[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-85383-en":3,"doc-seo-85383-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},85383,1099513958607,"Jiven","https://ap-avatar.wpscdn.com/avatar/100002390cf8733938c?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778829742770036399",8,"Research & Report","Research on Intellectual Property Resource Profile and Evolution Law","In the big-data era, intellectual property–oriented scientific and technological resources exhibit large-scale data volume, high information density, and low value density, creating obstacles to effective utilization and increasing the need to mine hidden information. The document presents a research focus on intellectual property resource portraits and evolution analysis. It organizes construction methods for such portraits and preliminary work, including property entity extraction and entity completion, covering algorithm classification and overall workflows, and outlines future improvement directions.","Research on Intellectual Property Resource Profile and Evolution  \nLaw  \nYuhui Wang  \nBeijing Key Laboratory of Intelligent Communication Software and Multimedia, School of Computer, Beijing University of Posts and Telecommunications (National Demonstration Software School) Beijing, China  \nYingxia Shao∗ Beijing Key Laboratory of Intelligent Communication Software and Multimedia, School of Computer, Beijing University of Posts and Telecommunications (National Demonstration Software School) Beijing, China [shaoyx@bupt.edu.cn](shaoyx@bupt.edu.cn)  \nAng Li  \nBeijing Key Laboratory of Intelligent Communication Software and Multimedia, School of Computer, Beijing University of Posts and Telecommunications (National Demonstration Software School) Beijing, China  \narXiv :2204 .0622 1v2 [ cs .DL] 11 Jul 2026  \nAbstract  \nIn the era of big data, intellectual property-oriented scientific and technological resources show the trend of large data scale, high information density, and low value density, which brings severe challenges to the effective use of intellectual property resources, and the demand for mining hidden information in intellectual property is increasing. This makes intellectual property-oriented science and technology resource portraits and analysis of evolution become a current research hotspot. This paper sorts out the construction method of intellectual property resource portraits and its preliminary work, including property entity extraction and entity completion, from the aspects of algorithm classification and general process, and identifies directions for improving future methods.  \nKeywords  \nintellectual property, resource profile, named entity recognition, evolution analysis, deep learning  \n1 Introduction  \nAs the most important information carrier and knowledge source of research results and technological innovation, patents are the main object of intellectual property analysis. The research on intellectual property in this paper also focuses on patents. With the rapid development of science and technology and the acceleration of technological iteration, the number of patents has exploded. Analysis and mining of intellectual property resources mainly based on patents can extract technology concepts, technology application fields, and other information from a large amount of patent data, and then reveal the development status and trends of technology. This helps enterprises identify technology opportunities [1], seize market opportunities [2], adjust claims to improve authorization opportunities [3], and enhance their core competitiveness. Interpretable machine-learning models also provide a way to connect extracted evidence with intelligent managerial decisions [4] .  \nPatent literature requires a strong professional background to understand, and its analysis mostly relies on patent analysts [5] . With the rapid increase in the number of patents, interdisciplinary technologies continue to emerge, and it is difficult to understand technological development quickly and comprehensively through manual analysis alone. Patents contain a large number of specialized words  \n∗ Corresponding author.  \nand technical terms, characterized by precise language, complex semantic information, and high information density, which challenges the accurate extraction of key information. At the same time, there are complex and rich connections among intellectual property entities such as technical concepts, applicants, and involved fields. Changes in these relationships can reflect fine-grained changes and development in intellectual property. When traditional patent analysis and data-mining methods analyze important information such as technical concepts and research topics, there is serious loss and fragmentation of semantic information [6] . These methods also make insufficient use of relationships among intellectual property entities, making it difficult to capture the development and change of intellectual property in subdivided","cbCaifBP3DPGOLTt","https://ap.wps.com/l/cbCaifBP3DPGOLTt","pdf",383338,2,1,5,"English","en",105,"# Introduction\n# Research on Intellectual Property Resource Profiles\n## Entity extraction method","[{\"question\":\"What motivates the need for intellectual property resource portraits and evolution analysis?\",\"answer\":\"Big-data conditions lead to large-scale, high-density intellectual property data but low value density, making effective use difficult. 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The increasing demand is to mine hidden information and understand technology evolution more precisely.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What is the main target of intellectual property analysis in the paper?",{"text":80,"@type":76},"The paper focuses on patents as the primary information carrier and knowledge source for research results and technological innovation.",{"name":82,"@type":73,"acceptedAnswer":83},"Which core tasks are involved in constructing intellectual property resource portraits?",{"text":84,"@type":76},"The document covers entity extraction and entity completion as preliminary work, then discusses portrait construction and evolution analysis as part of the overall workflow.","https://schema.org",{"og:url":51,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":51},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":92},[93,97,101,105,109,114,119,122,127,130,134],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":22,"doc_module":4,"doc_module_name":46,"category_name":106,"show_sort_weight":107,"slug":108},"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":46,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":22,"slug":137},19,"General","general"]