Social Influence-based Attentive Mavens Mining and Aggregative Representation Learning for Group Recommendation

08/10/2019
by   Peipei Wang, et al.
0

Frequent group activities of human beings have become an indispensable part in their daily life. Group recommendation can recommend satisfactory activities to group members in the recommender systems, and the key issue is how to aggregate preferences in different group members. Most existing group recommendation employed the predefined static aggregation strategies to aggregate the preferences of different group members, but these static strategies cannot simulate the dynamic group decision-making. Meanwhile, most of these methods depend on intuitions or assumptions to analyze the influence of group members and lack of convincing theoretical support. We argue that the influence of group members plays a particularly important role in group decision-making and it can better assist group profile modeling and perform more accurate group recommendation. To tackle the issue of preference aggregation for group recommendation, we propose a novel attentive aggregation representation learning method based on sociological theory for group recommendation, namely SIAGR (short for "Social Influence-based Attentive Group Recommendation"), which takes attention mechanisms and the popular method (BERT) as the aggregation representation for group profile modeling. Specifically, we analyze the influence of group members based on social identity theory and two-step flow theory and exploit an attentive mavens mining method. In addition, we develop a BERT-based representation method to learn the interaction of group members. Lastly, we complete the group recommendation under the neural collaborative filtering framework and verify the effectiveness of the proposed method by experimenting.

READ FULL TEXT
research
10/02/2020

Overcoming Data Sparsity in Group Recommendation

It has been an important task for recommender systems to suggest satisfy...
research
11/06/2019

Attentive Geo-Social Group Recommendation

Social activities play an important role in people's daily life since th...
research
08/06/2023

Predicting Group Choices from Group Profiles

Group recommender systems (GRS) identify items to recommend to a group b...
research
02/07/2023

ConsRec: Learning Consensus Behind Interactions for Group Recommendation

Since group activities have become very common in daily life, there is a...
research
07/27/2017

Group Recommendations: Axioms, Impossibilities, and Random Walks

We introduce an axiomatic approach to group recommendations, in line of ...
research
09/28/2022

B2B Advertising: Joint Dynamic Scoring of Account and Users

When a business sells to another business (B2B), the buying business is ...
research
04/13/2021

Group Recommendation Techniques for Feature Modeling and Configuration

In large-scale feature models, feature modeling and configuration proces...

Please sign up or login with your details

Forgot password? Click here to reset