Patents by Inventor Na Cheng
Na Cheng has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).
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Publication number: 20250166060Abstract: In some embodiments, a method stores a total number of generative credits for a generative artificial intelligence (AI) solution that is integrated with a software application in a database system. Usage data is tracked for a request to the generative artificial intelligence (AI) solution in the database system. The method determines a context from the usage data and retrieves a contextual pricing model for the generative AI solution using the context. The contextual pricing model translates a model specific charging policy to generative credits. The method applies the usage data to the contextual pricing model to translate the usage data to a number of generative credits. The number of generative credits for the generative AI solution is applied to an available number of generative credits of the total number of generative credits to generate a new available number of generative credits.Type: ApplicationFiled: November 20, 2023Publication date: May 22, 2025Applicant: Salesforce, Inc.Inventors: Oleksandr Minaiev, Fermin Ordaz, Khoa Le, Na Cheng
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Patent number: 12292906Abstract: Embodiments described herein provide systems and methods for document recommendation. A system receives a set of training data including a plurality of documents. The system determines whether the set of training data includes annotated contextual information corresponding to the plurality of documents. The system trains supervised and/or unsupervised models based on the availability of data. The models are used to generate vectors representing the documents. During a live text conversation, text from the conversation may be vectorized using the models and the vectors compared to those representing the documents in order to find the most relevant documents. The system may generate an indication of a recommended document.Type: GrantFiled: January 27, 2023Date of Patent: May 6, 2025Assignee: Salesforce, Inc.Inventors: Feifei Jiang, Aron Kale, Anuprit Kale, Sitaram Asur, Na Cheng, Zachary Alexander, Victor Yee, Fermin Ordaz
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Patent number: 12288032Abstract: Described herein are systems, apparatus, methods and computer program products for machine learning intent classification. In various embodiments, historical utterances provided by users may be utilized for bot training. Context and personally identifiable information may be removed from the utterances. The utterances may be associated with vectors. The utterances and vectors may be used to determine recommendations.Type: GrantFiled: October 31, 2023Date of Patent: April 29, 2025Assignee: Salesforce, Inc.Inventors: Anuprit Kale, Weiping Peng, Na Cheng, Rick Lindstrom, Zachary Alexander
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Publication number: 20240412059Abstract: Embodiments described herein provide A method for training a neural network based model. The methods include receiving a training dataset with a plurality of training samples, and those samples are encoded into representations in feature space. A positive sample is determined from the raining dataset based on a relationship between the given query and the positive sample in feature space. For a given query, a positive sample from the training dataset is selected based on a relationship between the given query and the positive sample in a feature space. One or more negative samples from the training dataset that are within a reconfigurable distance to the positive sample in the feature space are selected, and a loss is computed based on the positive sample and the one or more negative samples. The neural network is trained based on the loss.Type: ApplicationFiled: June 7, 2023Publication date: December 12, 2024Inventors: Regunathan Radhakrishnan, Zachary Alexander, Sitaram Asur, Shashank Harinath, Na Cheng, Shiva Kumar Pentyala
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Publication number: 20240256581Abstract: Embodiments described herein provide ______.Type: ApplicationFiled: January 27, 2023Publication date: August 1, 2024Inventors: Feifei Jiang, Aron Kale, Anuprit Kale, Sitaram Asur, Na Cheng, Zachary Alexander, Victor Yee, Fermin Ordaz
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Publication number: 20240242022Abstract: Embodiments described herein provide a structured conversation summarization framework. A user interface may be provided which allows an agent to perform a conversation with a customer, for example regarding resolving a customer support issue. Utterances by both the agent and customer may be stored, and at the end of the conversation, the utterances may be used to generate a structured summary. The structured summary may include components such as a general summary, an issue summary, and a resolution summary. Using neural network models and heuristics, each component of the summary may be automatically generated.Type: ApplicationFiled: January 18, 2023Publication date: July 18, 2024Inventors: Victor Yee, Chien-Sheng Wu, Na Cheng, Alexander R. Fabbri, Zachary Alexander, Nicholas Feinig, Sameer Abhinkar, Shashank Harinath, Sitaram Asur, Jacob Nathaniel Huffman, Wojciech Kryscinski, Caiming Xiong
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Patent number: 12019984Abstract: A method that includes receiving an input at an interactive conversation service that uses an intent classification model. The method may further include generating, using an encoder model of the intent classification model, a set of output vectors corresponding to the input, where the encoder model is configured to determine a set of metrics corresponding to intent classifications. The method may further include determining, using an outlier detection model of the intent classification model, whether the input is in-domain or out-of-domain (OOD) based on a first vector of the set of output vectors satisfying a domain threshold relative to one or more of the intent classifications. The method may further include outputting, by the intent classification model, a second vector of the set of output vectors that indicates the set of metrics corresponding to the intent classifications or an indication that the input is OOD.Type: GrantFiled: September 20, 2021Date of Patent: June 25, 2024Assignee: Salesforce, Inc.Inventors: Shilpa Bhagavath, Shubham Mehrotra, Abhishek Sharma, Shashank Harinath, Na Cheng, Zineb Laraki
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Patent number: 12001801Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for integrating question generation and answer retrieval in a question answer system. The system generates a question using a set of documents and determines whether it is semantically distinct from questions in a question-answer repository. After determining that the question is semantically distinct from questions in the question-answer repository, the system adds the question to the question-answer repository. Upon receipt of a user-submitted question, the system uses the question-answer repository to identify a semantically similar question. The system retrieves an answer corresponding to the identified question from the question-answer repository and provides the answer in response to the user-submitted question.Type: GrantFiled: November 15, 2019Date of Patent: June 4, 2024Assignee: Salesforce, Inc.Inventors: Yuanxin Wang, Anuprit Kale, Zachary Alexander, Na Cheng
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Publication number: 20240062010Abstract: Described herein are systems, apparatus, methods and computer program products for machine learning intent classification. In various embodiments, historical utterances provided by users may be utilized for bot training. Context and personally identifiable information may be removed from the utterances. The utterances may be associated with vectors. The utterances and vectors may be used to determine recommendations.Type: ApplicationFiled: October 31, 2023Publication date: February 22, 2024Applicant: Salesforce, Inc.Inventors: Anuprit KALE, Weiping PENG, Na CHENG, Rick LINDSTROM, Zachary ALEXANDER
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Publication number: 20240018452Abstract: An chip for integrated tumor cell behavior experiments, which comprises a functional area I, a functional area II, a functional area III, a functional area IV and a functional area V, wherein the functional area I comprises a cell invasion 3D co-culture plate (400) for cell invasion experiments; the functional area II comprises a cell migration culture hole (500) for cell migration experiments; the functional area III comprises a cell proliferation single-cell culture hole (600) for tumor single-cell culture; the functional area IV comprises an angiogenesis 3D co-culture plate (700) for tumor-related angiogenesis experiments; and the functional area V comprises a tumor single-cell culture hole (803), a matrix glue groove (805) and a tumor cell attraction factor hole (801) connected by matrix glue for tumor single-cell migration or invasion experiments.Type: ApplicationFiled: December 30, 2020Publication date: January 18, 2024Inventors: Zhiyuan LI, Rongqi HUANG, Shuai LI, Chao TIAN, Zuoxian LIN, Na CHENG
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Patent number: 11836450Abstract: Described herein are systems, apparatus, methods and computer program products for machine learning intent classification. In various embodiments, historical utterances provided by users may be utilized for bot training. Context and personally identifiable information may be removed from the utterances. The utterances may be associated with vectors. The utterances and vectors may be used to determine recommendations.Type: GrantFiled: November 16, 2020Date of Patent: December 5, 2023Assignee: Salesforce, Inc.Inventors: Anuprit Kale, Weiping Peng, Na Cheng, Rick Lindstrom, Zachary Alexander
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Patent number: 11790894Abstract: A system uses conversation engines to process natural language requests and conduct automatic conversations with users. The system generates responses to users in an online conversation. The system ranks generated user responses for the online conversation. The system generates a context vector based on a sequence of utterances of the conversation and generates response vectors for generated user responses. The system ranks the user responses based on a comparison of the context vectors and user response vectors. The system uses a machine learning based model that uses a pretrained neural network that supports multiple languages. The system determines a context of an utterance based on utterances in the conversation. The system generates responses and ranks them based on the context. The ranked responses are used to respond to the user.Type: GrantFiled: March 15, 2021Date of Patent: October 17, 2023Assignee: Salesforce, Inc.Inventors: Yixin Mao, Zachary Alexander, Victor Winslow Yee, Joseph R. Zeimen, Na Cheng, Chien-Sheng Wu, Wenhao Liu, Caiming Xiong
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Publication number: 20230086302Abstract: A method that includes receiving an input at an interactive conversation service that uses an intent classification model. The method may further include generating, using an encoder model of the intent classification model, a set of output vectors corresponding to the input, where the encoder model is configured to determine a set of metrics corresponding to intent classifications. The method may further include determining, using an outlier detection model of the intent classification model, whether the input is in-domain or out-of-domain (OOD) based on a first vector of the set of output vectors satisfying a domain threshold relative to one or more of the intent classifications. The method may further include outputting, by the intent classification model, a second vector of the set of output vectors that indicates the set of metrics corresponding to the intent classifications or an indication that the input is OOD.Type: ApplicationFiled: September 20, 2021Publication date: March 23, 2023Inventors: Shilpa Bhagavath, Shubham Mehrotra, Abhishek Sharma, Shashank Harinath, Na Cheng, Zineb Laraki
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Patent number: 11580179Abstract: A method and system for recommending articles including: receiving a customer request from the customer during the session; generating case data for a case, by an article recommender app; configuring a training set based on the subject and description data of the customer request; identifying, by an artificial intelligence (AI) app, a first pool of articles from a knowledge database; identifying by at least one query, a second pool of articles from a case article database to into a merged pool of articles; assigning, by the AI app, an implicit label to one of the first pool and the second pool of the articles; applying a model derived by the AI app based on customer behavior and a set of features related to the case to classify each article of the merged pool of articles based at least in part on the predicted relevance of the article.Type: GrantFiled: September 24, 2018Date of Patent: February 14, 2023Assignee: salesforce.com, inc.Inventors: Pingping Xiu, Sitaram Asur, Anjan Goswami, Ziwei Chen, Na Cheng, Suhas Satish, Jacob Nathaniel Huffman, Peter Francis White, WeiPing Peng, Aditya Sakhuja, Jayesh Govindarajan, Edgar Gerardo Velasco
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Patent number: 11544762Abstract: A system and related processing methodologies for recommending a product based on a work order are described. The system receives an input case description, including a current repair item and a current work type. Historical work orders associating a plurality of products with repair items and work types are searched for a co-occurrence of the repair item matching the current repair item, and the work type matching the current work type. Upon finding a match, the product associated with the match is added to a set of candidate products for the current work order. A similarity measure between the candidate product and current work order description, a current work type category, and popularity of the candidate product is generated and then used in the generation of a probability score for the candidate product and current work order. If the probability score meets a threshold, the candidate product is recommended.Type: GrantFiled: January 27, 2020Date of Patent: January 3, 2023Assignee: salesforce.com, inc.Inventors: Yixin Mao, Sitaram Asur, Na Cheng, Gary Brandeleer, Kavya Murali, Nicholas Beng Tek Geh
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Patent number: 11507617Abstract: Disclosed are some implementations of systems, apparatus, methods and computer program products for extracting topics from a corpus of exchanges. The system generates vector representations of utterances of an entity common to the exchanges and uses the vector representations to cluster the utterances. The system labels the clusters and uses the labeled clusters to generate an exchange label sequence for each of the exchanges, where each exchange label sequence corresponds to a sequence of utterances generated by the entity. The system processes the exchange label sequences to generate one or more subsets of the utterances, where each of the subsets corresponds to a particular topic.Type: GrantFiled: November 15, 2019Date of Patent: November 22, 2022Assignee: Salesforce, Inc.Inventors: Zachary Alexander, Na Cheng
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Publication number: 20220318669Abstract: A computing system may receive a corpus of training data including a plurality of data entity schemas. A first data entity of a first set of data entities corresponding to a first data entity schema is associated with a topic characteristic based on a first set of attributes defined by the first data entity schema, and a first attribute of the first set of attributes is associated with a structural characteristic that is common across each of the first set of data entities. The system may identify a respective attribute type identifier for each attribute of the first set, generate an attribute embedding for each attribute using the attribute value and the identifier, generate an entity embedding based on each attribute embedding and parameterize the topic characteristic for each data entity and the structural characteristic for each attribute.Type: ApplicationFiled: April 1, 2021Publication date: October 6, 2022Inventors: Zachary Alexander, Na Cheng, Jayesh Govindarajan
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Publication number: 20220293094Abstract: A system uses conversation engines to process natural language requests and conduct automatic conversations with users. The system generates responses to users in an online conversation. The system ranks generated user responses for the online conversation. The system generates a context vector based on a sequence of utterances of the conversation and generates response vectors for generated user responses. The system ranks the user responses based on a comparison of the context vectors and user response vectors. The system uses a machine learning based model that uses a pretrained neural network that supports multiple languages. The system determines a context of an utterance based on utterances in the conversation. The system generates responses and ranks them based on the context. The ranked responses are used to respond to the user.Type: ApplicationFiled: March 15, 2021Publication date: September 15, 2022Inventors: Yixin Mao, Zachary Alexander, Victor Winslow Yee, Joseph R. Zeimen, Na Cheng, Chien-Sheng Wu, Wenhao Liu, Caiming Xiong
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Patent number: 11392828Abstract: A system is provided for a machine learning engine using clustered case objects in a case management system. The system includes a multi-layer neural network. The system is configured to receive case object data comprising a case object and contextual objects in the case management system associated with the case object, the contextual objects comprising word vectors, generate a context embedding for the case object using the word vectors for the contextual objects, and cluster the case object with other case objects in the case management system based on the context embedding for the case object and other context embeddings for the other case objects.Type: GrantFiled: September 24, 2018Date of Patent: July 19, 2022Assignee: salesforce.com, inc.Inventors: Edgar Gerardo Velasco, Jayesh Govindarajan, Zachary Alexander, Na Cheng, Anuprit Kale, Peter White
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Patent number: 11379671Abstract: A system is configured to analyze a corpus of historical chat data to identify the list of “best” responses. As such, the user is not required to identify a list of canned responses for input into the system. The described system uses a context word embedding function and response word embedding function to generate context vectors and response vectors corresponding to the corpus of conversation data, and the vectors are represented by a respective context matrix and a response matrix. The system processes these matrices to generate scores for responses, clusters the responses, and identifies the responses corresponding to the best scores for each cluster.Type: GrantFiled: November 18, 2019Date of Patent: July 5, 2022Assignee: Salesforce, Inc.Inventors: Zachary Alexander, Edgar Gerardo Velasco, Victor Winslow Yee, Na Cheng, Khoa Le