[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-179029-105":59,"doc-detail-179029-en":131},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":124,"head_meta":126,"extra_data":128,"updated_unix":130},105,"en","document-metadata-extraction-multimodal","Document Metadata Extraction (Multimodal)","","This document outlines a multimodal approach to metadata extraction, focusing on the integration of text and image analysis. It details a system designed for \"case coverage determination\" and \"case factor extraction\" from non-factorized previous cases, represented by text descriptions. The system's performance is evaluated through accuracy metrics presented in graphical format, demonstrating how these metrics evolve with increasing \"new case size (n)\". The evaluation includes \"Case Relevance Determination Accuracy\", \"Probability of a past case being actually relevant\", and \"Case Factor Extraction Accuracy\" under different conditions. The research appears to be exploring the efficacy of AI-driven tools in enhancing the retrieval and analysis of information from complex datasets, aiming for improved precision and efficiency in handling historical or documented cases. The methodology suggests a sophisticated analysis pipeline that leverages both textual content and structural data to achieve robust metadata extraction, crucial for knowledge management and decision-making processes in various domains.",{"@graph":69,"@context":123},[70,84,106],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/document-metadata-extraction-multimodal/179029/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/document-metadata-extraction-multimodal/179029.png","ImageObject",300,407,{"name":92,"@type":93},"Jordan Avery","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-09-02",true,{"@type":102,"interactionType":103,"userInteractionCount":105},"InteractionCounter",{"@type":104},"ViewAction",12,{"@type":107,"mainEntity":108},"FAQPage",[109,115,119],{"name":110,"@type":111,"acceptedAnswer":112},"What are the primary functions of the described system?","Question",{"text":113,"@type":114},"The system performs \"case coverage determination\" and \"case factor extraction\" from previous cases represented by text descriptions.","Answer",{"name":116,"@type":111,"acceptedAnswer":117},"How is the system's performance evaluated?",{"text":118,"@type":114},"The system's performance is evaluated using accuracy metrics like \"Case Relevance Determination Accuracy\" and \"Case Factor Extraction Accuracy\", visualized against varying \"new case size (n)\".",{"name":120,"@type":111,"acceptedAnswer":121},"What type of input does the system process?",{"text":122,"@type":114},"The system processes non-factorized previous cases, which are described using text descriptions, and integrates this with image analysis for multimodal metadata extraction.","https://schema.org",{"og:url":83,"og:type":125,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":127,"canonical":83},"index,follow",{"doc_id":129,"site_id":62},179029,1790099871,{"code":4,"msg":5,"data":132},{"doc_id":129,"user_id":133,"nickname":92,"user_avatar":134,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":66,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":105,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":139,"language":140,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":141,"faqs":142,"seo_title":143,"seo_description":67,"update_tm":144,"read_time":145,"preview_page_count":4},1099523882367,"https://ap-avatar.wpscdn.com/davatar_9964176cb1d06d4a9deccf72a44ae3dc","cbCaie0gRwZGZDOQ","https://ap.wps.com/l/cbCaie0gRwZGZDOQ","pdf",6349015,82,"English","# Document Metadata Extraction (Multimodal)\n## Instructions\n## Language Rules\n## Field Specifications\n### Title Rules\n### `title_en`\n### `language`\n### abstract\n### `keywords`\n### `toc`\n### `faqs`\n### `category`\n## Output Requirements (STRICT)\n## Inputs","[{\"question\":\"What are the primary functions of the described system?\",\"answer\":\"The system performs \\\"case coverage determination\\\" and \\\"case factor extraction\\\" from previous cases represented by text descriptions.\"},{\"question\":\"How is the system's performance evaluated?\",\"answer\":\"The system's performance is evaluated using accuracy metrics like \\\"Case Relevance Determination Accuracy\\\" and \\\"Case Factor Extraction Accuracy\\\", visualized against varying \\\"new case size (n)\\\".\"},{\"question\":\"What type of input does the system process?\",\"answer\":\"The system processes non-factorized previous cases, which are described using text descriptions, and integrates this with image analysis for multimodal metadata extraction.\"}]","Document Metadata Extraction (Multimodal) | PDF",1788335117,207]