Zobrazeno 1 - 10
of 92
pro vyhledávání: '"Shangsong Liang"'
Publikováno v:
Mathematics, Vol 12, Iss 14, p 2189 (2024)
Capturing long-term dependency from historical behaviors is the key to the success of sequential recommendation; however, existing methods focus on extracting global sequential information while neglecting to obtain deep representations from subseque
Externí odkaz:
https://doaj.org/article/ea2e1f104cee4d46a3275e06575b459e
Autor:
Shiyang Liang, Siwei Liu, Junliang Song, Qiang Lin, Shihong Zhao, Shuaixin Li, Jiahui Li, Shangsong Liang, Jingjie Wang
Publikováno v:
BMC Bioinformatics, Vol 24, Iss 1, Pp 1-13 (2023)
Abstract Circular RNA (CircRNA) is a type of non-coding RNAs in which both ends are covalently linked. Researchers have demonstrated that many circRNAs can act as biomarkers of diseases. However, traditional experimental methods for circRNA-disease a
Externí odkaz:
https://doaj.org/article/e5738881f73c416c849805ad06923bec
Publikováno v:
IEEE Access, Vol 9, Pp 19208-19218 (2021)
Generative Adversarial Networks (GANs) are a powerful subclass of generative models. Yet, how to effectively train them to reach Nash equilibrium is a challenge. A number of experiments have indicated that one possible solution is to bound the functi
Externí odkaz:
https://doaj.org/article/b1d4db230d804e86ae0a365f163a2562
Publikováno v:
Information, Vol 13, Iss 3, p 110 (2022)
In order to facilitate designers to explore the market demand trend of laptops and to establish a better “network users-market feedback mechanism”, we propose a design and research method of a short text mining tool based on the K-means clusterin
Externí odkaz:
https://doaj.org/article/96c70ff14c474306b1181511acc09d06
Autor:
MANZOOR, MUHAMMAD ARSLAN, ALBARRI, SARAH, ZITING XIAN, ZAIQIAO MENG, NAKOV, PRESLAV, SHANGSONG LIANG
Publikováno v:
ACM Transactions on Multimedia Computing, Communications & Applications; Mar2024, Vol. 20 Issue 3, p1-34, 34p
Publikováno v:
ACM Transactions on the Web. 17:1-34
Conversational Recommendation Systems (CRSs) aim to improve recommendation performance by utilizing information from a conversation session. A CRS first constructs questions and then asks users for their feedback in each conversation session to refin
Publikováno v:
ACM Transactions on the Web; Nov2023, Vol. 17 Issue 4, p1-31, 31p
Publikováno v:
Proceedings of the AAAI Conference on Artificial Intelligence. 36:5530-5538
Learning effective representations of entities and relations for knowledge graphs (KGs) is critical to the success of many multi-relational learning tasks. Existing methods based on graph neural networks learn a deterministic embedding function, whic
Publikováno v:
Database Systems for Advanced Applications ISBN: 9783031306716
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5cc275cb472c481690392e36b11a5d4c
https://doi.org/10.1007/978-3-031-30672-3_38
https://doi.org/10.1007/978-3-031-30672-3_38
Publikováno v:
IEEE Transactions on Neural Networks and Learning Systems. :1-15
In this article, we study the problem of embedding temporal attributed networks, with the goal of which is to learn dynamic low-dimensional representations over time for temporal attributed networks. Existing temporal network embedding methods only l