Articles (2) Patents (3)
Knowledge Graphs in Research

Relation Embedding with Dihedral Group in Knowledge Graph

eBay researchers recently published a paper about a method for KG relation embedding using dihedral group. Experimental results on benchmark KGs show that the model outperforms existing bilinear form models and even deep learning methods.

By: Canran Xu and Ruijiang Li
Deep Learning in Research

Explainable Reasoning over Knowledge Graphs for Recommendation

Incorporating knowledge graphs into recommender systems has attracted increasing attention in recent years. By exploring the interlinks within a knowledge graph, the connectivity between users and items can be discovered as paths, which provide rich and complementary information to user-item interactions. Such connectivity not only reveals the semantics of entities and relations, but also helps to comprehend a user’s interest. However, existing efforts have not fully explored this connectivity to infer user preferences, especially in terms of modeling the sequential dependencies within and holistic semantics of a path. We have developed a new model named Knowledge-aware Path Recurrent Network (KPRN) to exploit knowledge graphs for recommendation.

By: Dingxian Wang, Canran Xu, Hua Yang and Xiaoyuan Wu

Abstract:

Disclosed are systems and methods for receiving a plurality of comments at a particular phase of a transaction with a member of a networked system, classifying one or more of the plurality of comments into one of a set of predetermined sentiment classifications, applying a trained machine learning system to select a category from a set of predefined categories for each of the one or more comments, applying a natural language processing module to generate a sub-category for each of the one or more comments, associating the generated sub-categories with their respective categories for the one or more comments, and generating a display of the determined categories for the particular transaction with the generated sub-categories, each generated sub-category being graphically connected to their respective categories.

Country: United States
Grant Date: December 26, 2023
INVENTORS: Jason Diran, Michelle Foster, Sanjika Hewavitharana, Brandon Lai, Janaka Ranatunga, Canran Xu

Abstract:

Disclosed are systems and methods for receiving a plurality of comments at a particular phase of a transaction with a member of a networked system, classifying one or more of the plurality of comments into one of a set of predetermined sentiment classifications, applying a trained machine learning system to select a category from a set of predefined categories for each of the one or more comments, applying a natural language processing module to generate a sub-category for each of the one or more comments, associating the generated sub-categories with their respective categories for the one or more comments, and generating a display of the determined categories for the particular transaction with the generated sub-categories, each generated sub-category being graphically connected to their respective categories.

Country: Republic of Korea
Grant Date: October 25, 2022
INVENTORS: Jason Diran, Michelle Foster, Sanjika Hewavitharana, Brandon Lai, Janaka Ranatunga, Canran Xu

Abstract:

Disclosed are systems and methods for receiving a plurality of comments at a particular phase of a transaction with a member of a networked system, classifying one or more of the plurality of comments into one of a set of predetermined sentiment classifications, applying a trained machine learning system to select a category from a set of predefined categories for each of the one or more comments, applying a natural language processing module to generate a sub-category for each of the one or more comments, associating the generated sub-categories with their respective categories for the one or more comments, and generating a display of the determined categories for the particular transaction with the generated sub-categories, each generated sub-category being graphically connected to their respective categories.

Country: United States
Grant Date: April 27, 2021
INVENTORS: Jason Diran, Michelle Foster, Sanjika Hewavitharana, Brandon Lai, Janaka Ranatunga, Canran Xu
View Archive

Canran Xu