Academic literature on the topic 'Rule Representation'

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Journal articles on the topic "Rule Representation"

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Branke, Jürgen, Torsten Hildebrandt, and Bernd Scholz-Reiter. "Hyper-heuristic Evolution of Dispatching Rules: A Comparison of Rule Representations." Evolutionary Computation 23, no. 2 (June 2015): 249–77. http://dx.doi.org/10.1162/evco_a_00131.

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Dispatching rules are frequently used for real-time, online scheduling in complex manufacturing systems. Design of such rules is usually done by experts in a time consuming trial-and-error process. Recently, evolutionary algorithms have been proposed to automate the design process. There are several possibilities to represent rules for this hyper-heuristic search. Because the representation determines the search neighborhood and the complexity of the rules that can be evolved, a suitable choice of representation is key for a successful evolutionary algorithm. In this paper we empirically compare three different representations, both numeric and symbolic, for automated rule design: A linear combination of attributes, a representation based on artificial neural networks, and a tree representation. Using appropriate evolutionary algorithms (CMA-ES for the neural network and linear representations, genetic programming for the tree representation), we empirically investigate the suitability of each representation in a dynamic stochastic job shop scenario. We also examine the robustness of the evolved dispatching rules against variations in the underlying job shop scenario, and visualize what the rules do, in order to get an intuitive understanding of their inner workings. Results indicate that the tree representation using an improved version of genetic programming gives the best results if many candidate rules can be evaluated, closely followed by the neural network representation that already leads to good results for small to moderate computational budgets. The linear representation is found to be competitive only for extremely small computational budgets.
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Mao, Yanying, and Honghui Chen. "Rule-Guided Compositional Representation Learning on Knowledge Graphs with Hierarchical Types." Mathematics 9, no. 16 (August 18, 2021): 1978. http://dx.doi.org/10.3390/math9161978.

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The representation learning of the knowledge graph projects the entities and relationships in the triples into a low-dimensional continuous vector space. Early representation learning mostly focused on the information contained in the triplet itself but ignored other useful information. Since entities have different types of representations in different scenarios, the rich information in the types of entity levels is helpful for obtaining a more complete knowledge representation. In this paper, a new knowledge representation frame (TRKRL) combining rule path information and entity hierarchical type information is proposed to exploit interpretability of logical rules and the advantages of entity hierarchical types. Specifically, for entity hierarchical type information, we consider that entities have multiple representations of different types, as well as treat it as the projection matrix of entities, using the type encoder to model entity hierarchical types. For rule path information, we mine Horn rules from the knowledge graph to guide the synthesis of relations in paths. Experimental results show that TRKRL outperforms baselines on the knowledge graph completion task, which indicates that our model is capable of using entity hierarchical type information, relation paths information, and logic rules information for representation learning.
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Niu, Guanglin, Yongfei Zhang, Bo Li, Peng Cui, Si Liu, Jingyang Li, and Xiaowei Zhang. "Rule-Guided Compositional Representation Learning on Knowledge Graphs." Proceedings of the AAAI Conference on Artificial Intelligence 34, no. 03 (April 3, 2020): 2950–58. http://dx.doi.org/10.1609/aaai.v34i03.5687.

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Representation learning on a knowledge graph (KG) is to embed entities and relations of a KG into low-dimensional continuous vector spaces. Early KG embedding methods only pay attention to structured information encoded in triples, which would cause limited performance due to the structure sparseness of KGs. Some recent attempts consider paths information to expand the structure of KGs but lack explainability in the process of obtaining the path representations. In this paper, we propose a novel Rule and Path-based Joint Embedding (RPJE) scheme, which takes full advantage of the explainability and accuracy of logic rules, the generalization of KG embedding as well as the supplementary semantic structure of paths. Specifically, logic rules of different lengths (the number of relations in rule body) in the form of Horn clauses are first mined from the KG and elaborately encoded for representation learning. Then, the rules of length 2 are applied to compose paths accurately while the rules of length 1 are explicitly employed to create semantic associations among relations and constrain relation embeddings. Moreover, the confidence level of each rule is also considered in optimization to guarantee the availability of applying the rule to representation learning. Extensive experimental results illustrate that RPJE outperforms other state-of-the-art baselines on KG completion task, which also demonstrate the superiority of utilizing logic rules as well as paths for improving the accuracy and explainability of representation learning.
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Doğan, Battal, Serhat Doğan, and Kemal Yıldız. "On Capacity-Filling and Substitutable Choice Rules." Mathematics of Operations Research 46, no. 3 (August 2021): 856–68. http://dx.doi.org/10.1287/moor.2021.1128.

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Each capacity-filling and substitutable choice rule is known to have a maximizer-collecting representation: There exists a list of priority orderings such that from each choice set that includes more alternatives than the capacity, the choice is the union of the priority orderings’ maximizers. We introduce the notion of a critical set and constructively prove that the number of critical sets for a choice rule determines its smallest-size maximizer-collecting representation. We show that responsive choice rules require the maximal number of priority orderings in their smallest-size maximizer-collecting representations among all capacity-filling and substitutable choice rules. We also analyze maximizer-collecting choice rules in which the number of priority orderings equals the capacity. We show that if the capacity is greater than three and the number of alternatives exceeds the capacity by at least two, then no capacity-filling and substitutable choice rule has a maximizer-collecting representation of the size equal to the capacity.
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Pugh, Zachary H., and Douglas J. Gillan. "Nodes Afford Connection: A Pilot Study Examining the Design and Use of a Graphical Modeling Language." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 65, no. 1 (September 2021): 1024–28. http://dx.doi.org/10.1177/1071181321651150.

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External representations such as diagrams facilitate reasoning. Many diagramming systems and notations are amenable to manipulation by actual or imagined intervention (e.g., transposing terms in an equation). Such manipulation is constrained by user-enforced constraints, including rules of syntax and semantics which help preserve the representation’s validity. We argue that the concepts of affordances and signifiers can be applied to understand such representations, and we suggest the term graphical affordance to refer to rule-constrained syntactic manipulation of an external representation. Following this argument, we examine a graphical modeling language in terms of these graphical affordances, and we present a pilot study examining how participants interact with the modeling language. Preliminary results suggest that using the modeling language, as opposed to prose representation, influences user behavior in a manner aligned with the graphical affordances and signifiers of the modeling language.
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Arawi, Fadia Amellia. "Perbandingan Representasi Perempuan di Parlemen Indonesia dan Filipina." Politeia: Jurnal Ilmu Politik 14, no. 2 (July 18, 2022): 74–85. http://dx.doi.org/10.32734/politeia.v14i2.8600.

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The purpose of this article is to examine the contrasts between the Philippines and Indonesia between the two countries. Both countries share the same democracy system, but its democratic value has not been fully operational, and there is still an imbalance for women in the parliament. The problem focused on the disparity of right to politically correct between women and men who were not equally equal. To analyze the problem using the theory of representation according to Hanna pitkin in (niron & seda, 2020), representational representation is divided into 4 of them: formal descriptive, substantiating/resonant and symbolic. Formal representation focuses on the rule of law on the procedure of how a representative is chosen or replaced. Descriptive reliability is focused on compositions that are proportionately composed between those represented and represented. Descriptive adherence is focused on composition in parliament. Subthanctive/clergy awareness focuses on a representative who should be in line with the person it represents. The last time of symbolic representation, it focused on how strongly the symbol was viewed by the viewer. Data was collected through literature studies from previous studies and qualitative analysis. Research has concluded that, based on ipu data in the 2019 elections in Indonesia, women's representations in parliament are only 17.39% while the Philippine parliament is at 27.96%. But in second representation
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Nowak-Brzezińska, Agnieszka. "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 (December 6, 2018): 1–14. http://dx.doi.org/10.1155/2018/2065491.

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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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Hardgrove, Anne. "Agrarian Environments: Resources, Representation, and Rule in India:Agrarian Environments: Resources, Representation, and Rule in India." Culture Agriculture 24, no. 2 (September 2002): 64–65. http://dx.doi.org/10.1525/cag.2002.24.2.64.

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Reshetnikova, Irina V. "Professional Representation in Russian Courts: The Application Practice." Arbitrazh-civil procedure 11 (October 29, 2020): 19–20. http://dx.doi.org/10.18572/1812-383x-2020-11-19-20.

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The article reveals the exceptions to professional representation in court (the rules on the mandatory presence of a representative in the court of higher legal education or a degree in law). This requirement does not apply to patent attorneys in disputes related to the legal protection of intellectual property results and means of individualization, arbitration managers in the performance of their duties in a bankruptcy case. An exception to the General rule is also legal representation, representation of organizations by bodies of legal entities. However, the head of a representative office (branch) of a legal entity must submit to the court documents on higher legal education or academic degree in a legal specialty. An auditor or a member of the chamber of Commerce and industry must have a higher legal education or a degree in law in the case of representation in court.
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Bello Hutt, Donald. "Rule of Law and Political Representation." Hague Journal on the Rule of Law 14, no. 1 (November 2, 2021): 1–25. http://dx.doi.org/10.1007/s40803-021-00163-5.

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AbstractHow do the rule of law and political representation relate to each other? I answer this question, hitherto neglected by rule-of-law scholars, taking my cue from Joseph Raz’s revision of his conception of the rule of law and by relying on a distinction between preferences and interests, which pervades discussions of political representation. I argue that political representatives’ attention to their constituents’ preferences, and not just their interests, is a necessary feature of a conception of representation that expresses a robust allegiance to the rule of law. More specifically, that such allegiance is better honoured when representatives are responsive to preferences warranted by public interests. I offer two groups of rule-of-law reasons for that claim. First, because respect for preferences by representatives facilitates the conditions for the law to be obeyed. Second, respect for those preferences through the justification of the representatives’ collective decisions allows for accountability and for non-arbitrary creation and application of the law. I finish addressing a threefold objection to my reliance on preferences as objects that representatives should consider when making their decisions.
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Dissertations / Theses on the topic "Rule Representation"

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Aude, J. S. "Design rule representation within a hardware design system." Thesis, University of Manchester, 1986. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.377479.

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Soltan-Zadeh, Yasaman. "Improved rule-based document representation and classification using genetic programming." Thesis, Royal Holloway, University of London, 2011. http://repository.royalholloway.ac.uk/items/479a1773-779b-8b24-b334-7ed485311abe/8/.

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Ghiasnezhad, Omran Pouya. "Rule Learning in Knowledge Graphs." Thesis, Griffith University, 2018. http://hdl.handle.net/10072/382680.

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With recent advancements in knowledge extraction and knowledge management systems, an enormous number of knowledge bases have been constructed, such as YAGO, and Wikidata. These automatically built knowledge bases which contain millions of entities and their relations have been stored in graph-based schemas, and thus are usually referred to as knowledge graphs (KGs). Since KGs have been built based on the limited available data, they are far from complete. However, learning frequent patterns in the form of logical rules from these incomplete KGs has two main advantages. First, by applying the learned rules, we can infer new facts, so we could complete the KGs. Second, the rules are stand-alone knowledge which express valuable insight about the data. However, learning rules from KGs in relation to the real-world scenarios imposes several challenges. First, due to the vast size of real-world KGs, developing a rule learning method is challenging. In fact, existing methods are not scalable for learning rst order rules, while various optimisation strategies are used such as sampling and language bias (i.e., restrictions on the form of rules). Second, applying the learned rules to the vast KG and inferring new facts is another di cult issue. Learned rules usually contain a lot of noises and adding new facts can cause inconsistency of KGs. Third, it is useful but non-trivial to extend an existing method of rule learning to the case of stream KGs. Forth, in many data repositories, the facts are augmented with time stamps. In this case, we face a stream of data (KGs). Considering time as a new dimension of data imposes some challenges to the rule learning process. It would be useful to construct a time-sensitive model from the stream of data and apply the obtained model to stream KGs. Last, the density of information in a KG is varied. Although the size of a KG is vast, it contains a limited amount of information for some relations. Consequently, that part of KG is sparse. Learning a set of accurate and informative rules regarding the sparse part of a KG is challenging due to the lack of su cient training data. In this thesis, we investigate these research problems and present our methods for rule learning in various scenarios. We have rst developed a new approach, named Rule Learning via Learning Representation (RLvLR), to learning rules from KGs by using the technique of embedding in representation learning together with a new sampling method. RLvLR learns rst-order rules from vast KGs by exploring the embedding space. It can handle some large KGs that cannot be handled by existing rule learners e ciently, due to a novel sampling method. To improve the performance of RLvLR for handling sparse data, we propose a transfer learning method, Transfer Rule Learner (TRL), for rule learning. Based on a similarity characterised by the embedding representation, our method is able to select most relevant KGs and rules to transfer from a pool of KGs whose rules have been obtained. We have also adapted RLvLR to handle stream KGs instead of static KGs. Then a system called StreamLearner is developed for learning rules from stream KGs. These proposed methods can only learn so-called closed path rules, which is a proper subset of Horn rules. Thus, we have also developed a transfer rule learner (T-LPAD) that learns the structure of logic program with annotated disjunctions. T-LPAD is created by employing transfer learning to explore the space of rules' structures more e ciently. Various experiments have been conducted to test and validate the proposed methods. Our experimental results show that our methods outperform state-of-the-art methods in many ways.
Thesis (PhD Doctorate)
Doctor of Philosophy (PhD)
School of Info & Comm Tech
Science, Environment, Engineering and Technology
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Brunson, Alicia. "Light, Bright, and Out of Sight: Hollywood’s Representation of the Tragic Mulatto." Thesis, University of North Texas, 2013. https://digital.library.unt.edu/ark:/67531/metadc407836/.

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The purpose of this research is to examine the longevity of the stereotype of the tragic mulatto in American film history. Specifically, my research focuses on the portrayals and perceptions of biracial actresses. Media informs, entertains, and influences how we, and especially youth, self-identify and interact with others. This research focuses on the portrayal of biracial actresses throughout film history. It is also important in its investigation of the perpetuation of the one-drop rule. In this research, I will examine if historical stereotypes of tragic mulatto are apparent in contemporary Hollywood film. The methodologies used in this research include a content analysis of films with biracial actresses and an online survey of respondents’ perceptions of four actresses. Statistical techniques used for analysis include ordinary least square regression and multinomial logistic regression. Findings suggest that the tragic mulatto stereotype is not blatant in contemporary Hollywood film, but issues of colorism may be apparent.
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Yang, Wanzhong. "Granule-based knowledge representation for intra and inter transaction association mining." Thesis, Queensland University of Technology, 2009. https://eprints.qut.edu.au/30398/1/Wanzhong_Yang_Thesis.pdf.

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Abstract With the phenomenal growth of electronic data and information, there are many demands for the development of efficient and effective systems (tools) to perform the issue of data mining tasks on multidimensional databases. Association rules describe associations between items in the same transactions (intra) or in different transactions (inter). Association mining attempts to find interesting or useful association rules in databases: this is the crucial issue for the application of data mining in the real world. Association mining can be used in many application areas, such as the discovery of associations between customers’ locations and shopping behaviours in market basket analysis. Association mining includes two phases. The first phase, called pattern mining, is the discovery of frequent patterns. The second phase, called rule generation, is the discovery of interesting and useful association rules in the discovered patterns. The first phase, however, often takes a long time to find all frequent patterns; these also include much noise. The second phase is also a time consuming activity that can generate many redundant rules. To improve the quality of association mining in databases, this thesis provides an alternative technique, granule-based association mining, for knowledge discovery in databases, where a granule refers to a predicate that describes common features of a group of transactions. The new technique first transfers transaction databases into basic decision tables, then uses multi-tier structures to integrate pattern mining and rule generation in one phase for both intra and inter transaction association rule mining. To evaluate the proposed new technique, this research defines the concept of meaningless rules by considering the co-relations between data-dimensions for intratransaction-association rule mining. It also uses precision to evaluate the effectiveness of intertransaction association rules. The experimental results show that the proposed technique is promising.
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Yang, Wanzhong. "Granule-based knowledge representation for intra and inter transaction association mining." Queensland University of Technology, 2009. http://eprints.qut.edu.au/30398/.

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Abstract With the phenomenal growth of electronic data and information, there are many demands for the development of efficient and effective systems (tools) to perform the issue of data mining tasks on multidimensional databases. Association rules describe associations between items in the same transactions (intra) or in different transactions (inter). Association mining attempts to find interesting or useful association rules in databases: this is the crucial issue for the application of data mining in the real world. Association mining can be used in many application areas, such as the discovery of associations between customers’ locations and shopping behaviours in market basket analysis. Association mining includes two phases. The first phase, called pattern mining, is the discovery of frequent patterns. The second phase, called rule generation, is the discovery of interesting and useful association rules in the discovered patterns. The first phase, however, often takes a long time to find all frequent patterns; these also include much noise. The second phase is also a time consuming activity that can generate many redundant rules. To improve the quality of association mining in databases, this thesis provides an alternative technique, granule-based association mining, for knowledge discovery in databases, where a granule refers to a predicate that describes common features of a group of transactions. The new technique first transfers transaction databases into basic decision tables, then uses multi-tier structures to integrate pattern mining and rule generation in one phase for both intra and inter transaction association rule mining. To evaluate the proposed new technique, this research defines the concept of meaningless rules by considering the co-relations between data-dimensions for intratransaction-association rule mining. It also uses precision to evaluate the effectiveness of intertransaction association rules. The experimental results show that the proposed technique is promising.
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Solihin, Wawan. "A simplified BIM data representation using a relational database schema for an efficient rule checking system and its associated rule checking language." Diss., Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/54831.

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Efforts to automate building rule checking have not brought us anywhere near to the ultimate goal to fully automate the rule checking process. With the advancement in BIM and the latest tools and computing capability, we have what is necessary to achieve it. And yet challenges still abound. This research takes a holistic approach to solve the issue by first examining the rule complexity and its logic structure. Three major aspects of the rules are addressed in this research. The first is a new approach to transform BIM data into a simple database schema and to make it easily query-able by adopting the data warehouse approach. Geometry and spatial operations are also commonly needed for automating rules, and therefore the second approach is to integrate these into a database in the form of multiple representations. The third is a standardized rule language that leverages the database query integrated with its geometry and spatial query capability, called BIMRL. It is designed for a non-programmatic approach to the rule definitions that is suitable for typical rule experts. The rule definition takes a form of triplet command: CHECK – EVALUATE – ACTION statement that can be chained to support more complex rules. A prototype system has been developed as a proof-of-concept using selected rules taken from various sources to demonstrate the validity of the approach to solve the challenges of automating the building rule checking.
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PISCHEDDA, DORIS. "Rule-guided behaviour: how and where rules are represented and processed in human brain." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2014. http://hdl.handle.net/10281/50374.

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Much of our behaviour is guided by rules defining associations between meaningful stimuli and proper responses. The ability to flexibly switch between rules to adapt to a continuously changing environment is one of the main challenges for the human cognitive system. Investigating how different types and combinations of rules are encoded and implemented in human brain is crucial to understand how we select and apply rules to guide our behaviour and react flexibly to a dynamic environment. The present thesis addressed the issue of where in the brain different types of rules are represented and how they are processed. Behavioural paradigms, functional magnetic resonance imaging, and multivariate pattern classification were combined to shed light on the cognitive mechanisms underlying rule processing and to identify brain areas encoding the contents of such processes. Using a priming paradigm, the first study assessed which types of associations (conditional, disjunctive, spatial, or quantified) could be activated automatically and trigger unconscious inferences. It proved that Modus Ponens inference is carried out unconsciously. The second study demonstrated that a condition-action rule instructed on a trial-by-trial basis and immediately marked as irrelevant causes significant interference effects when involuntarily triggered by target stimuli matching the condition in the rule. In the third study, using complex rule sets, we showed that rules at different level in the hierarchy of action control are encoded in partially separate brain networks. Moreover, we found that rule information is represented in distinct brain areas when different types of rules are encoded jointly. In the fourth study, we used rules composed using different logical connectives to expand the set of associations considered and to assess possible differences in rule representation and processing between rules with distinct logical forms. We found that separate brain areas encoded task rule information during rule representation and evaluation and that the involvement of these areas depended on the specific rule active in a trial. Taken together, our results suggest that conditional rules hold a special status in the human cognitive system, contributing to our knowledge on rule-guided behaviour.
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au, skhor@iinet net, and Sebastian Wankun Khor. "A Fuzzy Knowledge Map Framework for Knowledge Representation." Murdoch University, 2007. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20070822.32701.

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Cognitive Maps (CMs) have shown promise as tools for modelling and simulation of knowledge in computers as representation of real objects, concepts, perceptions or events and their relations. This thesis examines the application of fuzzy theory to the expression of these relations, and investigates the development of a framework to better manage the operations of these relations. The Fuzzy Cognitive Map (FCM) was introduced in 1986 but little progress has been made since. This is because of the difficulty of modifying or extending its reasoning mechanism from causality to relations other than causality, such as associative and deductive reasoning. The ability to express the complex relations between objects and concepts determines the usefulness of the maps. Structuring these concepts and relations in a model so that they can be consistently represented and quickly accessed and anipulated by a computer is the goal of knowledge representation. This forms the main motivation of this research. In this thesis, a novel framework is proposed whereby single-antecedent fuzzy rules can be applied to a directed graph, and reasoning ability is extended to include noncausality. The framework provides a hierarchical structure where a graph in a higher layer represents knowledge at a high level of abstraction, and graphs in a lower layer represent the knowledge in more detail. The framework allows a modular design of knowledge representation and facilitates the creation of a more complex structure for modelling and reasoning. The experiments conducted in this thesis show that the proposed framework is effective and useful for deriving inferences from input data, solving certain classification problems, and for prediction and decision-making.
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Rocher, Swan. "Querying existential rule knowledge bases : decidability and complexity." Thesis, Montpellier, 2016. http://www.theses.fr/2016MONTT291/document.

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Dans cette thèse, nous nous intéressons au problème d'interrogation de bases de connaissances composées de données et d'une ontologie, qui représente des connaissances générales sur le domaine d'application. Parmi les différents formalismes permettant de représenter les connaissances ontologiques, nous considérons ici un fragment de la logique du premier ordre appelé règles existentielles (aussi connues sous le nom de ``tuple generating dependencies'' et Datalog+/-). Le problème fondamental de conséquence logique au cœur de cette thèse demande si une requête conjonctive est conséquence d'une base de connaissances. Les règles existentielles étant très expressives, ce problème est indécidable. Toutefois, différentes restrictions sur les ensembles de règles ont été proposées afin d'obtenir sa décidabilité.La contribution de cette thèse est double. Premièrement, nous proposons un outil qui nous permet d'unifier puis d'étendre la plupart des classes de règles connues reposant sur des notions d'acyclicité assurant la finitude du chaînage avant. Deuxièmement, nous étudions la compatibilité des classes décidables de règles existentielles connues avec un type de connaissance souvent nécessaire dans les ontologies: la transitivité de relations binaires. Nous aidons à clarifier le paysage des résultats positifs et négatifs liés à cette question et fournissons une approche permettant de combiner la transitivité avec les règles existentielles linéaires
In this thesis we investigate the issue of querying knowledge bases composed of data and general background knowledge, called an ontology. Ontological knowledge can be represented under different formalisms and we consider here a fragment of first-order logic called existential rules (also known as tuple-generating dependencies and Datalog+/-).The fundamental entailment problem at the core of this thesis asks if a conjunctive query is entailed by an existential rule knowledge base. General existential rules are highly expressive, however at the cost of undecidability. Various restrictions on sets of rules have been proposed to regain the decidability of the entailment problem.Our specific contribution is two-fold. First, we propose a new tool that allows to unify and extend most of the known existential rule classes that rely on acyclicity conditions to tame infinite forward chaining, without increasing the complexity of the acyclicity recognition. Second, we study the compatibility of known decidable rule classes with a frequently required modeling construct, namely transitivity of binary relations. We help clarifying the picture of negative and positive results on this question, and provide a technique to safely combine transitivity with one of the simplest, yet useful, decidable rule classes, namely linear rules
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Books on the topic "Rule Representation"

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D, Friederici Angela, and Menzel Randolf 1940-, eds. Learning: Rule extraction and representation. Berlin: Walter de Gruyter, 1998.

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A, O'Donnell Guillermo, Schmitter Philippe C, and Whitehead Laurence, eds. Transitions from authoritarian rule. Baltimore: Johns Hopkins University Press, 1986.

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Banjoko, Olubadejo Olorunleke. Universal democracy (holocracy): The rule by all parties. Ibadan: Spectrum Books in association with Safari Books, 2004.

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A, O'Donnell Guillermo, Schmitter Philippe C, and Whitehead Laurence, eds. Transitions from authoritarian rule: Prospects for democracy. Baltimore: Johns Hopkins University Press, 1986.

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A, O'Donnell Guillermo, Schmitter Philippe C, Whitehead Laurence, and Woodrow Wilson International Center for Scholars. Latin American Program., eds. Transitions from authoritarian rule. Baltimore: Johns Hopkins University Press, 1986.

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Soche, H. Harris. Supremasi hukum dan prinsip demokrasi di Indonesia. Yogyakarta: Hanindita, 1985.

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"Here, the people rule": A constitutional populist manifesto. Cambridge, Mass: Harvard University Press, 1994.

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Bassiliades, Nick, Guido Governatori, and Adrian Paschke, eds. Rule Representation, Interchange and Reasoning on the Web. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88808-6.

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Min zhu, xian zheng, fa zhi. Taibei Shi: Tangshan chu ban she, 2001.

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A, O'Donnell Guillermo, Schmitter Philippe C, Whitehead Laurence, and Woodrow Wilson International Center for Scholars. Latin American Program., eds. Transitions from authoritarian rule. Baltimore: Johns Hopkins University Press, 1986.

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Book chapters on the topic "Rule Representation"

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Sudkamp, Thomas, Aaron Knapp, and Jon Knapp. "Effect of Rule Representation in Rule Base Reduction." In Interpretability Issues in Fuzzy Modeling, 303–24. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-37057-4_13.

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Abe, Shigeo. "Fuzzy Rule Representation and Inference." In Pattern Classification, 257–61. London: Springer London, 2001. http://dx.doi.org/10.1007/978-1-4471-0285-4_14.

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Hallmark, Gary, Christian de Sainte Marie, Marcos Didonet Del Fabro, Patrick Albert, and Adrian Paschke. "Please Pass the Rules: A Rule Interchange Demonstration." In Rule Representation, Interchange and Reasoning on the Web, 227–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88808-6_24.

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Ligęza, Antoni. "Granular Rules and Rule Frames for Compact Knowledge Representation." In Lecture Notes in Computer Science, 214–23. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25252-0_23.

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Colomer, Josep M. "Global Representation Requires Rotation of Countries." In How Global Institutions Rule the World, 101–11. New York: Palgrave Macmillan US, 2014. http://dx.doi.org/10.1057/9781137475084_9.

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Pfeiffer, Joseph J. "A Prototype Inference Engine for Rule-Based Geometric Reasoning." In Diagrammatic Representation and Inference, 216–26. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-25931-2_20.

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Pearl, Judea. "Jeffrey’s Rule, Passage of Experience, and Neo-Bayesianism." In Knowledge Representation and Defeasible Reasoning, 245–65. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0553-5_10.

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Kifer, Michael. "Rule Interchange Format: The Framework." In Rule Representation, Interchange and Reasoning on the Web, 1–2. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88808-6_1.

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van Someren, Maarten W. "Using attribute dependencies for rule learning." In Knowledge Representation and Organization in Machine Learning, 192–210. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/bfb0017223.

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Hatfield, Gary. "Representation and Rule-Instantiation in Connectionist Systems." In Connectionism and the Philosophy of Mind, 90–112. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-3524-5_5.

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Conference papers on the topic "Rule Representation"

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Ghiasnezhad Omran, Pouya, Kewen Wang, and Zhe Wang. "Scalable Rule Learning via Learning Representation." In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/297.

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We study the problem of learning first-order rules from large Knowledge Graphs (KGs). With recent advancement in information extraction, vast data repositories in the KG format have been obtained such as Freebase and YAGO. However, traditional techniques for rule learning are not scalable for KGs. This paper presents a new approach RLvLR to learning rules from KGs by using the technique of embedding in representation learning together with a new sampling method. Experimental results show that our system outperforms some state-of-the-art systems. Specifically, for massive KGs with hundreds of predicates and over 10M facts, RLvLR is much faster and can learn much more quality rules than major systems for rule learning in KGs such as AMIE+. We also used the RLvLR-mined rules in an inference module to carry out the link prediction task. In this task, RLvLR outperformed Neural LP, a state-of-the-art link prediction system, in both runtime and accuracy.
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Tena Cucala, David J., Bernardo Cuenca Grau, and Boris Motik. "Faithful Approaches to Rule Learning." In 19th International Conference on Principles of Knowledge Representation and Reasoning {KR-2022}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/kr.2022/50.

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Rule learning involves developing machine learning models that can be applied to a set of logical facts to predict additional facts, as well as providing methods for extracting from the learned model a set of logical rules that explain symbolically the model's predictions. Existing such approaches, however, do not describe formally the relationship between the model's predictions and the derivations of the extracted rules; rather, it is often claimed without justification that the extracted rules `approximate' or `explain' the model, and rule quality is evaluated by manual inspection. In this paper, we study the formal properties of Neural-LP--a prominent rule learning approach. We show that the rules extracted from Neural-LP models can be both unsound and incomplete: on the same input dataset, the extracted rules can derive facts not predicted by the model, and the model can make predictions not derived by the extracted rules. We also propose a modification to the Neural-LP model that ensures that the extracted rules are always sound and complete. Finally, we show that, on several prominent benchmarks, the classification performance of our modified model is comparable to that of the standard Neural-LP model. Thus, faithful learning of rules is feasible from both a theoretical and practical point of view.
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Corea, Carl, Matthias Thimm, and Patrick Delfmann. "Measuring Inconsistency over Sequences of Business Rule Cases." In 18th International Conference on Principles of Knowledge Representation and Reasoning {KR-2021}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/kr.2021/64.

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We investigate inconsistency and culpability measures for multisets of business rule bases. As companies might encounter thousands of rule bases daily, studying not only individual rule bases separately, but rather also their interrelations, becomes necessary. As current works on inconsistency measurement focus on assessing individual rule bases, we therefore present an extension of those works in the domain of business rules management. We show how arbitrary culpability measures (for single rule bases) can be automatically transformed for multisets, propose new rationality postulates for this setting, and investigate the complexity of central aspects regarding multi-rule base inconsistency measurement.
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Buron, Maxime, Marie-Laure Mugnier, and Michaël Thomazo. "Parallelisable Existential Rules: a Story of Pieces." In 18th International Conference on Principles of Knowledge Representation and Reasoning {KR-2021}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/kr.2021/16.

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In this paper, we consider existential rules, an expressive formalism well adapted to the representation of ontological knowledge, as well as data-to-ontology mappings in the context of ontology-based data integration. The chase is a fundamental tool to do reasoning with existential rules as it computes all the facts entailed by the rules from a database instance. We introduce parallelisable sets of existential rules, for which the chase can be computed in a single breadth-first step from any instance. The question we investigate is the characterization of such rule sets. We show that parallelisable rule sets are exactly those rule sets both bounded for the chase and belonging to a novel class of rules, called pieceful. The pieceful class includes in particular frontier-guarded existential rules and (plain) datalog. We also give another characterization of parallelisable rule sets in terms of rule composition based on rewriting.
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Wu, Hong, Zhe Wang, Kewen Wang, and Yi-Dong Shen. "Learning Typed Rules over Knowledge Graphs." In 19th International Conference on Principles of Knowledge Representation and Reasoning {KR-2022}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/kr.2022/51.

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Rule learning from large datasets has regained extensive interest as rules are useful for developing explainable approaches to many applications in knowledge graphs. However, existing methods for rule learning are still limited in terms of scalability and rule quality. This paper presents a new method for learning typed rules by employing entity class information. Our experimental evaluation shows the superiority of our system compared to state-of-the-art rule learners. In particular, we demonstrate the usefulness of typed rules in reasoning for link prediction.
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Clark, Matthew A., and Kuldip S. Rattan. "Hybrid representation of rule-based systems." In HSCC '15: 18th International Conference on Hybrid Systems: Computation and Control. New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2728606.2728649.

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Morak, Michael. "Sticky Existential Rules and Disjunction are Incompatible." In 18th International Conference on Principles of Knowledge Representation and Reasoning {KR-2021}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/kr.2021/71.

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Stickiness is one of the well-known properties in the literature that guarantees decidability of query answering under sets of existential rules, that is, Datalog rules extended with existential quantification in rule heads. In this note, we investigate whether this remains true in the case when rule heads are allowed to be disjunctive. We answer this question in the negative, providing a strong undecidability result that shows that the concept of stickiness cannot be extended to disjunctive existential rules, even when considering only fixed atomic queries and a fixed set of rules. This provides evidence that, in order to keep query answering decidable, a stronger property than stickiness is needed in the disjunctive case.
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Gottlob, Georg, Marco Manna, and Andreas Pieris. "Multi-head Guarded Existential Rules Over Fixed Signatures." In 17th International Conference on Principles of Knowledge Representation and Reasoning {KR-2020}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/kr.2020/45.

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Guarded existential rules form a robust rule-based language for modelling ontologies. The central problem of ontology-based query answering, as well as the notion of polynomial combined rewritability, have been extensively studied during the last years for this formalism. However, the relevant setting where the underlying signature is considered to be fixed is far from being well understood. All the existing results on ontology-based query answering and polynomial combined rewritability assume rule heads with one atom, while existential rules in real ontologies are typically coming with multi-heads consisting of several atoms. We aim to fill this gap.
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van Kuyck, Raf, and Beatrice Van Buggenhout. "A model for rule based legal knowledge representation." In the sixth international conference. New York, New York, USA: ACM Press, 1997. http://dx.doi.org/10.1145/261618.261667.

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Faeder, James R., Michael L. Blinov, and William S. Hlavacek. "Graphical rule-based representation of signal-transduction networks." In the 2005 ACM symposium. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1066677.1066712.

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Reports on the topic "Rule Representation"

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Kemoklidze, Nino. Proportional Representation: Implications for Georgia. Institute of Development Studies, June 2022. http://dx.doi.org/10.19088/k4d.2022.111.

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In a process that spanned over three years, Georgia adopted some important changes to its constitution that is meant to complete the country’s transition from a “semi-presidential to a parliamentary system of governance” (Civil.ge, 17 Dec. 2018). In the last 2020 parliamentary elections, Georgia’s current (revised) electoral mixed system was already the most proportional the country had seen in three decades (Bogishvili, 2020). 120 Members of Parliament (MPs) were elected proportionally by a party list (previously the number was 77) and the remaining 30 were single mandate (majoritarian) MPs elected by the ‘first-past-the-post’ rule (previous number was 73) (Bogishvili, 2020; OSCE, 2021, p.6). However, in the next parliamentary elections, due to take place in 2024, Georgia is meant to move to a fully proportional system (Civil.ge, 17 Dec. 2018). This rapid review explores some of the questions surrounding proportional representation in Georgia. In particular, what do these constitutional changes mean for Georgia? What might be some of the implications of Georgia’s move to proportional representation in 2024 and how might this affect governance? The report examines some of the main aspects of these constitutional changes during 2017-20 and puts them in context. It outlines some of the main discussions in Georgia concerning opportunities and challenges often associated with proportional representation and highlights some of the main points that emerge from these discussions on the future dynamics of governance in Georgia. Material summarised in this report is based on a mixture of (online) newspaper articles, government and other reports, and policy, and practitioner-based literature.
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Touretzky, David S., III Elvgren, and Gillette. Rule Representations in a Connectionist Chunker. Fort Belvoir, VA: Defense Technical Information Center, March 1990. http://dx.doi.org/10.21236/ada225535.

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Horrocks, Ian, Ulrike Sattler, and Stephan Tobies. A Description Logic with Transitive and Converse Roles, Role Hierarchies and Qualifying Number Restrictions. Aachen University of Technology, 1999. http://dx.doi.org/10.25368/2022.94.

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As widely argued [HG97; Sat96], transitive roles play an important role in the adequate representation of aggregated objects: they allow these objects to be described by referring to their parts without specifying a level of decomposition. In [HG97], the Description Logic (DL) ALCHR+ is presented, which extends ALC with transitive roles and a role hierarchy. It is argued in [Sat98] that ALCHR+ is well-suited to the representation of aggregated objects in applications that require various part-whole relations to be distinguished, some of which are transitive. However, ALCHR+ allows neither the description of parts by means of the whole to which they belong, or vice versa. To overcome this limitation, we present the DL SHI which allows the use of, for example, has part as well as is part of. To achieve this, ALCHR+ was extended with inverse roles. It could be argued that, instead of defining yet another DL, one could make use of the results presented in [DL96] and use ALC extended with role expressions which include transitive closure and inverse operators. The reason for not proceeding like this is the fact that transitive roles can be implemented more efficiently than the transitive closure of roles (see [HG97]), although they lead to the same complexity class (ExpTime-hard) when added, together with role hierarchies, to ALC. Furthermore, it is still an open question whether the transitive closure of roles together with inverse roles necessitates the use of the cut rule [DM98], and this rule leads to an algorithm with very bad behaviour. We will present an algorithm for SHI without such a rule. Furthermore, we enrich the language with functional restrictions and, finally, with qualifying number restrictions. We give sound and complete decision proceduresfor the resulting logics that are derived from the initial algorithm for SHI. The structure of this report is as follows: In Section 2, we introduce the DL SI and present a tableaux algorithm for satisfiability (and subsumption) of SI-concepts—in another report [HST98] we prove that this algorithm can be refined to run in polynomial space. In Section 3 we add role hierarchies to SI and show how the algorithm can be modified to handle this extension appropriately. Please note that this logic, namely SHI, allows for the internalisation of general concept inclusion axioms, one of the most general form of terminological axioms. In Section 4 we augment SHI with functional restrictions and, using the so-called pairwise-blocking technique, the algorithm can be adapted to this extension as well. Finally, in Section 5, we show that standard techniques for handling qualifying number restrictions [HB91;BBH96] together with the techniques described in previous sections can be used to decide satisfiability and subsumption for SHIQ, namely ALC extended with transitive and inverse roles, role hierarchies, and qualifying number restrictions. Although Section 5 heavily depends on the previous sections, we have made it self-contained, i.e. it contains all necessary definitions and proofs from scratch, for a better readability. Building on the previous sections, Section 6 presents an algorithm that decides the satisfiability of SHIQ-ABoxes.
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Kállai, Péter. How to Lose (the Almost) Guaranteed Representation – Recent Developments concerning Roma Parliamentary Representation in Hungary. European Centre for Minority Issues, March 2022. http://dx.doi.org/10.53779/djpm0924.

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As the Roma National Self-Government in Hungary failed to draw up its electoral list for the 2022 elections, it seemed that nobody would represent the most populous minority in Parliament; at least not within the framework of the preferential mandate system. This blog post covers the circumstances and developments behind this paradoxical situation and explains how uncompromising political wings have caused this outcome. The incumbent Roma minority advocate in Parliament and his allies worked hard to prevent anyone else from obtaining the first position on the electoral list and thus becoming a member of parliament, while the other political wing within the Roma self-government ruled out the re-election of the sitting advocate. As the author points out, however, the main problem lies in the very nature of the system, namely in the lack of real internal competition. Interestingly, as recent developments show, other Roma politicians may get elected on the party lists of both sides of the political spectrum.
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Garg, Deepak, Denis Serenyi, Frank Pfenning, and Brian Witten. A Logical Representation of Common Rules for Controlling Access to Classified Information. Fort Belvoir, VA: Defense Technical Information Center, June 2009. http://dx.doi.org/10.21236/ada506998.

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Legg, S. Abstract Syntax Notation X (ASN.X) Representation of Encoding Instructions for the XML Encoding Rules (XER). RFC Editor, July 2007. http://dx.doi.org/10.17487/rfc4914.

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Legg, S. Abstract Syntax Notation X (ASN.X) Representation of Encoding Instructions for the Generic String Encoding Rules (GSER). RFC Editor, July 2007. http://dx.doi.org/10.17487/rfc4913.

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Ye, Guosheng, Mark Messner, and T. Sham. Example Evaluation of a Representative Heat Pipe Test Article Design for Structural Acceptability using ASME Design Rules. Office of Scientific and Technical Information (OSTI), September 2020. http://dx.doi.org/10.2172/1658587.

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