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Main Content Extraction from Web Pages Based on Node Characteristics
Qingtang Liu,Mingbo Shao,Linjing Wu,Gang Zhao,Guilin Fan,Jun Li 한국정보과학회 2017 Journal of Computing Science and Engineering Vol.11 No.2
Main content extraction of web pages is widely used in search engines, web content aggregation and mobile Internet browsing. However, a mass of irrelevant information such as advertisement, irrelevant navigation and trash information is included in web pages. Such irrelevant information reduces the efficiency of web content processing in content-based applications. The purpose of this paper is to propose an automatic main content extraction method of web pages. In this method, we use two indicators to describe characteristics of web pages: text density and hyperlink density. According to continuous distribution of similar content on a page, we use an estimation algorithm to judge if a node is a content node or a noisy node based on characteristics of the node and neighboring nodes. This algorithm enables us to filter advertisement nodes and irrelevant navigation. Experimental results on 10 news websites revealed that our algorithm could achieve a 96.34% average acceptable rate.
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Main Content Extraction from Web Pages Based on Node Characteristics
Liu, Qingtang,Shao, Mingbo,Wu, Linjing,Zhao, Gang,Fan, Guilin,Li, Jun Korean Institute of Information Scientists and Eng 2017 Journal of Computing Science and Engineering Vol.11 No.2
Main content extraction of web pages is widely used in search engines, web content aggregation and mobile Internet browsing. However, a mass of irrelevant information such as advertisement, irrelevant navigation and trash information is included in web pages. Such irrelevant information reduces the efficiency of web content processing in content-based applications. The purpose of this paper is to propose an automatic main content extraction method of web pages. In this method, we use two indicators to describe characteristics of web pages: text density and hyperlink density. According to continuous distribution of similar content on a page, we use an estimation algorithm to judge if a node is a content node or a noisy node based on characteristics of the node and neighboring nodes. This algorithm enables us to filter advertisement nodes and irrelevant navigation. Experimental results on 10 news websites revealed that our algorithm could achieve a 96.34% average acceptable rate.
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Homologous tumor cell membrane vesicles active preferential self‑recognition of tumor cells in vitro
Wu Chenghu,Yu Ailin,Chen Yue,Fan Mingbo 한국응용생명화학회 2022 Applied Biological Chemistry (Appl Biol Chem) Vol.65 No.1
Cell membrane vesicles, as delivery carriers of drugs or biological agents in vivo, are an important therapeutic mode in the study of disease treatment. Tumor membrane-derived vesicles have been widely used in tumor therapy because of their good tumor enrichment effect. The most common method is the surface of nanoparticles coated with tumor cell membrane, which can effectively prolong the circulation time of particles in the blood and the enrichment of tumors. In this study, we prepared vesicles of different tumor cell membrane derivate and studied their targeting to tumors detailly. The results showed that homologous vesicles have high targeting to homologous tumor cells. The fluorescence of vesicles in homologous tumor cells was significantly higher than that in other tumor cells. This study will provide a new strategy and guidance for the clinical treatment of cancer based on the tumor cell membrane system.
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