Zobrazeno 1 - 10
of 18
pro vyhledávání: '"Yanru Qu"'
Publikováno v:
Nanoscale. 13:15-35
Lithium-sulfur (Li-S) batteries have shown great application prospects as next-generation energy storage systems due to their high theoretical capacity and high energy density. However, the practical application of Li-S batteries is still hindered by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::17b99b8ca0dfc21b257c6b7ad8f0eb48
https://doi.org/10.1039/d0nr06732f
https://doi.org/10.1039/d0nr06732f
Autor:
Guang Ning, Zhiyun Zhao, Yufang Bi, Jieli Lu, Min Xu, Weiqing Wang, Mingcheng Chen, Yanru Qu, Zhenghui Wang, Xiawei Guo, Yong Yu, Wei-Wei Tu, Jian Shen, Mian Li, Tiange Wang, Weinan Zhang, Yu Xu
Diabetes prediction is an important data science application in the social healthcare domain. There exist two main challenges in the diabetes prediction task: data heterogeneity since demographic and metabolic data are of different types, data insuff
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8acb25c74f47755182927e65245282e
http://arxiv.org/abs/2108.07107
http://arxiv.org/abs/2108.07107
Publikováno v:
NAACL-HLT
Grounding events into a precise timeline is important for natural language understanding but has received limited attention in recent work. This problem is challenging due to the inherent ambiguity of language and the requirement for information prop
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::19b219c4648c5b8970820b9c4cfd4753
https://doi.org/10.18653/v1/2021.naacl-main.6
https://doi.org/10.18653/v1/2021.naacl-main.6
Publikováno v:
Machine Learning and Knowledge Discovery in Databases ISBN: 9783030676575
ECML/PKDD (1)
ECML/PKDD (1)
With the rapid development in online education, knowledge tracing (KT) has become a fundamental problem which traces students’ knowledge status and predicts their performance on new questions. Questions are often numerous in online education system
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::02b3f8addca3935f070d4c8736e6334d
https://doi.org/10.1007/978-3-030-67658-2_18
https://doi.org/10.1007/978-3-030-67658-2_18
Publikováno v:
EMNLP (1)
While neural sequence learning methods have made significant progress in single-document summarization (SDS), they produce unsatisfactory results on multi-document summarization (MDS). We observe two major challenges when adapting SDS advances to MDS
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9f31fdccd23fd161c280d04c38ed4a12
https://doi.org/10.18653/v1/2020.emnlp-main.136
https://doi.org/10.18653/v1/2020.emnlp-main.136
Publikováno v:
ACL (1)
Text-based question answering (TBQA) has been studied extensively in recent years. Most existing approaches focus on finding the answer to a question within a single paragraph. However, many difficult questions require multiple supporting evidence fr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::9d18957f372b878e05636eb3c513bc63
http://arxiv.org/abs/1905.06933
http://arxiv.org/abs/1905.06933
This paper studies graph-based recommendation, where an interaction graph is constructed from historical records and is lever-aged to alleviate data sparsity and cold start problems. We reveal an early summarization problem in existing graph-based mo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b6b4040bcc236a6fedd972d8426ffefb
Autor:
Ken Chen, Liheng Chen, Weinan Zhang, Yanru Qu, Yong Yu, Zhenghui Wang, Lin Qiu, Shaodian Zhang
In graphs with rich texts, incorporating textual information with structural information would benefit constructing expressive graph embeddings. Among various graph embedding models, random walk (RW)-based is one of the most popular and successful gr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::19544665b9b932c418eccfeba3241e98
http://arxiv.org/abs/1809.04234
http://arxiv.org/abs/1809.04234
Autor:
Minzhe Niu, Xiuqiang He, Ruiming Tang, Huifeng Guo, Weinan Zhang, Yong Yu, Bohui Fang, Yanru Qu
User response prediction is a crucial component for personalized information retrieval and filtering scenarios, such as recommender system and web search. The data in user response prediction is mostly in a multi-field categorical format and transfor
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::31a72c9469aa1a2a9bc195cd13ecfc4f
http://arxiv.org/abs/1807.00311
http://arxiv.org/abs/1807.00311
Autor:
Suoheng Li, Dongyu Ru, Yanru Qu, Lin Qiu, Hao Zhou, Kewei Tu, Lihua Qian, Yong Yu, Weinan Zhang, Shu Rong
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030006709
ISWC (1)
ISWC (1)
Information Extraction (IE) refers to automatically extracting structured relation tuples from unstructured texts. Common IE solutions, including Relation Extraction (RE) and open IE systems, can hardly handle cross-sentence tuples, and are severely
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c5497449b1e152d4e925c1d0ee3aa2df
https://doi.org/10.1007/978-3-030-00671-6_12
https://doi.org/10.1007/978-3-030-00671-6_12