Zobrazeno 1 - 10
of 502
pro vyhledávání: '"Subgraph mining"'
Publikováno v:
PeerJ Computer Science, Vol 10, p e2361 (2024)
Frequent subgraph mining (FSM) is an essential and challenging graph mining task used in several applications of the modern data science. Some of the FSM algorithms have the objective of finding all frequent subgraphs whereas some of the algorithms f
Externí odkaz:
https://doaj.org/article/adf9017876054ccaaa8f05d3589299e1
Autor:
Leng, Yilin a, b, 1, Cui, Wenju a, b, 1, Chen, Bai a, b, Jiang, Xi c, Peng, Yunsong d, Zheng, Jian a, b, e, ⁎
Publikováno v:
In Expert Systems With Applications 10 March 2025 264
Autor:
Basak Buluz Komecoglu, Burcu Yilmaz
Publikováno v:
IEEE Access, Vol 12, Pp 105613-105632 (2024)
In an era of exponential growth in online news sources, the need for intelligent digital solutions capable of efficiently analyzing and organizing large amounts of news content has become crucial. This paper presents a graph-based methodology designe
Externí odkaz:
https://doaj.org/article/e58fdad89b0c4add91042b0c2dbb4f6a
Publikováno v:
Applied Sciences, Vol 14, Iss 6, p 2456 (2024)
Lesion prediction, a very important aspect of cancer disease prediction, is an important marker for patients before they become cancerous. Currently, traditional machine learning methods are gradually applied in disease prediction based on patient vi
Externí odkaz:
https://doaj.org/article/05da8f91c98e44c59b02344b947a27bb
Publikováno v:
Mathematics, Vol 12, Iss 6, p 916 (2024)
Inductive Logic Programming (ILP) is a research field at the intersection between machine learning and logic programming, focusing on developing a formal framework for inductively learning relational descriptions in the form of logic programs from ex
Externí odkaz:
https://doaj.org/article/de4373cfda9d44c281802e9d40792d6c
Publikováno v:
IEEE Access, Vol 10, Pp 131747-131764 (2022)
Applications such as providing a preview of personal albums (e.g., Google Photos) or suggesting thematic collections based on user interests (e.g., Pinterest) require a semantically-enriched image representation, which should be more informative with
Externí odkaz:
https://doaj.org/article/b6c8d95c7d6844eab89e3dfd3e05dbc7
Publikováno v:
Dianxin kexue, Vol 37, Pp 51-63 (2021)
Fault diagnosis is one of the most challenging tasks in power communication.The fault diagnosis based on rules can no longer meet the demand of massive alarms processing.The existing approaches based on the supervised learning need large sets of the
Externí odkaz:
https://doaj.org/article/d15be2dc595c4296ae82d3bdba0c6987
Publikováno v:
Applied Sciences, Vol 13, Iss 18, p 10041 (2023)
Recommender systems play a crucial role in personalizing online user experiences by creating user profiles based on user–item interactions and preferences. Knowledge graphs (KGs) are intricate data structures that encapsulate semantic information,
Externí odkaz:
https://doaj.org/article/f31b112dc5244cc196bc1fd81a89adb1
Autor:
Tianyu Zheng, Li Wang
Publikováno v:
IEEE Access, Vol 9, Pp 88970-88980 (2021)
Large graph networks frequently appear in the latest applications. Their graph structures are very large, and the interaction among the vertices makes it difficult to split the structures into separate multiple structures, thus increasing the difficu
Externí odkaz:
https://doaj.org/article/c2d0829998aa4aecb822fd244cfd1b44
Publikováno v:
Frontiers in Neuroscience, Vol 16 (2022)
The brain network structure is highly uncertain due to the noise in imaging signals and evaluation methods. Recent works have shown that uncertain brain networks could capture uncertain information with regards to functional connections. Most of the
Externí odkaz:
https://doaj.org/article/bbea5b2303fa441fad8eb055aabac647