LAUSR

TruCom: Exploiting Domain-Specific Trust Networks for Multicategory Item Recommendation

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0 Published in 2017 at "IEEE Systems Journal"

DOI: 10.1109/jsyst.2015.2427193

Abstract: Recommender systems (RSs) have become important tools for solving the problem of information overload. With the advent and popularity of online social networks, some studies on network-based recommendation have emerged, raising the concern of many… read more here.

Keywords: recommendation; domain specific; trust; item recommendation ... See more keywords

HIGnet: Hierarchical and Interactive Gate Networks for Item Recommendation

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1 Published in 2020 at "IEEE Intelligent Systems"

DOI: 10.1109/mis.2020.3005928

Abstract: Existing research exploits the semantic information from reviews to complement user-item interactions for item recommendation. However, as these approaches either defer the user-item interactions until the prediction layer or simply concatenate all the reviews of… read more here.

Keywords: item; item recommendation; user item; hierarchical interactive ... See more keywords

GCRec: Graph-Augmented Capsule Network for Next-Item Recommendation.

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1 Published in 2022 at "IEEE transactions on neural networks and learning systems"

DOI: 10.1109/tnnls.2022.3164982

Abstract: Next-item recommendation has been a hot research, which aims at predicting the next action by modeling users' behavior sequences. While previous efforts toward this task have been made in capturing complex item transition patterns, we… read more here.

Keywords: item; item recommendation; term; graph ... See more keywords

On sampled metrics for item recommendation

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1 Published in 2022 at "Communications of the ACM"

DOI: 10.1145/3535335

Abstract: Recommender systems personalize content by recommending items to users. Item recommendation algorithms are evaluated by metrics that compare the positions of truly relevant items among the recommended items. To speed up the computation of metrics,… read more here.

Keywords: item recommendation; sampled metrics; metrics item;