Papers Next-basket recommendation
“Next-basket recommendation” 태그가 달린 논문 18편 · 필터 해제
Repeat-bias-aware Optimization of Beyond-accuracy Metrics for Next Basket Recommendation
In next basket recommendation (NBR) a set of items is recommended to users based on their historical basket sequences. In many domains, the recommended baskets consist of both repeat items and explore items. Some state-o…
DiversityFairnessNext-basket recommendationSAFERec: Self-Attention and Frequency Enriched Model for Next Basket Recommendation
Transformer-based approaches such as BERT4Rec and SASRec demonstrate strong performance in Next Item Recommendation (NIR) tasks. However, applying these architectures to Next-Basket Recommendation (NBR) tasks, which ofte…
Next-basket recommendationA Universal Sets-level Optimization Framework for Next Set Recommendation
Next Set Recommendation (NSRec), encompassing related tasks such as next basket recommendation and temporal sets prediction, stands as a trending research topic. Although numerous attempts have been made on this topic, t…
DiversityNext-basket recommendationBasket-Enhanced Heterogenous Hypergraph for Price-Sensitive Next Basket Recommendation
Next Basket Recommendation (NBR) is a new type of recommender system that predicts combinations of items users are likely to purchase together. Existing NBR models often overlook a crucial factor, which is price, and do …
Next-basket recommendationRecommendation SystemsAre We Really Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation?
Next basket recommendation (NBR) is a special type of sequential recommendation that is increasingly receiving attention. So far, most NBR studies have focused on optimizing the accuracy of the recommendation, whereas op…
DiversityFairnessNavigateNext-basket recommendation+1[RE] Modeling Personalized Item Frequency Information for Next-basket Recommendation
This paper focuses on reproducing and extending the results of the paper: "Modeling Personalized Item Frequency Information for Next-basket Recommendation" which introduced the TIFU-KNN model and proposed to utilize Pers…
FairnessNext-basket recommendationHypergraph Enhanced Knowledge Tree Prompt Learning for Next-Basket Recommendation
Next-basket recommendation (NBR) aims to infer the items in the next basket given the corresponding basket sequence. Existing NBR methods are mainly based on either message passing in a plain graph or transition modellin…
Next-basket recommendationPrompt LearningMasked and Swapped Sequence Modeling for Next Novel Basket Recommendation in Grocery Shopping
Next basket recommendation (NBR) is the task of predicting the next set of items based on a sequence of already purchased baskets. It is a recommendation task that has been widely studied, especially in the context of gr…
Next-basket recommendationTime-Aware Item Weighting for the Next Basket Recommendations
In this paper we study the next basket recommendation problem. Recent methods use different approaches to achieve better performance. However, many of them do not use information about the time of prediction and time int…
Next-basket recommendationMitigating Frequency Bias in Next-Basket Recommendation via Deconfounders
Recent studies on Next-basket Recommendation (NBR) have achieved much progress by leveraging Personalized Item Frequency (PIF) as one of the main features, which measures the frequency of the user's interactions with the…
Causal InferenceFairnessNext-basket recommendationRecommendation SystemsA Systematical Evaluation for Next-Basket Recommendation Algorithms
Next basket recommender systems (NBRs) aim to recommend a user's next (shopping) basket of items via modeling the user's preferences towards items based on the user's purchase history, usually a sequence of historical ba…
Next-basket recommendationRecommendation SystemsEfficiently Maintaining Next Basket Recommendations under Additions and Deletions of Baskets and Items
Recommender systems play an important role in helping people find information and make decisions in today's increasingly digitalized societies. However, the wide adoption of such machine learning applications also causes…
Next-basket recommendationRecommendation SystemsSequential RecommendationA Next Basket Recommendation Reality Check
The goal of a next basket recommendation (NBR) system is to recommend items for the next basket for a user, based on the sequence of their prior baskets. Recently, a number of methods with complex modules have been propo…
Next-basket recommendationModeling Dynamic Attributes for Next Basket Recommendation
Traditional approaches to next item and next basket recommendation typically extract users' interests based on their past interactions and associated static contextual information (e.g. a user id or item category). Howev…
AttributeNext-basket recommendationModeling Personalized Item Frequency Information for Next-basket Recommendation
Next-basket recommendation (NBR) is prevalent in e-commerce and retail industry. In this scenario, a user purchases a set of items (a basket) at a time. NBR performs sequential modeling and recommendation based on a sequ…
Next-basket recommendationSession-Based RecommendationsM2: Mixed Models with Preferences, Popularities and Transitions for Next-Basket Recommendation
Next-basket recommendation considers the problem of recommending a set of items into the next basket that users will purchase as a whole. In this paper, we develop a novel mixed model with preferences, popularities and t…
DecoderNext-basket recommendationCorrelation-Sensitive Next-Basket Recommendation
Items adopted by a user over time are indicative of the underlying preferences. We are concerned with learning such preferences from observed sequences of adoptions for recommendation. As multiple items are commonly adop…
Next-basket recommendationPre-training of Context-aware Item Representation for Next Basket Recommendation
Next basket recommendation, which aims to predict the next a few items that a user most probably purchases given his historical transactions, plays a vital role in market basket analysis. From the viewpoint of item, an i…
Next-basket recommendationRecommendation Systems