期刊：
INTERNATIONAL JOURNAL OF DATA MINING AND BIOINFORMATICS,2016年15(2):125-144 ISSN：1748-5673
通讯作者：
Guo, Xiyue
作者机构：
[Guo, Xiyue] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;[Guo, Xiyue] Xingyi Normal Univ Nationalities, Sch Informat Technol, Xingyi, Peoples R China.;[He, Tingting] Cent China Normal Univ, Sch Comp, Nat Language Proc Lab, Wuhan, Peoples R China.;[Xing, Ying] Zhongyuan Univ Technol, Software Coll, Zhengzhou, Peoples R China.
通讯机构：
[Guo, Xiyue] C;[Guo, Xiyue] X;Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Peoples R China.;Xingyi Normal Univ Nationalities, Sch Informat Technol, Xingyi, Peoples R China.
关键词：
PPI extraction;weakly supervised;word dictionary construction;rule learning
摘要：
Each method, machine learning-based and rule-based, for extracting PPI (Protein-Protein Interactions) from biomedical literatures has advantages and disadvantages. In order to utilise the superiorities of these methods reasonably, this paper designs a new structure for the relational word dictionary, uses weakly supervised method to find dictionary items and fill them into the PPI relational word dictionary, and presents a method to learn PPI relational rules automatically based on slot-filling principle. Moreover, this method takes the PPI relation instances without apparent relational words into consideration aiming to improve the final performance. We conduct the experiments with five authoritative biomedical PPI corpuses, and discover some distribution features about PPI relational words. Finally, we also compare our method with several recent research achievements, and the results show that the performance of our method is better than the average level among these methods.
摘要：
以全国教育科学规划立项课题、高等教育学专业博硕士研究生学位论文以及高等教育学领域核心期刊论文三类数据作为数据来源,基于词频分析法,借助Bicomb和Cite Space III,对2009-2014年间高等教育学的研究重点进行多角度分析,结果表明:教学评估、素质教育、彰显特色、推进马克思主义大众化、中国特色、深度合作、教授治学等是近6年的重点研究领域;立德树人、内部治理结构、经济发展方式、学术委员会、教授委员会成为高等教育学科的研究前沿。
作者机构：
Department of Information Management,Central China Normal University,Wuhan 430079,China
会议名称：
第十三届海峡两岸图书资讯学学术研讨会
会议时间：
2016-07-01
会议地点：
武汉
会议论文集名称：
第十三届海峡两岸图书资讯学学术研讨会 论文集
关键词：
Social Network;group recommendation;Time-hybrid group Recommendation;social relationship factor;similarity factor
摘要：
The existing recommender systems are most aimed at single users,rather than groups.A group in social networks is characterized by complexity and diversity,so the traditional group recommender algorithms(GRAs)are unable to adapt to social networks.Therefore,we proposed a time-factor-based hybrid GRA for personalized Weibo recommendation on social networks.The new algorithm comprehensively considers the between-user interaction and determines the importance degree of a microblog through extraction of current context information.Moreover,it considers the between-group relation structure and interests also change with time.Here the real data from Sina Weibo were used in test and evaluation.The new algorithm outperforms the existing algorithms in Weibo group recommendation.
作者机构：
[Xiao, Yi] Cent China Normal Univ, Sch Informat Management, Wuhan, Peoples R China.;[Wang, Shouyang] Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China.;[Liu, John J.] City Univ Hong Kong, Ctr Transport Trade & Financial Studies, Hong Kong, Hong Kong, Peoples R China.;[Xiao, Jin] Sichuan Univ, Sch Business, Chengdu 610064, Peoples R China.;[Hu, Yi] Univ Chinese Acad Sci, Sch Management, Beijing, Peoples R China.
通讯机构：
[Hu, Yi] U;Univ Chinese Acad Sci, Sch Management, Beijing, Peoples R China.
关键词：
port development and management;policies analysis;container throughput estimation
摘要：
With the rapid growth of seaborne commodity trades, port development and management has become a challenging issue to the government, enterprise and academia. To alleviate pressures on spatial demand and the environment, sustainable development and scientific management of a port is of crucial importance for its investment, construction and operation. In this article, a research path based on throughput estimation is proposed. The container port of Tianjin could expect to face immense, increasing pressure in the future several years. To meet future increasing capacity requirement, constructing new waterway and berths in a bigger contiguous area or new locations becomes a crucial strategy. Moreover, the strategy of accommodating peak seasonal traffic means existing container terminals have to attain higher output by redesigning their high-precision schedule, reconfiguring terminal topology, improving worker efficiency and employing more modern container-handling facilities.
