94 hasil untuk "Lin, Hongfei"

A Multiple Relevance Feedback Strategy with Positive and Negative Models

Ma, Yunlong; Lin, Hongfei

PLoS One · 2014 · Inggris · PubMed Central

A commonly used strategy to improve search accuracy is through feedback techniques. Most existing work on feedback relies on positive information, and has been extensively studied in information retrieval. However, when a query topic is difficult and the results from the first-pass retrieval are…

Transfer Learning Oriented Text Feature Alignment Algorithm

WEI Xiaocong,LIN Hongfei

Jisuanji gongcheng, Vol. 43 No. 2 · 2017 · Tionghoa · DOAJ Scopus

The inconsistency between source domain and target domain feature spaces results in accuracy decline of transfer learning.To resolve this problem,this paper proposes a different domain feature alignment method based on Word2Vec.Adjectives,adverbs,nouns and verbs are selected as features.Pivot…

Ontology integration to identify protein complex in protein interaction networks

Xu, Bo; Lin, Hongfei; Yang, Zhihao

Proteome Sci · 2011 · Inggris · PubMed Central

BACKGROUND: Protein complexes can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein…

Incorporating rich background knowledge for gene named entity classification and recognition

Li, Yanpeng; Lin, Hongfei; Yang, Zhihao

BMC Bioinformatics · 2009 · Inggris · PubMed Central

BACKGROUND: Gene named entity classification and recognition are crucial preliminary steps of text mining in biomedical literature. Machine learning based methods have been used in this area with great success. In most state-of-the-art systems, elaborately designed lexical features, such as words…

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Learning an enriched representation from unlabeled data for protein-protein interaction extraction

Li, Yanpeng; Hu, Xiaohua; Lin, Hongfei dkk.

BMC Bioinformatics · 2010 · Inggris · PubMed Central

BACKGROUND: Extracting protein-protein interactions from biomedical literature is an important task in biomedical text mining. Supervised machine learning methods have been used with great success in this task but they tend to suffer from data sparseness because of their restriction to obtain…

Enhancing Biomedical Text Summarization Using Semantic Relation Extraction

Shang, Yue; Li, Yanpeng; Lin, Hongfei dkk.

PLoS One · 2011 · Inggris · PubMed Central

Automatic text summarization for a biomedical concept can help researchers to get the key points of a certain topic from large amount of biomedical literature efficiently. In this paper, we present a method for generating text summary for a given biomedical concept, e.g., H1N1 disease, from…

Construction of Ontology Augmented Networks for Protein Complex Prediction

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao dkk.

PLoS One · 2013 · Inggris · PubMed Central

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most…

A document level neural model integrated domain knowledge for chemical-induced disease relations

Zheng, Wei; Lin, Hongfei; Liu, Xiaoxia dkk.

BMC Bioinformatics · 2018 · Inggris · PubMed Central

BACKGROUND: The effective combination of texts and knowledge may improve performances of natural language processing tasks. For the recognition of chemical-induced disease (CID) relations which may span sentence boundaries in an article, although existing CID systems explored the utilization for…

Document triage for identifying protein–protein interactions affected by mutations: a neural network ensemble approach

Luo, Ling; Yang, Zhihao; Lin, Hongfei dkk.

Database (Oxford) · 2018 · Inggris · PubMed Central

The precision medicine (PM) initiative promises to identify individualized treatment depending on a patients’ genetic profile and their related responses. In order to help health professionals and researchers in the PM endeavor, BioCreative VI organized a PM Track to mine protein–protein…

Construction of dynamic probabilistic protein interaction networks for protein complex identification

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao dkk.

BMC Bioinformatics · 2016 · Inggris · PubMed Central

BACKGROUND: Recently, high-throughput experimental techniques have generated a large amount of protein-protein interaction (PPI) data which can construct large complex PPI networks for numerous organisms. System biology attempts to understand cellular organization and function by analyzing these…

Learning to rank-based gene summary extraction

Shang, Yue; Hao, Huihui; Wu, Jiajin dkk.

BMC Bioinformatics · 2014 · Inggris · PubMed Central

BACKGROUND: In recent years, the biomedical literature has been growing rapidly. These articles provide a large amount of information about proteins, genes and their interactions. Reading such a huge amount of literature is a tedious task for researchers to gain knowledge about a gene. As a result…

Integrating experimental and literature protein-protein interaction data for protein complex prediction

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao dkk.

BMC Genomics · 2015 · Inggris · PubMed Central

BACKGROUND: Accurate determination of protein complexes is crucial for understanding cellular organization and function. High-throughput experimental techniques have generated a large amount of protein-protein interaction (PPI) data, allowing prediction of protein complexes from PPI networks…

Supervised Learning Based Hypothesis Generation from Biomedical Literature

Sang, Shengtian; Yang, Zhihao; Li, Zongyao dkk.

Biomed Res Int · 2015 · Inggris · PubMed Central

Nowadays, the amount of biomedical literatures is growing at an explosive speed, and there is much useful knowledge undiscovered in this literature. Researchers can form biomedical hypotheses through mining these works. In this paper, we propose a supervised learning based approach to generate…

Drug–target interaction prediction using knowledge graph embedding

Li, Nan; Yang, Zhihao; Wang, Jian dkk.

iScience · 2024 · Inggris · PubMed Central

The prediction of drug-target interactions (DTIs) is a critical phase in the sustainable drug development process, especially when the research focus is to capitalize on the repositioning of existing drugs. Computational approaches to predicting DTIs can provide important insights into drug…

Improving Human Happiness Analysis Based on Transfer Learning: Algorithm Development and Validation

Yu, Lele; Zhang, Shaowu; Zhang, Yijia dkk.

JMIR Med Inform · 2021 · Inggris · PubMed Central

BACKGROUND: Happiness refers to the joyful and pleasant emotions that humans produce subjectively. It is the positive part of emotions, and it affects the quality of human life. Therefore, understanding human happiness is a meaningful task in sentiment analysis. OBJECTIVE: We mainly discuss 2…

Nanoparticle/Metal–Organic Framework Composites for Catalytic Applications: Current Status and Perspective

Xiang, Wenlong; Zhang, Yueping; Lin, Hongfei dkk.

Molecules · 2017 · Inggris · PubMed Central

Nanoparticle/metal–organic frameworks (MOF) based composites have recently attracted significant attention as a new class of catalysts. Such composites possess the unique features of MOFs (including clearly defined crystal structure, high surface area, single site catalyst, special confined…

Minimal Kinetic Model of Direct Air Capture of CO(2) by Supported Amine Sorbents in Dry and Humid Conditions

Liu, Hongjun; Lin, Hongfei; Dai, Sheng dkk.

Ind Eng Chem Res · 2024 · Inggris · PubMed Central

[Image: see text] Dilute concentration (∼400 ppm) and humidity are two important factors in the direct air capture (DAC) of CO(2) by supported sorbents. In this work, a minimal DAC CO(2) adsorption-kinetics model was formulated for supported amine sorbents under dry and humid conditions. Our model…

Segmented Summarization Model for Legal Documents

WANG Gang, SUN Yuanyuan, CHEN Yanguang, LIN Hongfei

Jisuanji gongcheng, Vol. 48 No. 6 · 2022 · Tionghoa · DOAJ Scopus

Text summary refers to the process of summarization the content of text information, extracting the relevant content, and then formulating a summarization.Existing text summarization models usually analyze content selection and summarization generation separately.Although they can effectively…

Extracting Drug-Drug Interaction from the Biomedical Literature Using a Stacked Generalization-Based Approach

He, Linna; Yang, Zhihao; Zhao, Zhehuan dkk.

PLoS One · 2013 · Inggris · PubMed Central

Drug-drug interaction (DDI) detection is particularly important for patient safety. However, the amount of biomedical literature regarding drug interactions is increasing rapidly. Therefore, there is a need to develop an effective approach for the automatic extraction of DDI information from the…