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Session-Based Recommendations Using Item Embedding
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1145/1526709.1526943openalex-snapshot
Buzz-based recommender system
inferredcites →https://doi.org/10.1145/2766462.2767780openalex-snapshot
Word Embedding based Generalized Language Model for Information Retrieval
inferredcites →https://doi.org/10.1145/2856767.2856781openalex-snapshot
Learning Item Temporal Dynamics for Predicting Buying Sessions
inferredcites →https://doi.org/10.1145/2872518.2889361openalex-snapshot
Improving Document Ranking with Dual Word Embeddings
inferredcites →https://doi.org/10.1145/371920.372071openalex-snapshot
Item-based collaborative filtering recommendation algorithms
inferredcites →https://doi.org/10.1145/504216.504224openalex-snapshot
Fluid annotations in an open world
inferredcites →https://doi.org/10.1163/1872-9037_afco_asc_2264openalex-snapshot
Indiana University Press
inferredcites →https://doi.org/10.1177/089443939201000402openalex-snapshot
Social Impacts of Computing: Codes of Professional Ethics
inferredcites →https://doi.org/10.3115/v1/d14-1162openalex-snapshot
Glove: Global Vectors for Word Representation
inferredcites →https://doi.org/10.3115/v1/p15-1025openalex-snapshot
Learning Continuous Word Embedding with Metadata for Question Retrieval in Community Question Answering
inferredcites →https://doi.org/10.3115/v1/w14-4012openalex-snapshot
On the Properties of Neural Machine Translation: Encoder–Decoder Approaches
inferredcites →https://doi.org/10.48550/arxiv.1301.0600openalex-snapshot
An MDP-based Recommender System
inferredcites →https://doi.org/10.48550/arxiv.1301.3781openalex-snapshot
Efficient Estimation of Word Representations in Vector Space
inferredcites →https://doi.org/10.48550/arxiv.1511.06939openalex-snapshot
Session-based Recommendations with Recurrent Neural Networks
inferredcites →https://doi.org/10.5860/choice.32-5434openalex-snapshot
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What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Deep Learning for Recommender Systems
inferred← citeshttps://doi.org/10.1007/978-3-030-01171-0_12openalex-snapshot
A Systematic Literature Review on Word Embeddings
inferred← citeshttps://doi.org/10.1007/978-3-030-91699-2_22openalex-snapshot
Time-Dependent Item Embeddings for Collaborative Filtering
inferred← citeshttps://doi.org/10.1007/978-3-031-21689-3_35openalex-snapshot
Interact2Vec: Neural Item and User Embedding for Collaborative Filtering
inferred← citeshttps://doi.org/10.1007/978-3-031-23515-3_8openalex-snapshot
Boosting Item Coverage in Session-Based Recommendation
inferred← citeshttps://doi.org/10.1007/978-3-032-30518-3_16openalex-snapshot
Lightweight Transformer-Based Event Embeddings with Log-Frequency Session Weighting for Purchase Prediction in E-Commerce Clickstream Data
inferred← citeshttps://doi.org/10.1007/978-981-16-1342-5_49openalex-snapshot
Session-based Personalized Recommender System for Online Shopping
inferred← citeshttps://doi.org/10.1007/s11390-018-1853-0openalex-snapshot
Illuminating Recommendation by Understanding the Explicit Item Relations
inferred← citeshttps://doi.org/10.1007/s12599-023-00843-6openalex-snapshot
SJORS: A Semantic Recommender System for Journalists
inferred← citeshttps://doi.org/10.1007/s13042-026-03206-1openalex-snapshot
Capturing dynamic interests with deformable attention mechanism for session-based recommendation
inferred← citeshttps://doi.org/10.1007/s13369-020-05112-2openalex-snapshot
Research on Understanding the Effect of Deep Learning on User Preferences
inferred← citeshttps://doi.org/10.1016/j.datak.2019.101781openalex-snapshot
Dynamic monitoring of software use with recurrent neural networks
inferred← citeshttps://doi.org/10.1016/j.elerap.2019.100914openalex-snapshot
Machine learning and operation research based method for promotion optimization of products with no price elasticity history
inferred← citeshttps://doi.org/10.1016/j.eswa.2021.114834openalex-snapshot
Context-aware item attraction model for session-based recommendation
inferred← citeshttps://doi.org/10.1016/j.jbi.2023.104577openalex-snapshot
Improving severity classification of Hebrew PET-CT pathology reports using test-time augmentation
inferred← citeshttps://doi.org/10.1016/j.knosys.2018.02.026openalex-snapshot
Personal price aware multi-seller recommender system: Evidence from eBay
inferred← citeshttps://doi.org/10.1088/1742-6596/1437/1/012047openalex-snapshot
Travel Attractions Recommendation based on Max-negative the Gated Recurrent Unit trajectory mining Representation
inferred← citeshttps://doi.org/10.1109/access.2020.2976491openalex-snapshot
Generating Realistic Users Using Generative Adversarial Network With Recommendation-Based Embedding
inferred← citeshttps://doi.org/10.1109/access.2023.3298672openalex-snapshot
Improvement and Optimization of Vulnerability Detection Methods for Ethernet Smart Contracts
inferred← citeshttps://doi.org/10.1109/iccubea47591.2019.9128976openalex-snapshot
Trend Detection Using Time Based Sequential Recommendations
inferred← citeshttps://doi.org/10.1109/tnnls.2024.3383246openalex-snapshot
Context-Aware REpresentation: Jointly Learning Item Features and Selection From Triplets
inferred← citeshttps://doi.org/10.1145/3109859.3109877openalex-snapshot
Sequential User-based Recurrent Neural Network Recommendations
inferred← citeshttps://doi.org/10.1145/3172944.3172957openalex-snapshot
Session-based Suggestion of Topics for Geographic Exploratory Search
inferred← citeshttps://doi.org/10.1145/3184558.3191582openalex-snapshot
Session-based News Recommendations
inferred← citeshttps://doi.org/10.1145/3289600.3290973openalex-snapshot
Solving the Sparsity Problem in Recommendations via Cross-Domain Item Embedding Based on Co-Clustering
inferred← citeshttps://doi.org/10.1145/3426723openalex-snapshot
Deep Learning for Sequential Recommendation
inferred← citeshttps://doi.org/10.1145/3465401openalex-snapshot
A Survey on Session-based Recommender Systems
inferred← citeshttps://doi.org/10.1145/3490099.3511143openalex-snapshot
Learning User Interface Semantics from Heterogeneous Networks with Multimodal and Positional Attributes
inferred← citeshttps://doi.org/10.1145/3583780.3615152openalex-snapshot
Counterfactual Adversarial Learning for Recommendation
inferred← citeshttps://doi.org/10.1145/3604915.3608879openalex-snapshot
Challenges for Anonymous Session-Based Recommender Systems in Indoor Environments
inferred← citeshttps://doi.org/10.1360/ssi-2019-0177openalex-snapshot
Recurrent memory networks: modeling long short-term user preferences for session-based recommendation
inferred← citeshttps://doi.org/10.1587/transinf.2023dap0006openalex-snapshot
A Personalised Session-Based Recommender System with Sequential Updating Based on Aggregation of Item Embeddings
inferred← citeshttps://doi.org/10.3837/tiis.2020.02.004openalex-snapshot
Gated Recurrent Unit Architecture for Context-Aware Recommendations with improved Similarity Measures
inferred← citeshttps://doi.org/10.48550/arxiv.1706.10231openalex-snapshot
Improving Session Recommendation with Recurrent Neural Networks by Exploiting Dwell Time
inferred← citeshttps://doi.org/10.48550/arxiv.1802.08452openalex-snapshot
Sequence-Aware Recommender Systems
inferred← citeshttps://doi.org/10.48550/arxiv.1905.01686openalex-snapshot
New Item Consumption Prediction Using Deep Learning
inferred← citeshttps://doi.org/10.48550/arxiv.1905.01997openalex-snapshot
Deep Learning for Sequential Recommendation: Algorithms, Influential Factors, and Evaluations
inferred← citeshttps://doi.org/10.48550/arxiv.2111.06057openalex-snapshot
Characterization of Frequent Online Shoppers using Statistical Learning with Sparsity
inferred← citeshttps://doi.org/10.5753/jbcs.2025.5426openalex-snapshot
Beyond Recommendations: Intrinsic Evaluation Strategies for Item Embeddings in Recommender Systems
inferred← citeshttps://doi.org/10.5753/webmedia.2024.243199openalex-snapshot
Why Ignore Content? A Guideline for Intrinsic Evaluation of Item Embeddings for Collaborative Filtering
inferred← citeshttps://doi.org/10.58837/chula.the.2019.165openalex-snapshot
A generative adversarial network for generating realistic users using embedding from recommendation systems
inferred← citeshttps://doi.org/10.70675/c59febf8z3f87z4b7dzb5edz68985e616f7eopenalex-snapshot
Pattern Recognition in the Usage Sequences of Medical Apps
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