公开(公告)号：US20230289854A1

公开(公告)日：2023-09-14

申请号：US17692934

申请日：2022-03-11

申请人： TREDENCE INC.

发明人： Ankush Chopra ,  Aravind Chandramouli ,  Ashutosh Rajesh Kothiwala ,  Shiven Purohit ,  Siddharth Shukla ,  Shubham Pandey ,  Soumendra Mohanty

IPC分类号： G06Q30/02 ,  G06F40/30 ,  G06F40/289 ,  G06F40/253

CPC分类号： G06Q30/0282 ,  G06F40/30 ,  G06F40/289 ,  G06F40/253

摘要： An analytics system receives, from a client computing device, a request to generate a presentation. The analytics system accesses one or more feedback datasets of feedback data. The feedback data comprises unstructured data available from multiple data stores. The analytics system generates, for each feedback dataset, a respective feedback text and a respective sentiment score indicating a degree of negativity associated with the respective feedback text. For a combination of a plurality of generated feedback texts, the analytics system selects a set of themes based at least on a plurality of generated sentiment scores. Each sentiment score of the plurality of generated sentiment scores is associated with one of the plurality of generated feedback texts. The analytics system generates a presentation file that indicates the set of themes. The analytics system causes the presentation file to be transmitted to the client computing device.

公开(公告)号：US11755831B2

公开(公告)日：2023-09-12

申请号：US17061989

申请日：2020-10-02

申请人： Telia Company AB

发明人： Aleksanteri Vuoristo

IPC分类号： G06F40/205 ,  G06F40/289 ,  G06Q30/016 ,  H04L51/04 ,  G06F16/31 ,  G06F16/33 ,  G06F16/35

CPC分类号： G06F40/205 ,  G06F16/316 ,  G06F16/3347 ,  G06F16/355 ,  G06F40/289 ,  G06Q30/016 ,  H04L51/04

摘要： The present invention relates to a method for performing a detection of a topic of a message introduced in a real-time customer service messaging platform. In the method a message comprising at least one word from which the topic is definable is received; a topic from the received message is extracted; it is inquired from a database if the topic is determinable from a number of messages received chronically earlier than the received message; and an indication is generated to an operator of the real-time customer service messaging platform in accordance with a detection result obtained through an inquiry to the database. Some aspects of the present invention relate to a network node, to a computer program product and to a system.

公开(公告)号：US20230281393A1

公开(公告)日：2023-09-07

申请号：US17978443

申请日：2022-11-01

申请人： Tata Consultancy Services Limited

发明人： Nidhi Harshad Shroff ,  Paras Dwivedi ,  Siva Prasad Pusarla ,  Sudhakara Deva Poojary ,  Pranav Champaklal Shah ,  Varsha Nayak ,  Amit Aggrawal ,  Godfrey Claudin Mathais

IPC分类号： G06F40/30 ,  G06F40/284 ,  G06F40/289 ,  G06F40/211

CPC分类号： G06F40/30 ,  G06F40/284 ,  G06F40/289 ,  G06F40/211

摘要： This disclosure relates to systems and methods for multi-utterance generation of data. Conventionally, the process of utterance generation involves manual efforts and for the utterances to be contextually relevant, identification of subject area is also required. Conventional approaches for utterance generation work with a blackbox approach taking in data and giving augmented utterances. However, these approaches fail to provide any control over quality of utterances generated. The method of the present disclosure addresses unresolved problems of multi-utterance generation with a control over quality of utterances generated. Embodiments of the present disclosure utilizes a smart framework that is capable of generating contextually relevant utterances with immutability regulation and punctuation-memory. More Specifically, the present disclosure generates multiple syntactically and semantically correct utterances for text input data in such a way that a provision to selectively maintain or regulate phrases or words intact is provided and punctuation consistency is maintained.

公开(公告)号：US20230274095A1

公开(公告)日：2023-08-31

申请号：US17570281

申请日：2022-01-06

申请人： Gotlt! Inc.

发明人： Amol Kelkar ,  Nikhil Varghese ,  Chandra Khatri ,  Utkarsh Mittal ,  Nachiketa Rajpurohit ,  Peter Relan ,  Hung Tran

IPC分类号： G06F40/49 ,  G06F40/289 ,  G06F40/247 ,  H04M3/527

CPC分类号： G06F40/49 ,  G06F40/247 ,  G06F40/289 ,  H04M3/527

摘要： Described herein is an Autonomous Conversational AI system, which does not require any human configuration or annotation, and is used to have multi-tum dialogs with a user. A typical Conversational AI system consists of three main models: Natural Language Understanding (NLU), Dialog Manager (DM) and Natural Language Generation (NLG), which requires human provided data and configuration. The system proposed herein leverages novel Conversational AI methods which automatically generates conversational AI configuration from any historical conversation logs. The automatically generated configuration contains Auto-Topics, Auto-Subtopics, Auto-Intents, Auto-Responses and Auto-Flows which are used to automatically train NLU, DM and NLG models. Once these models are trained for given conversation logs, the system can be used to have dialog with any user.

公开(公告)号：US11741052B2

公开(公告)日：2023-08-29

申请号：US17650720

申请日：2022-02-11

申请人： Vijay Madisetti

发明人： Vijay Madisetti ,  Arshdeep Bahga

IPC分类号： G06F16/176 ,  G06F40/289 ,  G06F16/18 ,  G06F16/182 ,  G06F40/169

CPC分类号： G06F16/176 ,  G06F16/182 ,  G06F16/1815 ,  G06F40/169 ,  G06F40/289

摘要： A method of collaborating in real-time via action creation, including detecting an annotation on a managed document, parsing the annotation, generating an action record responsive to information identified from parsing the annotation, and recording a generated action record to an action database. A user can access the action database and retrieve action records for which they are the assigned user. The annotation does not change the file content of the managed document.

公开(公告)号：US11734511B1

公开(公告)日：2023-08-22

申请号：US16946840

申请日：2020-07-08

申请人： Mineral Earth Sciences LLC

发明人： Nanzhu Wang ,  Gaoxiang Chen ,  Yueqi Li

IPC分类号： G06F40/289 ,  G06N3/044

CPC分类号： G06F40/289 ,  G06N3/044

摘要： Techniques are disclosed that enable generating a unified data set by mapping a set of item description phrases, describing entries in a data set, to a set of canonical phrases. Various implementations include generating a similarity measure between each item description phrase and each canonical phrase by processing the corresponding item description phrase and the corresponding canonical phrase using a natural language processing model. Additional or alternative implementations include generating a bipartite graph based on the set of item description phrases, the set of canonical phrases, and the similarity measures. The mapping can be generated based on the bipartite graph.

公开(公告)号：US20230259711A1

公开(公告)日：2023-08-17

申请号：US17669484

申请日：2022-02-11

申请人： International Business Machines Corporation

发明人： Takuya Goto ,  Yoshiroh Kamiyama

IPC分类号： G06F40/30 ,  G06F40/242 ,  G06F40/289 ,  G06F40/117

CPC分类号： G06F40/30 ,  G06F40/242 ,  G06F40/289 ,  G06F40/117

摘要： Described are techniques for topic modeling including a computer-implemented method of generating a plurality of topic labels corresponding to a plurality of documents clustered into a plurality of topics, where the plurality of topic labels include a sentiment-oriented topic label and a sentiment-neutral topic label. The method further comprises calculating term frequency-inverse document frequency (TF-IDF) values for respective topic labels and corresponding pluralities of documents. The method further comprises receiving a selected sentiment polarity from a user device. The method further comprises identifying a subset of the plurality of topic labels that satisfy the selected sentiment polarity. The method further comprises transmitting at least one topic label of the subset of the plurality of topic labels to the user device, where the at least one topic label has a higher TF-IDF value than other topic labels in the subset of the plurality of topic labels.

公开(公告)号：US11720760B2

公开(公告)日：2023-08-08

申请号：US16652490

申请日：2019-05-02

申请人： AbbType Ltd

发明人： Huben Stefanov Stefanov ,  Huben Zlatkov Stefanov

IPC分类号： G06F40/44 ,  G06F40/56 ,  G06F40/289

CPC分类号： G06F40/44 ,  G06F40/289 ,  G06F40/56

摘要： The invention provides a computer implemented method of drafting of abbreviations for the statistically most frequent word forms and phrases for the purposes of computer typing and compression of texts written in languages using alphabetic scripts with full vowel representation. Therein, drafted abbreviations do not constitute meaningful word forms of a given language, for which they are drafted. Every abbreviated word form or phrase is attributed only one unique and exclusive abbreviation, which is based on the letters contained in this abbreviated word form or phrase and in accordance with the order, in which these letters appear in the abbreviated word form or phrase. For a given word form, one-letter, two-letter, three-letter and four-letter abbreviations of the word forms are chosen according to the statistical frequency of the word forms in a way that allows the mathematically most efficient process of abbreviation of the text.

公开(公告)号：US20230244879A1

公开(公告)日：2023-08-03

申请号：US17923316

申请日：2021-07-23

申请人： Beijing Bytedance Network Technology Co., Ltd.

发明人： Xinsong ZHANG ,  Pengshuai LI ,  Hang LI

IPC分类号： G06F40/40 ,  G06F40/30 ,  G06F40/205 ,  G06F40/289

CPC分类号： G06F40/40 ,  G06F40/30 ,  G06F40/205 ,  G06F40/289

摘要： Disclosed are a language representation model system, a language representation model pre-training method, a natural language processing method, an electronic device, and a storage medium. The language representation model system includes: a word granularity language representation sub-model based on segmentation in units of words, and a phrase granularity language representation sub-model based on segmentation in units of words. The word granularity language representation sub-model is configured to output, based on a sentence segmented in units of words, a first semantic vector corresponding to a semantic expressed by each segmented word in the sentence. The phrase granularity language representation sub-model is configured to output, based on the sentence segmented in units of phrases, a second semantic vector corresponding to a semantic expressed by each segmented phrase in the sentence.

公开(公告)号：US20230244871A1

公开(公告)日：2023-08-03

申请号：US17589860

申请日：2022-01-31

申请人： Walmart Apollo, LLC

发明人： Deepa Mohan ,  Komal Arvind Dhuri ,  Simral Chaudhary ,  Jorge Adrian Sanchez Castro

IPC分类号： G06F40/289 ,  G06K9/62

CPC分类号： G06F40/289 ,  G06K9/628 ,  G06N20/00

摘要： A method implemented via execution of computing instructions configured to run at one or more processors and stored at one or more non-transitory computer-readable media. The method can include generating training data for an intent classification machine learning model by: (a) determining, via a text-to-text machine learning model, one or more respective paraphrases for each sample phrase of training phrases; (b) generating, via a label generating machine learning model, labeled data based on unlabeled live logs by: (i) determining live-log samples from the unlabeled live logs based at least in part on: a respective timestamp of each live log of the unlabeled live logs, or random sampling; and (ii) generating, via the label generating machine learning model, the labeled data based on the live-log samples and one or more labeling functions; and (c) adding the one or more respective paraphrases for the each sample phrase of the training phrases and the labeled data to the training data. In certain embodiments, a respective quantity of the one or more respective paraphrases can vary for the each sample phrase of the training phrases. In some embodiments, the method further can include transmitting the training data, as generated, to the intent classification machine learning model for training. Other embodiments are described.