Zobrazeno 1 - 9
of 9
pro vyhledávání: '"Selasi Kwashie"'
Autor:
Michael Bewong, John Wondoh, Selasi Kwashie, Jixue Liu, Lin Liu, Jiuyong Li, Md. Zahidul ISLAM, David Kernot
Publikováno v:
IEEE Access, Vol 11, Pp 32826-32841 (2023)
Topic modelling is important for tackling several data mining tasks in information retrieval. While seminal topic modelling techniques such as Latent Dirichlet Allocation (LDA) have been proposed, the ubiquity of social media and the brevity of its t
Externí odkaz:
https://doaj.org/article/9a948d9d955d450080e1f581434d9703
Autor:
Zaiwen Feng, Wolfgang Mayer, Keqing He, Selasi Kwashie, Markus Stumptner, Georg Grossmann, Rong Peng, Wangyu Huang
Publikováno v:
IEEE Access, Vol 9, Pp 5609-5639 (2021)
Knowledge Graphs (KGs), as one of the key trends which are driving the next wave of technologies, have now become a new form of knowledge representation, and a cornerstone for several applications from generic to specific industrial use cases. Howeve
Externí odkaz:
https://doaj.org/article/6989adcf8e0e4b0db44ce6710a2c0abf
Autor:
Vincent Mwintieru Nofong, Priscilla Owiredu Okai, Hamidu Abdel-Fatao, Selasi Kwashie, Michael Bewong, John Wondoh
Publikováno v:
2022 IEEE International Conference on Data Mining Workshops (ICDMW).
Finding High Utility Itemsets (HUls) in databases is crucial for identifying items that are of high importance (like profit) for decision-making. However, current High Utility Itemset Mining (HUIM) algorithms often ignore the interest or target of us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0325fd961a59da823e39e4e688687458
https://doi.org/10.1109/icdmw58026.2022.00073
https://doi.org/10.1109/icdmw58026.2022.00073
Autor:
Wolfgang Mayer, Rong Peng, Georg Grossmann, Markus Stumptner, Zaiwen Feng, Keqing He, Wangyu Huang, Selasi Kwashie
Publikováno v:
IEEE Access, Vol 9, Pp 5609-5639 (2021)
Knowledge Graphs (KGs), as one of the key trends which are driving the next wave of technologies, have now become a new form of knowledge representation, and a cornerstone for several applications from generic to specific industrial use cases. Howeve
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5cf96b5a5576385cb8cf458961ee7219
https://doi.org/10.1109/access.2020.3048186
https://doi.org/10.1109/access.2020.3048186
Autor:
Markus Stumptner, Wolfgang Mayer, Keqing He, Georg Grossmann, Selasi Kwashie, Zaiwen Feng, Da Ning
Publikováno v:
SERVICES
Refereed/Peer-reviewed Traditionally the integration of data from multiple sources is done on an ad-hoc basis for each analysis scenario and application. This is an approach that is inflexible, incurs high costs, and leads to 'silos' that prevent sha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::30c7b3f82eb567073d6b63d85e02aefb
https://doi.org/10.1109/services51467.2021.00033
https://doi.org/10.1109/services51467.2021.00033
Entity resolution (ER) is the problem of accurately identifying multiple, differing, and possibly contradicting representations of unique real-world entities in data. It is a challenging and fundamental task in data cleansing and data integration. In
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::64554a808b06970f67e62cffa333a2a0
https://hdl.handle.net/11541.2/137224
https://hdl.handle.net/11541.2/137224
Publikováno v:
Advances in Databases and Information Systems ISBN: 9783319231341
ADBIS
ADBIS
Differential dependency (DD) is a newly proposed data dependency theory that captures the relationships amongst data values. Like the classical functional dependency (FD) theory, DDs are defined to hold over entire instances of relations. This paper
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e21d43b3c4120879549b1b8a2db0ee9a
https://doi.org/10.1007/978-3-319-23135-8_1
https://doi.org/10.1007/978-3-319-23135-8_1
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783319086071
ADC
ResearcherID
ADC
ResearcherID
The discovery of differential dependencies (DDs) is the problem of finding a minimal cover set of DDs that hold in a given relation. This paper proposes a novel subspace-clustering-based approach to mine DDs that exist in a given relation. We study a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90dc72bbfbb79e90bbfe8c1e90ceb8be
https://doi.org/10.1007/978-3-319-08608-8_5
https://doi.org/10.1007/978-3-319-08608-8_5
Publikováno v:
Scopus-Elsevier
Charles Sturt University
Charles Sturt University
Entity linking and resolution is a fundamental database problem with applications in data integration, data cleansing, information retrieval, knowledge fusion, and knowledge-base population. It is the task of accurately identifying multiple, differin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f36a22d12707ede4a16c3b8036a8fdd
http://www.scopus.com/inward/record.url?eid=2-s2.0-85072734549&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-85072734549&partnerID=MN8TOARS