scispace - formally typeset
Search or ask a question
Topic

Knowledge representation and reasoning

About: Knowledge representation and reasoning is a research topic. Over the lifetime, 20078 publications have been published within this topic receiving 446310 citations. The topic is also known as: KR & KR².


Papers
More filters
Proceedings Article
20 Aug 1995
TL;DR: A methodology for comparing knowledge representation formalisms in terms of their "representational succinctness," that is, their ability to express knowledge situations relatively efficiently, is developed.
Abstract: We develop a methodology for comparing knowledge representation formalisms in terms of their "representational succinctness," that is, their ability to express knowledge situations relatively efficiently. We use this framework for comparing many important formalisms for knowledge base representation: propositional logic, default logic, circumscription, and model preference defaults; and, at a lower level, Horn formulas, characteristic models, decision trees, disjunctive normal form, and conjunctive normal form. We also show that adding new variables improves the effective expressibility of certain knowledge representation formalisms.

132 citations

Journal ArticleDOI
TL;DR: A family of extensions of Sowa's model, based on rules and constraints, keeping graph homomorphism as the basic operation is presented, including their operational semantics and relationships with FOL.
Abstract: Simple conceptual graphs are considered as the kernel of most knowledge representation formalisms built upon Sowa's model. Reasoning in this model can be expressed by a graph homomorphism called projection, whose semantics is usually given in terms of positive, conjunctive, existential FOL. We present here a family of extensions of this model, based on rules and constraints, keeping graph homomorphism as the basic operation. We focus on the formal definitions of the different models obtained, including their operational semantics and relationships with FOL, and we analyze the decidability and complexity of the associated problems (consistency and deduction). As soon as rules are involved in reasonings, these problems are not decidable, but we exhibit a condition under which they fall in the polynomial hierarchy. These results extend and complete the ones already published by the authors. Moreover we systematically study the complexity of some particular cases obtained by restricting the form of constraints and/or rules.

132 citations

Book ChapterDOI
TL;DR: A first theoretical framework and a model for the new field of knowledge visualization are presented, which describes guidelines and principles derived from professional practice and previous research on how architects successfully use complementary visualizations to transfer and create knowledge among individuals from different social, cultural, and educational backgrounds.
Abstract: This article presents synergies between the research areas information visualization and knowledge visualization from a knowledge management and a communication science perspective. It presents a first theoretical framework and a model for the new field of knowledge visualization. It describes guidelines and principles derived from our professional practice and previous research on how architects successfully use complementary visualizations to transfer and create knowledge among individuals from different social, cultural, and educational backgrounds. The findings and insights are important for researchers and practitioners in the fields of information visualization, knowledge visualization, knowledge management, information design, media didactics, instructional psychology, and communication sciences.

132 citations

Journal ArticleDOI
Yiyu Yao1
01 Aug 2009
TL;DR: This paper examines a conceptual framework for concept learning from the viewpoints of cognitive informatics and granular computing and interprets concept learning based on a layered model of knowledge discovery.
Abstract: Cognitive informatics and granular computing are two emerging fields of study concerning information and knowledge processing. A central notion to this processing is information and knowledge granularity. Concepts, as the basic units of thought underlying human intelligence and communication, may play a fundamental role when integrating the results from the two fields in terms of information and knowledge coding, representation, communication, and processing. While cognitive informatics focuses on information processing in the abstract, in machines, and in the brain, granular computing models such processing at multiple levels of granularity. In this paper, we examine a conceptual framework for concept learning from the viewpoints of cognitive informatics and granular computing. Within the framework, we interpret concept learning based on a layered model of knowledge discovery.

132 citations

Journal Article
TL;DR: An ontology to represent the semantics of the IMS Learning Design (IMS LD) specification, a meta-language used to describe the main elements of the learning design process, is presented and its implementation in OWL, the standard language of the Semantic Web, is provided.
Abstract: In this paper, we present an ontology to represent the semantics of the IMS Learning Design (IMS LD) specification, a meta-language used to describe the main elements of the learning design process. The motivation of this work relies on the expressiveness limitations found on the current XML-Schema implementation of the IMS LD conceptual model. To solve these limitations, we have developed an ontology using Protege at the knowledge level. In addition, we provide its implementation in OWL, the standard language of the Semantic Web, and the set of associated axioms in first-order logic. The OWL file is available at http://www.eume.net/ontology/imsld_a.owl.

132 citations


Network Information
Related Topics (5)
User interface
85.4K papers, 1.7M citations
82% related
Graph (abstract data type)
69.9K papers, 1.2M citations
81% related
Genetic algorithm
67.5K papers, 1.2M citations
79% related
Robot
103.8K papers, 1.3M citations
79% related
Fuzzy logic
151.2K papers, 2.3M citations
79% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202378
2022192
2021390
2020528
2019566
2018509