KNOWLEDGE-BASED SYSTEMS
In order to make computers intelligent，knowledge should be given to them．Knowledge-based systems are such computer systems that they can effectively store and manage human knowledge，and use the knowledge to solve problems that originally require human intelligence．Examples of such systems are expert systems，decision support systems，knowledge base systems，etc．Knowledge-based systems are of crucial importance in AI applications and in future information technology．
The first basic question we are confronted in the construction of a knowledge-based system is how to represent knowledge，which is referred to as knowledge representation．Knowledge representation is to encode information such objects，goal，actions，and processes into data structures and procedures．It is a fundamental component of any knowledge-based systems．Various schemes for representing knowledge have been proposed，of which the most important ones are production rules，frames，semantic networks，logic，script and etc．
The reasoning mechanism and knowledge management are another two important parts of a knowledge-based system．The function of reasoning mechanism is knowledge utilization．It solves users queries by inferencing using knowledge in the knowledge base．Whereas knowledge management is responsible for performing various operations on the knowledge，such as retrieving and updating．
Knowledge acquisition is the central but most difficult problem．In order to acquire knowledge from various sources，such as experts or text，many stages，such as identification，conceptualization，formalization，implementation，and testing have to be conducted．So far，only a small number of systems currently exist that automate portions of the knowledge acquisition task．
One approach to construct a knowledge base system is to combine a relational database management system and PROLOG，with PROLOG functioning as the inference engine．Some research effort has been devoted to constructing such systems by using commercial DBMSs，while others in an attempt to largely improve the perforrmance，by developing new languages which combine logic programming and relational programming concepts（e. g．，the Logic Data language developed by MCC）and developing high performance parallel database machines[1]．It is expected that these systems will exhibit powerful capabilities both in data management and knowledge management．
NOTES
[1]while引導的比較狀語表示前后對比。兩個by...介詞短語都是方式狀語，表示方法、手段。
KEYWORDS
acquisition 獲取
decision support systems 決策支持系統
conceptualization 概念化
production rule 產生式規則
formalization 形式化
frame 框架
DBMS-database management system 數據庫管理系統
reasoning mechanism 推理機制
EXERCISES
Multiple choices．
（1）In order to make computers intelligent，what should be given to them？
a．keyboard b．I/O port
c．network adapter d．knowledge
（2）What is the first basic question we are confronted in the construction of a knowledge-based system？
a．knowledge representation b．parallelism
c．object-oriented programming d．logic programming
（3）What is the function of reasoning mechanism？
a．knowledge representation b．knowledge management
c．knowledge construction d．knowledge utilization
（4）How to solve users queries using knowledge in the knowledge base？
a．by accessing b．by retrieving
c．by inferencing d．by invoking
答案：
（1）d （2）a （3）d （4）c
翻譯：
基于知識的系統
為了使計算機智能化，必須將知識賦予它們，基于知識的系統就是這樣的一種計算機系統，它能有效地存儲和管理知識并用這些知識來解決原來需要人類智能來解決的問題，這些系統的例子有專家系統、決策支持系統、知識庫系統等�；谥R的系統在人工智能應用和將來的信息技術中是至關重要的。
在基于知識的系統構成中，我們所面臨的第一個主要問題就是如何表達知識，這稱之為知識表達。知識表達是將諸如對象、目標、作用和進程等信息編碼成數據結構和過程，它是所有基于知識的系統的基本組成部分。為了表達知識，人們提出了各種各樣的方案，其中最為主要的就是產生規則、框架、語義網絡、邏輯和腳本等。
推理機制和知識管理是基于知識的系統中另外兩個重要部分。推理機制的功能是知識的利用，它通過用知識庫中的知識進行推理來解決用戶查詢，而知識管理則負責對知識進行各種操作，比如檢索和更新。
知識獲取是最主要的也是最困難的問題。為了從各種途徑（比如從專家或書本上）獲取知識，必須經過像辨識、概念化、形式化、實現和測試等許多階段。迄今為止，只有少數幾個系統部分地實現了自動知識獲取。
構成知識庫系統的方法之一是將關系數據庫系統和邏輯程序設計語言結合起來，以邏輯程序設計語言驅動推理機。某些研究已試圖努力通過商業DBMS來構成這樣的系統；此外，為了大幅度提高性能，其他研究則致力于通過開發結合邏輯編程和關系編程概念的新語言（如由MCC開發的邏輯數據語言）以及開發高性能的并行數據庫計算機。人們期望這些系統將在數據管理和知識管理兩方面展示強大的能力。
文章來源于領測軟件測試網 http://www.kjueaiud.com/
