G Parthasarathy, Lakshmanan L, Ramanathan L
Department of Computer Science and Engineering, Jeppiaar Maamallan Engineering College, Anna University, Chennai, India. Email:
Department of Computer Science and Engineering,, Sathyabama Institute of Science and Technology, Chennai, India.
Asian Pac J Cancer Prev. 2019 Mar 26;20(3):951-960. doi: 10.31557/APJCP.2019.20.3.951.
Objective: In recent years, citation analysis tools provide many devices for finding or computing the citation score or impact factor for journals. It is important for the researchers to identify good journals for collecting research ideas discussed. A journal with a good impact factor value is preferably referred to by many researchers. In this research work, the author proposes a system for ranking journals on the basis of ideas and results cited in other papers. Methods: The work involves the cited content extractor for extracting the descriptive features mentioned about the cited paper. The cited content refers to the content in the article written by a citing paper and relating to the cited paper. The ranking system uses a citation score estimator for computing the overall weight of the descriptive cited content relating to a specific paper in the citing papers. The journal ranking system performs classification of the citation content with the evaluation of a citation score. The work that involves the citation content is classified under different categories as positively cited, negatively cited or neutral and unrelated. Results: Then the computed citation score is used for ranking the dealing with research on cancer research journals. The results of the ranking journals indicate that the particular ranked journal has been cited in the literature of many journals with a good descriptive content. Journal ranking system can be considered as a well-organized tool for ranking the cancer research scientific journal based on citation content and citation counting. Conclusion: This experimental cancer journal ranking method increases accuracy and effectiveness by using the citation content when compared with PageRank and HITS.
近年来，引文分析工具为查找或计算期刊的引文得分或影响因子提供了许多手段。对于研究人员来说，识别用于收集所讨论研究思路的优秀期刊非常重要。具有良好影响因子值的期刊更受许多研究人员的青睐。在这项研究工作中，作者提出了一种基于其他论文中引用的思路和结果对期刊进行排名的系统。方法：这项工作涉及引用内容提取器，用于提取关于被引论文提及的描述性特征。被引内容是指引用论文中与被引论文相关的文章内容。排名系统使用引文得分估计器来计算与引用论文中特定论文相关的描述性被引内容的总体权重。期刊排名系统通过评估引文得分对引文内容进行分类。涉及引文内容的工作被分类为正引用、负引用或中性及不相关等不同类别。结果：然后，计算出的引文得分用于对癌症研究期刊的研究进行排名。期刊排名结果表明，特定排名的期刊在许多具有良好描述性内容的期刊文献中被引用。期刊排名系统可被视为一种基于引文内容和引文计数对癌症研究科学期刊进行排名的组织良好的工具。结论：与PageRank和HITS相比，这种实验性癌症期刊排名方法通过使用引文内容提高了准确性和有效性。
