A retrospective of knowledge graphs
Abstract Information on the Internet is fragmented and presented in different data sources,
which makes automatic knowledge harvesting and understanding formidable for machines …
which makes automatic knowledge harvesting and understanding formidable for machines …
Evaluating the state of the art in coreference resolution for electronic medical records
Background The fifth i2b2/VA Workshop on Natural Language Processing Challenges for
Clinical Records conducted a systematic review on resolution of noun phrase coreference in …
Clinical Records conducted a systematic review on resolution of noun phrase coreference in …
Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies
B Cope, M Kalantzis, D Searsmith - Educational philosophy and …, 2021 - Taylor & Francis
Over the past ten years, we have worked in a collaboration between educators and
computer scientists at the University of Illinois to imagine futures for education in the context …
computer scientists at the University of Illinois to imagine futures for education in the context …
[PDF][PDF] Combining Knowledge with Deep Convolutional Neural Networks for Short Text Classification.
Text classification is a fundamental task in NLP applications. Most existing work relied on
either explicit or implicit text representation to address this problem. While these techniques …
either explicit or implicit text representation to address this problem. While these techniques …
KBQA: learning question answering over QA corpora and knowledge bases
Question answering (QA) has become a popular way for humans to access billion-scale
knowledge bases. Unlike web search, QA over a knowledge base gives out accurate and …
knowledge bases. Unlike web search, QA over a knowledge base gives out accurate and …
Probase: A probabilistic taxonomy for text understanding
Knowledge is indispensable to understanding. The ongoing information explosion highlights
the need to enable machines to better understand electronic text in human language. Much …
the need to enable machines to better understand electronic text in human language. Much …
Deep feature-based text clustering and its explanation
R Guan, H Zhang, Y Liang, F Giunchiglia… - … on Knowledge and …, 2020 - ieeexplore.ieee.org
Text clustering is a critical step in text data analysis and has been extensively studied by the
text mining community. Most existing text clustering algorithms are based on the bag-of …
text mining community. Most existing text clustering algorithms are based on the bag-of …
Combining context-relevant features with multi-stage attention network for short text classification
Y Liu, P Li, X Hu - Computer Speech & Language, 2022 - Elsevier
Short text classification is a challenging task in natural language processing. Existing
traditional methods using external knowledge to deal with the sparsity and ambiguity of short …
traditional methods using external knowledge to deal with the sparsity and ambiguity of short …
[图书][B] Sentic computing: Techniques, tools, and applications
In this book common sense computing techniques are further developed and applied to
bridge the semantic gap between word-level natural language data and the concept-level …
bridge the semantic gap between word-level natural language data and the concept-level …
Understanding the recent trend of haze pollution in eastern China: roles of climate change
HJ Wang, HP Chen - Atmospheric Chemistry and Physics, 2016 - acp.copernicus.org
In this paper, the variation and trend of haze pollution in eastern China for winter of 1960–
2012 were analyzed. With the overall increasing number of winter haze days in this period …
2012 were analyzed. With the overall increasing number of winter haze days in this period …