Learning Word Embeddings from Wikipedia for Content-Based Recommender Systems-Reference-Cited by-同舟云学术

Learning Word Embeddings from Wikipedia for Content-Based Recommender Systems

Published:2016 Issue: Volume: Page:729-734
ISSN:0302-9743
Container-title:Lecture Notes in Computer Science
language:
Short-container-title:

Author:

Musto Cataldo,Semeraro Giovanni,de Gemmis Marco,Lops Pasquale

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-30671-1_60

Reference10 articles.

1. Deerwester, S., Dumais, S., Landauer, T., Furnas, G., Harshman, R.: Indexing by latent semantic analysis. JASIS 41, 391–407 (1990)

2. Gouws, S., Bengio, Y., Corrado, G. Bilbowa: Fast bilingual distributed representations without word alignments (2014). arXiv:1410.2455

3. Harris, Z.S.: Mathematical Structures of Language. Interscience, New York (1968)

4. Lecture Notes in Computer Science;F McCarey,2006

5. Mikolov, T., Sutskever, I., Chen, K., Corrado, G., Dean, J.: Distributed representations of words and phrases and their compositionality. In: NIPS, pp. 3111–3119 (2013)

Cited by 65 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Evaluating Content-based Pre-Training Strategies for a Knowledge-aware Recommender System based on Graph Neural Networks;Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization;2024-06-22

2. Performance Evaluation of Vector Embeddings with Retrieval-Augmented Generation;2024 9th International Conference on Computer and Communication Systems (ICCCS);2024-04-19

3. Temporally Dynamic Session-Keyword Aware Sequential Recommendation System;2023 IEEE International Conference on Data Mining Workshops (ICDMW);2023-12-04

4. A Movie Recommender System with Collaborative and Content Filtering;Artificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications;2023-08-14

5. Combining Graph Neural Networks and Sentence Encoders for Knowledge-aware Recommendations;Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization;2023-06-18