Serialized Co-Training-Based Recognition of Medicine Names for Patent Mining and Retrieval

IF 0.5 4区计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING

International Journal of Data Warehousing and Mining Pub Date : 2020-07-01 DOI:10.4018/ijdwm.2020070105

Na Deng, Caiquan Xiong

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引用次数: 2

Abstract

IntheretrievalandminingoftraditionalChinesemedicine(TCM)patents,akeystepisChineseword segmentationandnamedentityrecognition.However,thealiasphenomenonoftraditionalChinese medicinescausesgreatchallengestoChinesewordsegmentationandnamedentityrecognitioninTCM patents,whichdirectlyaffectstheeffectofpatentmining.Becauseofthelackofacomprehensive Chineseherbalmedicinenamethesaurus,traditionalthesaurus-basedChinesewordsegmentation andnamedentityrecognitionarenotsuitableformedicineidentificationinTCMpatents.Inviewof thepresentsituation,usingthelanguagecharacteristicsandstructuralcharacteristicsofTCMpatent texts,amodifiedandserializedco-trainingmethodtorecognizemedicinenamesfromTCMpatent abstract texts isproposed.Experimentsshowthat thismethodcanmaintainhighaccuracyunder relativelylowtimecomplexity.Inaddition,thismethodcanalsobeexpandedtotherecognitionof othernamedentitiesinTCMpatents,suchasdiseasenames,preparationmethods,andsoon. KeyWoRDS Annotation, Co-Training, Machine Learning, Medicine Name, Patent Mining, Patent Retrieval, Traditional Chinese Medicine

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基于序列化协同训练的药品名称识别专利挖掘与检索

IntheretrievalandminingoftraditionalChinesemedicine(TCM)patents、akeystepisChineseword segmentationandnamedentityrecognition。However，thealiasphenomenonoftraditionalChinese medicinescausesgreatchallengestoChinesewordsegmentationandnamedentityrecognitioninTCM专利，whichdirectlyaffectstheeffectofpatentmining。Becauseofthelackofacomprehensive Chineseherbalmedicinenamethesaurus，traditionalthesaurus-basedChinesewordsegmentation andnamedentityrecognitionarenotsuitableformedicineidentificationinTCMpatents。Inviewof thepresentsituation，usingthelanguagecharacteristicsandstructuralcharacteristicsofTCMpatent texts，amodifiedandserializedco-trainingmethodtorecognizemedicinenamesfromTCMpatent abstracttexts.com isproposed。Experimentsshowthat thismethodcanmaintainhighaccuracyunder relativelylowtimecomplexity。Inaddition，thismethodcanalsobeexpandedtotherecognitionof othernamedentitiesinTCMpatents，suchasdiseasenames，preparationmethods，andsoon。关键词:标注，协同训练，机器学习，药物名称，专利挖掘，专利检索，中药

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来源期刊

International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

2.40

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving