Jd.com American Technologies Corporation

Beijing Jingdong Shangke Information Technology Co., Ltd.

Beijing Wodong Tianjun Information Technology Co., Ltd.

Li Chen

Hui Zhou

Shizhu Liu

Shanglin Yang

Huasong Shan

Jianxun Sun

Kailin Huang

Ning Xu

Huiman Hou

Jixing Wang

Yingqiu Tian

Yang Tao

Chengchong Zhang

A system for assessing text content of a product. The system includes a computing device having a processor and a storage device storing computer executable code. The computer executable code, when executed at the processor, is configured to: provide text contents and confounding features of products; train a first regression model using the text content and the confounding features of the products; train the second regression model using the confounding features; operate the first regression model using the text contents and the confounding features to obtain a total loss; operate the second regression model using the confounding features of to obtain a partial loss; subtract the total loss from the partial loss to obtain a residual loss; use the residual loss to evaluate models and parameters for the regression models; and use the first regression model to obtain log odds of the words indicating importance of the words.

System and method for quality assessment of product description

A system and a method for obtaining a content plan are provided. The system includes a computing device configured to: provide a tag for each clause of each sentence of each product description of each of a category of products, where the tags include introductive tags corresponding to attributions of the products and description tags corresponding to descriptions of the products; determine tag exclusiveness, tag similarity, tag distance, and tag causality between the tags; generate candidate tag sequences the product descriptions; and filter the candidate tag sequences using the tag exclusiveness, the tag similarity, the tag distance and the tag causality to obtain the content plan.

System and method for automatic generation of knowledge-powered content planning

A system and a method for multimedia data analysis. The system includes a computing device. The computer device includes a processor and a storage device storing computer executable code. The computer executable code, when executed at the processor, is configured to: encode task description and task meta info into concatenated task vectors; encode context text and context meta info into concatenated context text vectors; encode context image and the context meta info into concatenated context image vectors; perform dual coattention on the concatenated task vectors and the concatenated context text and image vectors to obtain attended task vectors and attended context vectors; perform BiLSTM on the attended task vectors and the attended context vectors to obtain task encoding and context encoding; and decode the task encoding and the context encoding to obtain an answer to the task.

System and method for semantic analysis of multimedia data using attention-based fusion network

A method and system for constructing an evolving ontology database. The method includes: receiving a plurality of data entries; calculating semantic similarity scores between any two of the data entries; clustering the data entries into a multiple current themes based on the semantic similarity scores; selecting, new concepts from the current themes by comparing the current themes with a plurality of previous themes prepared using previous data entries; and updating the evolving ontology database using the new concepts. The semantic score between any two of the data entries are calculated by: semantic similarity score=&#x3a0;se, where sis weight of features sources, fis a feature similarity between the two of the data entries, wis a weight of f, and j, k and n are positive integers.

System and method for building an evolving ontology from user-generated content

A method and system for monitoring an e-commerce platform using artificial intelligence and fixing malfunctions on the e-commerce platform. The method includes: receiving, by a computing device, a feedback submitted by a user through the e-commerce platform; generating a vector based on content of the feedback, context of the feedback and profile of the user using AI processors; and classifying the vector to determine function corresponding to the feedback and status of the function using AI classifiers. The content includes text, voice, image and video; the context includes time, location and submission channel of the feedback; the profile includes attributes, history and preference of the user. Dimensions of the vector respectively corresponding to the text, voice, image, video, time, location, submission channel, attributes, history, and preference of the user.

System and method for monitoring online retail platform using artificial intelligence and fixing malfunction

A method and system for generating an article of a product. The method includes: receiving a request from a user; when the request include an identification of the product, retrieving traits of the product from a trait database, when the request include keywords, retrieving the traits of the product by comparing the similarity between the keywords and the traits or the synonym of the traits; generating candidate sentences corresponding to the traits; selecting sentences from the candidate sentences, and revising and rearranging the sentences to generate the article.

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Mountain View, CA, United States of America

Li Chen