Zobrazeno 1 - 8
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pro vyhledávání: '"Changping Meng"'
Dissertation/ Thesis
Autor:
Changping Meng (8802956)
In many complex domains, the input data are often not suited for the typical vector representations used in deep learning models. For example, in knowledge representation, relational learning, and some computer vision tasks, the data are often better
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030454388
Analyzing the readability of articles has been an important sociolinguistic task. Addressing this task is necessary to the automatic recommendation of appropriate articles to readers with different comprehension abilities, and it further benefits edu
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2db32c1081fc6ed07e7b8e119f53e7fb
https://doi.org/10.1007/978-3-030-45439-5_3
https://doi.org/10.1007/978-3-030-45439-5_3
Autor:
Changping Meng
In many complex domains, the input data are often not suited for the typical vector representations used in deep learning models. For example, in knowledge representation, relational learning, and some computer vision tasks, the data are often better
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ecf27fd09dd700817f803f32f2d302f
Publikováno v:
IEEE BigData
Current Wikipedia editing approaches typically summarize a named entity by one main-article supplemented by multiple sub-articles describing various aspects and subtopics of the entity. Such separation of articles aims at improving the curation of co
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::929c61b31738d532e222452eaa604839
https://doi.org/10.1109/bigdata47090.2019.9005578
https://doi.org/10.1109/bigdata47090.2019.9005578
Publikováno v:
KDD
In many complex domains, the input data are often not suited for the typical vector representations used in deep learning models. For example, in relational learning and computer vision tasks, the data are often better represented as sets (e.g., the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52b1523d5d37987e9ca240025c4caa44
https://doi.org/10.1145/3292500.3330876
https://doi.org/10.1145/3292500.3330876
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030109967
ECML/PKDD (3)
ECML/PKDD (3)
Nowadays, editors tend to separate different subtopics of a long Wiki-pedia article into multiple sub-articles. This separation seeks to improve human readability. However, it also has a deleterious effect on many Wikipedia-based tasks that rely on t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::93df14a5752627b2ef283db027b2b21d
https://doi.org/10.1007/978-3-030-10997-4_1
https://doi.org/10.1007/978-3-030-10997-4_1
Publikováno v:
WWW
WWW, May 2015, Florence, Italy
WWW, May 2015, Florence, Italy
International audience; The Heterogeneous Information Network (HIN) is a graph data model in which nodes and edges are annotated with class and relationship labels. Large and complex datasets, such as Yago or DBLP, can be modeled as HINs. Recent work
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::372e80190e8e4a06d655f85922b52653
https://doi.org/10.1145/2736277.2741123
https://doi.org/10.1145/2736277.2741123