Articles (2) Patents (4)
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
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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: China
Grant Date: June 21, 2024
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: 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
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Canran Xu