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Joint Deep Network With Auxiliary Semantic Learning for Popular Recommendation

Xingkai Wang, Yiqiang Sheng, Haojiang Deng
2020 IEEE Access  
We use the optimized CharCNN networks to learn the auxiliary semantic vectors from the users' reviews.  ...  In this paper, we propose a new joint deep network model with auxiliary semantic learning for the popular recommendation algorithm (DMPRA).  ...  ACKNOWLEDGMENT The authors would like to thank the editor and the anonymous reviewers for constructive suggestions.  ... 
doi:10.1109/access.2020.2976498 fatcat:7y5kidjvzfdzzhm5qfv35h7hjm

Attention-based Adaptive Memory Network for Recommendation with Review and Rating

Wei Liu, Zhiping Lin, Huaijie Zhu, Jing Wang, Arun Kumar Sangaiah
2020 IEEE Access  
Notably, this paper is the first to bring static features into adaptively extracting semantic information from reviews, which can not only characterize user and item from a global view, but also assist  ...  extraction from reviews.  ...  ACKNOWLEDGMENT The authors thank the anonymous reviewers very much for their efforts in evaluating their paper.  ... 
doi:10.1109/access.2020.2997115 fatcat:yo6ko6awtrelnehw3nrsijnpve

Hierarchical Text Interaction for Rating Prediction [article]

Jiahui Wen and Jingwei Ma and Hongkui Tu and Wei Yin and Jian Fang
2020 arXiv   pre-print
To address these challenges, many works propose to exploit semantic information from review data.  ...  For textual modeling, they simply concatenate all the reviews of a user/item into a single review. However, feature extraction at word/phrase level can violate the meaning of the original reviews.  ...  At review level, we propose an interactive network that propagates textual features between the user and item, and guide each other to select the relevant reviews for recommendation.  ... 
arXiv:2010.07628v1 fatcat:yugnqn2hsbhotnbrflrqxzkise

Preface to the Special Issue on Recommender Systems

Tommaso Di Noia, Dietmar Jannach
2016 Journal on Data Semantics  
This Special Issue on Recommender Systems of the Journal of Data Semantics includes the extended versions of three selected papers from the Search, Comparison and Recommender Systems track of the 16th  ...  An interesting result presented in the paper is that extracting and using the features from the trailer of a movie can be sufficient for recommendation purposes.  ... 
doi:10.1007/s13740-015-0056-x fatcat:rip4bwoxhze3ldcjb7j7emhhtm

A Literature Review on Medicine Recommender Systems

Benjamin Stark, Constanze Knahl, Mert Aydin, Karim Elish
2019 International Journal of Advanced Computer Science and Applications  
In this paper, we conduct a literature review on the existing solutions for medicine recommender systems, describe and compare them based on various features, and present future research directions.  ...  Medicine recommender systems can assist the medical care providers with the selection of an appropriate medication for the patients.  ...  In this paper, we review the existing medicine recommendation system solutions, and compare them based on various features.  ... 
doi:10.14569/ijacsa.2019.0100802 fatcat:ahkrevzj2ffnvkqbwc4zxepq3e

Augmenting the User-Item Graph with Textual Similarity Models [article]

Federico López and Martin Scholz and Jessica Yung and Marie Pellat and Michael Strube and Lucas Dixon
2021 arXiv   pre-print
This paper introduces a simple and effective form of data augmentation for recommender systems.  ...  A paraphrase similarity model is applied to widely available textual data, such as reviews and product descriptions, yielding new semantic relations that are added to the user-item graph.  ...  ACKNOWLEDGMENTS This work has been supported by the German Research Foundation (DFG) as part of the Research Training Group Adaptive Preparation of Information from Heterogeneous Sources (AIPHES) under  ... 
arXiv:2109.09358v1 fatcat:vveigeq64fdchbvtvuph6igq6m

Interactive Movie Recommendation Through Latent Semantic Analysis and Storytelling [article]

Kodzo Wegba, Aidong Lu, Yuemeng Li, Wencheng Wang
2017 arXiv   pre-print
We propose a Latent Semantic Model (LSM) that captures the statistical features of semantic concepts on 2D domains and abstracts user preferences for personal recommendation.  ...  Second, we propose an interactive recommendation approach through a storytelling mechanism for promoting the communication between the user and the recommendation system.  ...  For efficiency, we recommend movies in groups, with each group containing movies selected from combined movie features that are extracted from watch history.  ... 
arXiv:1701.00199v1 fatcat:ai4prf3zvvd2bd4jcht7a7kwcq

LOD Cloud Mining for Prognosis Model(Case Study: Native App for Drug Recommender System)

Nidhi Kushwaha, Raman Goyal, Pramiti Goel, Sidharth Singla, Om Prakash Vyas
2014 Advances in Internet of Things  
recommendation) according to the features of the patient.  ...  With this project we try to provide an assistant to the doctor for better recommendations.  ...  Here, manual revision has been done by selecting some semantically generated features manually for Data Mining task, while on the other side, the rest of the features are directly fed to the final user's  ... 
doi:10.4236/ait.2014.43004 fatcat:wo4sjaz5mneafacrpocttttjmu

Guest editorial: web multimedia semantic inference using multi-cues

Yahong Han, Yi Yang, Xiaofang Zhou
2015 World wide web (Bussum)  
The paper "From constrained to unconstrained datasets an evaluation of local action descriptors and fusion strategies for interaction recognition" introduce a new unconstrained video dataset for interaction  ...  The proposed method employs sparse feature selection to select relevant features and then maximize the canonical coefficient during image-audio feature dimension reduction for cross-media correlation mining  ... 
doi:10.1007/s11280-015-0360-2 fatcat:vc4plge5qvg7hfmza3dffmawki

Visual Exploration for Social Recommendations [chapter]

Junichi Tatemura
2000 Advances in Visual Information Management  
We propose a visual exploration technique, "visual exploration by example," for recommendations in a social filtering system.  ...  A dynamic semantic map of items, rearranged dynamically for each query or filtering result, gives explanations of the result with contextual information and helps the user's composition of a new query.  ...  By composing a movie query with these reviewers, the user obtains new movies as recommendations from them.  ... 
doi:10.1007/978-0-387-35504-7_5 fatcat:4p4xrxmqtzgdpodhnhp7krr7va

Learning Hierarchical Review Graph Representations for Recommendation [article]

Yong Liu, Susen Yang, Yinan Zhang, Chunyan Miao, Zaiqing Nie, Juyong Zhang
2021 arXiv   pre-print
from the review data for recommendation.  ...  Moreover, a personalized graph pooling operator is proposed to learn hierarchical representations of the review graph to form the semantic representation for each user/item.  ...  from the reviewcontent view and user-item interaction view for recommendation. • DAML [25] : This method employs CNN with local and mutual attention mechanism to learn the review features and improve  ... 
arXiv:2004.11588v3 fatcat:r5j5dncjjzhw5jtysqewmy35va

Multimedia and semantic technologies for future computing environments

Seungmin Rho, Marco Bertini, Gamhewage Chaminda de Silva, Stephan Kopf
2011 Multimedia tools and applications  
We have selected fourteen research papers whose topics are strongly related to the multimedia and semantic technology.  ...  This special issue on multimedia and semantic technologies for future computing environments provides high quality contributions addressing related theoretical and practical aspects of semantic multimedia  ...  Fourteen manuscripts were finally selected for this special issue. Each manuscript selected was blindly reviewed by at least three reviewers consisting of guest editors and external reviewers.  ... 
doi:10.1007/s11042-011-0777-2 fatcat:zs6rretk6ngobmcnhfuae7uqhe

Requirement specification of an ontology-based semantic recommender system for medical prescriptions and drug interaction detection

Ali Asghar Safaei, Sayyed Saeid Safaei
2019 International Journal of Electronic Healthcare  
In this paper, requirement specification of a ontology-based semantic recommender system for medical prescriptions and drug interaction detection has been presented.  ...  A prototype was developed using Java to evaluate the functions of drug recommendations and drug interaction detection.  ...  Table 1 A selection of functional requirements of the seminal recommender system for prescription and interaction detection Requirement code Requirement description GetIntFR17 The system must insert  ... 
doi:10.1504/ijeh.2019.108565 fatcat:bkzmycavpner3dfuyvv3qgzx7q

Multimedia Recommendation System for Video Game Based on High-Level Visual Semantic Features

Fasiha Ikram, Humera Farooq
2022 Scientific Programming  
Recent approaches have shown that the inclusion of visual information is helpful to understand the semantic features for a recommendation model.  ...  This study proposed a novel method named Deep Visual Semantic Multimedia Recommendation Systems (D_VSMR) to deal with high-level visual features for multimedia recommendation systems.  ...  For data scrapping, games data is selected considering that it provides rich semantic visual features for model learning and attributes for data recommendation.  ... 
doi:10.1155/2022/6084363 doaj:32ac8be58aff40fa8f64b20352aa07b8 fatcat:qdjb7v5lznag3gz7eqrdvxd2p4

Use of Deep Learning in Modern Recommendation System: A Summary of Recent Works

Ayush Singhal, Pradeep Sinha, Rakesh Pant
2017 International Journal of Computer Applications  
for recommendation.  ...  The review also discusses the contribution of deep learning integrated recommendation systems into several application domains.  ...  We used the Google scholar search engine to fetch research articles pool to select relevant papers for our review.  ... 
doi:10.5120/ijca2017916055 fatcat:m6icpquumbgczhrdnya7x35of4
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