiple sources and categorized based on the data type. For each data type, a triple extraction technique specific to that data type may be invoked. One set of techniques can allow the extraction of triples from the data based on natural language-based rules. Another set of techniques can allow a similar extraction based on logical or structural-based rules. A triple may store a relationship between elements of the data. The extracted triples can be stored with corresponding identifiers in a list. Further, dictionaries storing associations between elements of the data and the triples can be updated. The list and the dictionaries can be used to return triples in response to a query that specifies one or more elements.

公开(公告)号：US10296924B2

公开(公告)日：2019-05-21

申请号：US14445999

申请日：2014-07-29

Applicant: ADOBE INC.

Inventor： Sachin Soni ,  Ashish Duggal ,  Sanjeev Tagra ,  Vineet Sharma ,  Anmol Dhawan ,  Walter Chang

IPC: G06Q30/02

Abstract: A computer-implemented method for providing performance indicators of destination documents includes identifying a referral document to a destination document, where the referral document comprising a source of at least one visitor to the destination document. The method also includes extracting referral keywords from content of the referral document, the referral keywords corresponding to a referral context of the referral document. The method further includes determining a degree of correlation between the referral document and the destination document based on a comparison between the referral keywords and destination keywords, the destination keywords corresponding to destination context of the destination document. Additionally, the method includes providing one or more performance indicators to a user based on the correlation between the referral document and the destination document, where the one or more performance indicators correspond to a performance metric that quantifies interactions between visitors and the destination document.

公开(公告)号：US10235681B2

公开(公告)日：2019-03-19

申请号：US14054318

申请日：2013-10-15

Applicant: Adobe Inc.

Inventor： Walter Chang ,  Chris Chen ,  Shone Sadler ,  David Jared

IPC: G06Q30/02 ,  G06F17/27

Abstract: A contextual analysis engine systematically extracts, analyzes and organizes digital content stored in an electronic file such as a webpage. Content can be extracted using a text extraction module which is capable of separating the content which is to be analyzed from less meaningful content such as format specifications and programming scripts. The resulting unstructured corpus of plain text can then be passed to a text analytics module capable of generating a structured categorization of topics included within the content. This structured categorization can be organized based on a content topic ontology which may have been previously defined or which may be developed in real-time. The systems disclosed herein optionally include an input/output interface capable of managing workflows of the text extraction module and the text analytics module, administering a cache of previously generated results, and interfacing with other applications that leverage the disclosed contextual analysis services.

公开(公告)号：US12147771B2

公开(公告)日：2024-11-19

申请号：US17361878

申请日：2021-06-29

Applicant: ADOBE INC.

Inventor： Sangwoo Cho ,  Franck Dernoncourt ,  Timothy Jeewun Ganter ,  Trung Huu Bui ,  Nedim Lipka ,  Varun Manjunatha ,  Walter Chang ,  Hailin Jin ,  Jonathan Brandt

IPC: G06F40/35 ,  G06F40/279

Abstract: System and methods for a text summarization system are described. In one example, a text summarization system receives an input utterance and determines whether the utterance should be included in a summary of the text. The text summarization system includes an embedding network, a convolution network, an encoding component, and a summary component. The embedding network generates a semantic embedding of an utterance. The convolution network generates a plurality of feature vectors based on the semantic embedding. The encoding component identifies a plurality of latent codes respectively corresponding to the plurality of feature vectors. The summary component identifies a prominent code among the latent codes and to select the utterance as a summary utterance based on the prominent code.