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===Implementations===
The earliest frame-based languages were custom developed for specific research projects and were not packaged as tools to be re-used by other researchers.
The earliest frame-based languages were custom developed for specific research projects and were not packaged as tools to be re-used by other researchers. Just as with [[expert system]] [[inference engine]]s, researchers soon realized the benefits of extracting part of the core infrastructure and developing general-purpose frame languages that were not coupled to specific applications. One of the first general-purpose frame languages was KRL.<ref>{{cite journal|last=Bobrow|first=D.G.|author2=Terry Winograd|title=An Overview of KRL: A Knowledge Representation Language|journal=Cognitive Science|year=1977|volume=1|pages=3–46|doi=10.1207/s15516709cog0101_2|doi-access=free}}</ref> One of the most influential early frame languages was [[KL-ONE]].<ref>{{cite journal|last=Brachman|first=Ron|title=A Structural Paradigm for Representing Knowledge|journal=Bolt, Beranek, and Neumann Technical Report|year=1978|issue=3605}}}{{cbignore|bot=medic}}</ref> KL-ONE spawned several subsequent Frame languages. One of the most widely used successors to KL-ONE was the [[LOOM (ontology)|Loom language]] developed by Robert MacGregor at the [[Information Sciences Institute]].<ref>{{cite journal|last=MacGregor|first=Robert|title=Using a description classifier to enhance knowledge representation|journal=IEEE Expert|date=June 1991|volume=6|issue=3|doi=10.1109/64.87683|pages=41–46|s2cid=29575443 }}</ref>▼
Just as with [[expert system]] [[inference engine]]s, researchers soon realized the benefits of extracting part of the core infrastructure and developing general-purpose frame languages that were not coupled to specific applications.
In the 1980s Artificial Intelligence generated a great deal of interest in the business world fueled by expert systems. This led to the development of many commercial products for the development of knowledge-based systems. These early products were usually developed in Lisp and integrated constructs such as IF-THEN rules for logical reasoning with Frame hierarchies for representing data. One of the most well known of these early Lisp knowledge-base tools was the [[Knowledge Engineering Environment]] (KEE) from [[IntelliCorp (software)|Intellicorp]]. KEE provided a full Frame language with multiple inheritance, slots, triggers, default values, and a rule engine that supported backward and forward chaining. As with most early commercial versions of AI software KEE was originally deployed in [[Lisp (programming language)|Lisp]] on [[Lisp machine]] platforms but was eventually ported to PCs and Unix workstations.<ref>{{cite journal|last=Mettrey|first=William|title=An Assessment of Tools for Building Large Knowledge-Based Systems|journal=AI Magazine|year=1987|volume=8|issue=4|url=http://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/625|access-date=2013-12-09|archive-url=https://web.archive.org/web/20131110022104/http://www.aaai.org/ojs/index.php/aimagazine/article/viewArticle/625|archive-date=2013-11-10|url-status=dead}}</ref>▼
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One of the most widely used successors to KL-ONE was the [[LOOM (ontology)|Loom language]] developed by Robert MacGregor at the [[Information Sciences Institute]].<ref>{{cite journal|last=MacGregor|first=Robert|title=Using a description classifier to enhance knowledge representation|journal=IEEE Expert|date=June 1991|volume=6|issue=3|doi=10.1109/64.87683|pages=41–46|s2cid=29575443 }}</ref>
In the 1980s, Artificial Intelligence generated a great deal of interest in the business world fueled by [[expert system]]<nowiki/>s. This led to the development of many commercial products for the development of knowledge-based systems. These early products were usually developed in [[Lisp (programming language)|Lisp]] and integrated constructs such as IF-THEN rules for [[logical reasoning]] with Frame hierarchies for representing data.
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The research agenda of the [[Semantic Web]] spawned a renewed interest in automatic classification and frame languages. An example is the [[Web Ontology Language]] (OWL) standard for describing information on the Internet. OWL is a standard to provide a semantic layer on top of the Internet. The goal is that rather than organizing the web using keywords as most applications (e.g. Google) do today the web can be organized by concepts organized in an ontology.
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