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Recommendation Through Mixtures of Heterogeneous Item Relationships [article]

Wang-Cheng Kang, Mengting Wan, Julian McAuley
2018 arXiv   pre-print
Here we seek to develop a framework that is capable of combining such heterogeneous item relationships by simultaneously modeling (a) what modality of recommendation is a user likely to be susceptible  ...  Specific instances make use of signals ranging from user feedback, item relationships, geographic locality, social influence (etc.).  ...  We capture this intuition with a new model-Mixtures of Heterogeneous Recommenders (MoHR).  ... 
arXiv:1808.10031v1 fatcat:uqijrxoctfhqfptbb2ujjcfw3u

Predictive and Contrastive: Dual-Auxiliary Learning for Recommendation [article]

Yinghui Tao, Min Gao, Junliang Yu, Zongwei Wang, Qingyu Xiong, Xu Wang
2022 arXiv   pre-print
Accordingly, the rich semantics reflected by social relationships and item categories, which lie in the recommendation data-based heterogeneous graphs, are not fully exploited.  ...  To explore recommendation-specific auxiliary tasks, we first quantitatively analyze the heterogeneous interaction data and find a strong positive correlation between the interactions and the number of  ...  Support Program of Chongqing (cx2020097).  ... 
arXiv:2203.03982v2 fatcat:wvqlbmet6vhfzldyvis2nn3774

Graph Neural News Recommendation with Long-term and Short-term Interest Modeling [article]

Linmei Hu, Chen Li, Chuan Shi, Cheng Yang, Chao Shao
2019 arXiv   pre-print
Existing methods on news recommendation mainly include collaborative filtering methods which rely on direct user-item interactions and content based methods which characterize the content of user reading  ...  The incorporated topic information would help indicate a user's interest and alleviate the sparsity of user-item interactions.  ...  This work is supported by the National Natural Science Foundation of China  ... 
arXiv:1910.14025v2 fatcat:unpsq7kqynfqjlof3nxyq4uan4

A Multi-Granular Aggregation-Enhanced Knowledge Graph Representation for Recommendation

Xi Liu, Rui Song, Yuhang Wang, Hao Xu
2022 Information  
nodes in the heterogeneous network into three categories—users, items, and entities, and connects the edges according to the similarity between the users and items so as to enhance the high-order connectivity  ...  limitation of information loss of the traditional GNN recommendation model.  ...  Acknowledgments: The authors would like to thank all of anonymous reviewers and editors for their helpful suggestions for the improvement of this paper.  ... 
doi:10.3390/info13050229 fatcat:k4fqottd3vaoncy5r7kgdty4zi

TwHIN: Embedding the Twitter Heterogeneous Information Network for Personalized Recommendation [article]

Ahmed El-Kishky, Thomas Markovich, Serim Park, Chetan Verma, Baekjin Kim, Ramy Eskander, Yury Malkov, Frank Portman, Sofía Samaniego, Ying Xiao, Aria Haghighi
2022 arXiv   pre-print
Social networks, such as Twitter, form a heterogeneous information network (HIN) where nodes represent domain entities (e.g., user, content, advertiser, etc.) and edges represent one of many entity interactions  ...  downstream recommendation and classification tasks: personalized ads rankings, account follow-recommendation, offensive content detection, and search ranking.  ...  Follow-up works have leveraged the rich plethora of entity relationships to perform personalized recommendation [58] .  ... 
arXiv:2202.05387v1 fatcat:jcjk7kc5bnenfemj2ibysbveze

Is Living in Mwanza Region More Economically Better and Happier than Living in Kagera Region? Finite Mixture (FIMIX) Approach

Ntogwa N. Bundala, Deus Dominic P. Ngaruko, Timothy M. Lyanga
2021 Asian Journal of Economics Business and Accounting  
The study aimed to uncover the unobserved heterogeneity of the population in Mwanza and Kagera regions.  ...  Moreover, further study recommended by using a panel data to attest the posed facts because this study limited to the cross-sectional data.  ...  for the conceptually similar items and 85 percent for non-conceptually similar items [23] .  ... 
doi:10.9734/ajeba/2021/v21i630387 fatcat:ejmbfut6rbg53ean6kngxkizk4

The Accuracy of Computerized Adaptive Testing in Heterogeneous Populations: A Mixture Item-Response Theory Analysis

Richard Sawatzky, Pamela A. Ratner, Jacek A. Kopec, Amery D. Wu, Bruno D. Zumbo, Fabio Rapallo
2016 PLoS ONE  
items of the CAT-5D-QOL.  ...  We evaluated bias by comparing the referent PRO scores of the LVMM with PRO scores predicted by a "conventional" CAT (ignoring heterogeneity) and a LVMM-based "mixture" CAT (accommodating heterogeneity  ...  Accordingly, researchers have recommended the use of latent variable mixture models (LVMM) to examine the possibility of heterogeneity in a sample with the measurement of a construct [26] [27] [28] [30  ... 
doi:10.1371/journal.pone.0150563 pmid:26930348 pmcid:PMC4773251 fatcat:2544vslsdnfzhiju34kta5rija

Temporal Meta-path Guided Explainable Recommendation [article]

Hongxu Chen, Yicong Li, Xiangguo Sun, Guandong Xu, Hongzhi Yin
2021 arXiv   pre-print
recommendations.  ...  Extensive evaluations of TMER on three real-world benchmark datasets show state-of-the-art performance compared against recent strong baselines.  ...  For example, the transitivity of co-purchasing relationships between friends and the substitute relationship of items can be discovered by modelling higher-order relations in a bipartite user-item graph  ... 
arXiv:2101.01433v1 fatcat:hmwunjchvfashccozecbkswtra

Learning personal + social latent factor model for social recommendation

Yelong Shen, Ruoming Jin
2012 Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12  
There have been a few studies on social recommendations; however, they almost completely ignored the heterogeneity and diversity of the social relationship.  ...  Especially, the PSLF extracts the social factor vectors for each user based on the state-of-the-art mixture membership stochastic blockmodel, which can explicitly express the varieties of the social relationship  ...  Clearly, the existing approaches have largely ignored the heterogeneity and diversity of the social relationship.  ... 
doi:10.1145/2339530.2339732 dblp:conf/kdd/ShenJ12 fatcat:m6f76tiqdrgu3dnu3rwfrqttaa

A Survey of Data Mining Techniques on Information Networks

Sadhana Kodali, Madhavi Dabbiru, B Thirumala Rao
2018 International Journal of Engineering & Technology  
The Data Mining techniques of both homogeneous and heterogeneous information networks are discussed in detail and a comparative study on each problem category is showcased.  ...  This paper presents a survey of various Data Mining techniques that can be applicable to information networks.  ...  The final step is to generate recommendation using mostfrequent item based recommendation where the count of most frequent items purchased are calculated ,sorted and the most frequent products are given  ... 
doi:10.14419/ijet.v7i2.6.11267 fatcat:zavu7rli4ja2ne3nj6wiz4wxhi


Navin Tatyaba Gopal, Anish Raj Khobragade
2020 EPRA international journal of research & development  
The Knowledge graphs (KGs) catches structured data and relationships among a bunch of entities and items.  ...  Generally, constitute an attractive origin of information that can advance the recommender systems.  ...  A major role in the Recommendation is the interaction between the user -item relationship and the user -user relationship.  ... 
doi:10.36713/epra6692 fatcat:4lbgcu52bzdwnjnqgngcxhzh7u

Implementing Managerial Constraints in Model-Based Segmentation: Extensions of Kim, Fong, and DeSarbo (2012) with an Application to Heterogeneous Perceptions of Service Quality

Sunghoon Kim, Simon J. Blanchard, Wayne S. Desarbo, Duncan K.H. Fong
2013 Journal of Marketing Research  
Researchers have recently introduced a finite mixture Bayesian regression model to simultaneously identify consumer market segments (heterogeneity) and determine how such segments differ with respect to  ...  The authors demonstrate with synthetic data that the new constrained finite mixture Bayesian regression models can be used to identify and represent several constrained heterogeneous response patterns  ...  quality as measured through a single-item scale (Babakus and Boiler 1992; Jain and Gupta 2004) .  ... 
doi:10.1509/jmr.13.0056 fatcat:5wbgwo7aovcohd3d6ethbqeta4

A Variational Autoencoder Mixture Model for Online Behavior Recommendation

Minh-Duc Nguyen, Yoon-Sik Cho
2020 IEEE Access  
MMM and HGM are two state-of-the-art mixture models for behavior recommendation.  ...  Because the latent representation reflects the latent interests of users, which is heterogeneous to all user, VAE can suggest different but suitable unseen items for each user.  ... 
doi:10.1109/access.2020.3010508 fatcat:wr7kbfnmkbfezeprtpg2xvyeta

Understanding Heterogeneity in Adaptation to Retirement: A Growth Mixture Modeling Approach

Alexa M. Muratore, Joanne K. Earl, Catherine G. Collins
2014 The International Journal of Aging & Human Development  
For life satisfaction, growth mixture modeling identified three distinctly growing subgroups.  ...  Previous research has shown that as people transition to retirement they display heterogeneous growth in outcomes.  ...  Observing subgroups that display distinct growth has become possible through the development of more sophisticated and flexible analysis techniques, for example Growth Mixture Modeling (GMM; Muthén, 2001  ... 
doi:10.2190/ag.79.2.c pmid:25536703 fatcat:u4axcah7szayxfl64mto3vmkiq

Psychological characteristics and household savings behavior: The importance of accounting for latent heterogeneity

Patrick Gerhard, Joe J. Gladstone, Arvid O.I. Hoffmann
2018 Journal of Economic Behavior and Organization  
We employ a finite mixture model with maximum likelihood (ML) estimation to analyze latent heterogeneity in the relationship between psychological characteristics and household savings behavior.  ...  We find that the relationship between psychological characteristics and savings behavior differs across these two classes, demonstrating the importance of accounting for latent heterogeneity when studying  ...  Results In this section, we present evidence on unobserved heterogeneity in savings behavior, obtained through fitting a finite mixture model in a one-step maximum likelihood (ML) estimation approach with  ... 
doi:10.1016/j.jebo.2018.02.013 fatcat:ghwbqqsrbvdnvmaevctiij7y54
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