scholarly journals Automation and related technologies: a mapping of the new knowledge base

2022 ◽  
Author(s):  
Enrico Santarelli ◽  
Jacopo Staccioli ◽  
Marco Vivarelli
Keyword(s):  
Knowledge Base ◽  
New Knowledge

SWRLx

2018 ◽  
pp. 348-367
Author(s):  
Souad Bouaicha ◽  
Zizette Boufaida
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Object Oriented ◽  
Web Ontology Language ◽  
Rule Engine ◽  
Ontology Language ◽  
New Knowledge ◽  
Semantic Web Rule Language

Although OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language) add considerable expressiveness to the Semantic Web, they do have expressive limitations. For some reasoning problems, it is necessary to modify existing knowledge in an ontology. This kind of problem cannot be fully resolved by OWL and SWRL, as they only support monotonic inference. In this paper, the authors propose SWRLx (Extended Semantic Web Rule Language) as an extension to the SWRL rules. The set of rules obtained with SWRLx are posted to the Jess engine using rewrite meta-rules. The reason for this combination is that it allows the inference of new knowledge and storing it in the knowledge base. The authors propose a formalism for SWRLx along with its implementation through an adaptation of different object-oriented techniques. The Jess rule engine is used to transform these techniques to the Jess model. The authors include a demonstration that demonstrates the importance of this kind of reasoning. In order to verify their proposal, they use a case study inherent to interpretation of a preventive medical check-up.

scholarly journals Combining Axiom Injection and Knowledge Base Completion for Efficient Natural Language Inference

2019 ◽  
Vol 33 ◽  
pp. 7410-7417 ◽  
Author(s):  
Masashi Yoshikawa ◽  
Koji Mineshima ◽  
Hiroshi Noji ◽  
Daisuke Bekki
Keyword(s):  
Natural Language ◽  
Knowledge Base ◽  
Processing Speed ◽  
Processing Time ◽  
State Of The Art ◽  
Proof Automation ◽  
New Knowledge ◽  
Textual Entailment ◽  
Amount Of Knowledge ◽  
Recognizing Textual Entailment

In logic-based approaches to reasoning tasks such as Recognizing Textual Entailment (RTE), it is important for a system to have a large amount of knowledge data. However, there is a tradeoff between adding more knowledge data for improved RTE performance and maintaining an efficient RTE system, as such a big database is problematic in terms of the memory usage and computational complexity. In this work, we show the processing time of a state-of-the-art logic-based RTE system can be significantly reduced by replacing its search-based axiom injection (abduction) mechanism by that based on Knowledge Base Completion (KBC). We integrate this mechanism in a Coq plugin that provides a proof automation tactic for natural language inference. Additionally, we show empirically that adding new knowledge data contributes to better RTE performance while not harming the processing speed in this framework.

scholarly journals Public Health and Disasters: An Emerging Translational and Implementation Science, Not “Lessons Learned”

2017 ◽  
Vol 11 (5) ◽  
pp. 610-611 ◽  
Author(s):  
Kristi L. Koenig ◽  
Carl H. Schultz ◽  
Miryha Gould Runnerstrom ◽  
Oladele A. Ogunseitan
Keyword(s):  
Public Health ◽  
Knowledge Base ◽  
Implementation Science ◽  
Scientific Method ◽  
Disaster Medicine ◽  
Scientific Discipline ◽  
Lessons Learned ◽  
Evidence Based ◽  
Disaster Research ◽  
New Knowledge

AbstractDisaster Medicine is a relatively new multidisciplinary field of science with clear public health implications as it focuses on improving outcomes for populations rather than for individual patients. As with any other scientific discipline, the goal of public health and disaster research is to create new knowledge and transfer evidence-based data to improve public health. The phrase “lessons learned” has crept into the disaster lexicon but must be permanently erased as it has no place in the scientific method. The second edition of Koenig and Schultz’s Disaster Medicine: Comprehensive Principles & Practice adds to the growing knowledge base of this emerging specialty and explains why “lessons learned” should be discarded from the associated vocabulary. (Disaster Med Public Health Preparedness. 2017;11:610–611)

Exploitation of biotechnology in a large company

1989 ◽  
Vol 324 (1224) ◽  
pp. 599-611
Keyword(s):  
Knowledge Base ◽  
Biological Systems ◽  
Toxic Action ◽  
Biological Products ◽  
Large Company ◽  
New Knowledge ◽  
New Business

Almost from the outset, most large companies saw the ‘new biotechnology’ not as a new business but as a set of very powerful techniques that, in time, would radically improve the understanding of biological systems. This new knowledge was generally seen by them as enhancing the process of invention and not as a substitute for tried and tested ways of meeting clearly identified targets. As the knowledge base grows, so the big-company response to biotechnology becomes more positive. Within ICI, biotechnology is now integrated into five biobusinesses (Pharmaceuticals, Agrochemicals, Seeds, Diagnostics and Biological Products). Within the Central Toxicology Laboratory it also contributes to the understanding of the mechanisms of toxic action of chemicals as part of assessing risk. ICI has entered two of these businesses (Seeds and Diagnostics) because it sees biotechnology making a major contribution to the profitability of each.

scholarly journals Economy, Law, and Politics; Choudhury’s Theories and Fundamental Utopia

2020 ◽  
Vol 8 (2) ◽  
Author(s):  
JM Muslimin
Keyword(s):  
Social Justice ◽  
Knowledge Base ◽  
Social Order ◽  
Karl Marx ◽  
Social Conditions ◽  
Class Consciousness ◽  
Law And Politics ◽  
Law And Ethics ◽  
New Knowledge ◽  
Political Foundations

Masudul  Alam Choudhury agrees that fundamental thinking to construct a new knowledge base is needed when scientific and social conditions tend to be closed and monopolistic. The construction is expected to be able to dismantle the structural veil to find an alternative foundation and format that can be expected to realize social justice. For this reason, law, economics, and social paradigm can be effective instruments. In contrast to Choudhury, Karl Marx emphasized the existence of a new, rational-material awareness that dimensioned an economic struggle based on class consciousness, historical dialectics and materialism as the choice of objectives above. This awareness can be grown contextually, by moving the oppressed to demand equality. So the legal, economic and political foundations can change. While Choudhury focuses more on the transcendental dimension of the divine (tauhid paradigm) which is interpreted comprehensively and totally to dismantle the legal, economic and social order. Thus, the legal, economic and political infrastructure rests on fairness and productivity that remains competitive. The values that are in the divine foundation are arranged in the building of law and ethics (morals) to be integrated into the institution towards the desired reconstruction. However, Choudhury’s ideas remain normative and fail to be translated. It is too utopian.

scholarly journals Evaluation of new knowledge generation in the oil and gas sector of Russia through the prism of patent activity

2020 ◽  
Vol 174 ◽  
pp. 04004
Author(s):  
Valeriy Kryukov ◽  
Anatoliy Tokarev
Keyword(s):  
Knowledge Base ◽  
World Wide ◽  
Oil And Gas ◽  
Knowledge Generation ◽  
Patent Activity ◽  
Resource Base ◽  
New Knowledge ◽  
Modern Knowledge ◽  
Oil And Gas Sector

One way to describe the evolution of the modern knowledge base in the Russian oil and gas sector (OGS) is to consider it through the dynamics and results of patent activity related to inventions. On the whole, we observe rising complexity of the industrial knowledge base of OGS, which responds to changes in the resource base of OGS and reflects world- wide trends of innovation-driven growth. Notably, Russian inventions for OGS comprise rather limited use of technologies from complementary knowledge fields.

scholarly journals Enhancing the Efficiency of a Decision Support System through the Clustering of Complex Rule-Based Knowledge Bases and Modification of the Inference Algorithm

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Agnieszka Nowak-Brzezińska
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Representation ◽  
Knowledge Base ◽  
Support System ◽  
Inference Algorithm ◽  
Rule Based ◽  
New Knowledge ◽  
The Impact ◽  
Base Structure

Decision support systems founded on rule-based knowledge representation should be equipped with rule management mechanisms. Effective exploration of new knowledge in every domain of human life requires new algorithms of knowledge organization and a thorough search of the created data structures. In this work, the author introduces an optimization of both the knowledge base structure and the inference algorithm. Hence, a new, hierarchically organized knowledge base structure is proposed as it draws on the cluster analysis method and a new forward-chaining inference algorithm which searches only the so-called representatives of rule clusters. Making use of the similarity approach, the algorithm tries to discover new facts (new knowledge) from rules and facts already known. The author defines and analyses four various representative generation methods for rule clusters. Experimental results contain the analysis of the impact of the proposed methods on the efficiency of a decision support system with such knowledge representation. In order to do this, four representative generation methods and various types of clustering parameters (similarity measure, clustering methods, etc.) were examined. As can be seen, the proposed modification of both the structure of knowledge base and the inference algorithm has yielded satisfactory results.

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