[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-292433-105":59,"doc-detail-292433-en":130},{"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":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","future-trends-in-expert-data-base-systems-read-and-discuss-expert-dbms-evolution","FUTURE TRENDS IN EXPERT DATA BASE SYSTEMS - read and discuss expert DBMS evolution","","The paper examines how database management systems (DBMSs) are expected to evolve over the next several years to support expert database applications. It highlights research thrusts receiving insufficient attention, proposes architectural approaches such as loose and tight coupling between rule management and data management, and evaluates techniques for triggering rules from large rule sets. It concludes that building real-world expert systems requires far more than adding rule management to a DBMS, including challenging object management issues.",{"@graph":69,"@context":122},[70,84,105],{"@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/future-trends-in-expert-data-base-systems-read-and-discuss-expert-dbms-evolution/292433/",{"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/future-trends-in-expert-data-base-systems-read-and-discuss-expert-dbms-evolution/292433.png","ImageObject",300,407,{"name":92,"@type":93},"Skyler","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-26","2026-09-17",true,{"@type":102,"interactionType":103,"userInteractionCount":24},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What is the main focus of the paper on expert database systems?","Question",{"text":112,"@type":113},"The paper discusses how DBMS capabilities should evolve to meet the needs of expert database applications and identifies key research areas that may be underemphasized.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How does the paper compare loose coupling and tight coupling architectures?",{"text":117,"@type":113},"It first considers loose coupling between a rule manager and a data manager, then discusses flaws in that approach, and argues that tight coupling can enable expert systems implemented within the data manager or in a cooperative style using an embedded inference engine.",{"name":119,"@type":110,"acceptedAnswer":120},"Why are existing methods for deciding when to fire rules considered unsatisfactory?",{"text":121,"@type":113},"The paper reviews approaches based on theorem provers, indexing techniques, and physical markers, then concludes none are fully satisfactory alternatives and calls for other mechanisms.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},292433,1789651275,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":24,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":143,"preview_page_count":4},2336464648746,"https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c","FUTURE TRENDS IN EXPERT DATA BASE SYSTEMS  \nMichael Stonebraker and Marti Hearst  \nEECS Dept.  \nUniversity of California, Berkeley  \nAbstract  \nIn this paper we discuss how we see the capabilities of DBMSs evolving over the next several years to meet the needs of expert data base applications. We also present some of the research thrusts which we see as important that appear to be receiving insufficient attention in the research community.  \n1. INTRODUCTION  \nWe begin in Section 2 with an example application which we think characterizes the need for expert data base management systems. This application will set the context for the discussion in the rest of the paper.  \nThis paper then turns in Section 3 to the architectural alternatives that can be adopted for the construction of expert data base systems such as the one described in Section 2. We begin with loose coupling between a rule manager and a data manager. The serious flaws in this architecture are then discussed followed by the possibility of tight coupling between rule and data management. We then point out that tight coupling will allow simple expert systems to be entirely implemented within the data manager while more complex ones can be written in a cooperative style whereby a data manager with an embedded inference engine and an expert system shell work cooperatively to implement an expert data base application.  \nThen we turn in Section 4 to the two thrusts which research on DBMSs with an embedded rule system have taken. A collection of researchers have concentrated on the efficient solution of rules systems that are recursive in nature. These naturally lead to the construction of query optimizers for a DBMS that can deal with recursive queries. On the other hand, other researchers have focused on more mundane rule systems where recursion is not present and have worked on efficiently discovering when one must \"fire\" rules from a large rule set. We conclude Section 4 by discussing the importance of these two thrusts and their likely commercial exploitation.  \nIn Section 5 we discuss the possible technical approaches to deciding when to \"fire\" rules from a large rule set. We discuss approaches based on theorem provers, indexing techniques and physical markers in the data base. We conclude that none are satisfactory alternatives, and we are enthusiastic about research on other possible mechanisms.  \nSection 6 then concludes by indicating that the construction of real world expert systems entails much more than adding rule management to a DBMS. Specifically, expert data base applications seem to entail a collection of difficult object management problems. In Section 6 we discuss a simple expert system which we have been working on and indicate why a conventional relational system with an inference engine is not adequate for our application.  \nThis research was sponsored by the U.S. Air Force Office of Scientific Research Grant 83-0254 and the Naval Electronics Systems Command Contract N39-82-C-0235  \n2. AN EXAMPLE EXPERT DATA BASE APPLICATION  \nConsider a computer program which is intended to give a person directions from any starting location in a particular geographic area to his destination. Such a program would be useful to car rental companies who must give directions from an airport location to the traveler’s final destination. It would also be useful to route delivery vehicles in unfamiliar territory, etc. In fact, simple systems with the capabilities which we will describe are under development commerically at the present time.  \nThe intended program will run off a data base which consists of a street map of the area in question. For each adjacent pair of nodes, the data base must store:  \nthe travel time along the arc (perhaps by time of day)  \nthe legal house numbers along the arc  \nwhether it is a one-way street  \nthe presence of stop signs  \nthe road surface  \nFor a geographic area such as the San Francisco Bay area, there are (say) 5 million people, two million le","cbCaiuQg9tLgxog2","https://ap.wps.com/l/cbCaiuQg9tLgxog2","pdf",35024,"English","# Introduction\n# Architectures for Expert Data Base Applications\n# Examples of Expert Data Base Applications\n# Rule Firing and Technical Approaches\n# Real-World Construction and Object Management","[{\"question\":\"What is the main focus of the paper on expert database systems?\",\"answer\":\"The paper discusses how DBMS capabilities should evolve to meet the needs of expert database applications and identifies key research areas that may be underemphasized.\"},{\"question\":\"How does the paper compare loose coupling and tight coupling architectures?\",\"answer\":\"It first considers loose coupling between a rule manager and a data manager, then discusses flaws in that approach, and argues that tight coupling can enable expert systems implemented within the data manager or in a cooperative style using an embedded inference engine.\"},{\"question\":\"Why are existing methods for deciding when to fire rules considered unsatisfactory?\",\"answer\":\"The paper reviews approaches based on theorem provers, indexing techniques, and physical markers, then concludes none are fully satisfactory alternatives and calls for other mechanisms.\"}]","FUTURE TRENDS IN EXPERT DATA BASE SYSTEMS - read and discuss expert DBMS evolution | PDF",25]