Готові списки джерел за темами / Ruleset generation

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Добірка наукової літератури з теми "Ruleset generation"

Автор: Grafiati

Опубліковано: 18 листопада 2024

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Статті в журналах з теми "Ruleset generation"

Alharbi, Fares, Gautam Siddharth Kashyap, and Budoor Ahmad Allehyani. "Automated Ruleset Generation for “HTTPS Everywhere”." International Journal of Information Security and Privacy 18, no. 1 (July 17, 2024): 1–14. http://dx.doi.org/10.4018/ijisp.347330.

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This paper details the implementation of a Web crawler aimed at automating ruleset construction for “HTTPS Everywhere,” with a goal to convert HTTP URLs to secure HTTPS equivalents for enhanced communication security. Developed within a seven-month timeframe, the crawler faced challenges in verifying HTTPS support, varying based on SSL certificate existence and validity. Successful ruleset creation and testing in Firefox and Chrome, adhering to stylistic standards, demonstrated the potential for effective development. The paper explores improving productivity through alternative libraries like Scrapy and Scrapy Cloud. While certain goals, such as in-depth cryptocurrency analysis and web crawler background reading, were unmet due to time constraints, valuable insights were gained. The conclusion underscores the difficulties, successes, and promises of automating ruleset generation through web crawlers for “HTTPS Everywhere,” offering valuable recommendations for advancing web security.

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Rijati, Nova, Diana Purwitasar, Surya Sumpeno, and Mauridhi Hery Purnomo. "A Rule-Generation Model for Class Imbalances to Detect Student Entrepreneurship Based on the Theory of Planned Behavior." Cybernetics and Information Technologies 22, no. 2 (June 1, 2022): 160–78. http://dx.doi.org/10.2478/cait-2022-0023.

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Abstract The ability to identify the entrepreneurial potential of students enables higher education institutions to contribute to the economic and social development of a country. Current research trends regarding the detection of student entrepreneurial potential have the greatest challenge in the unequal ratio of datasets. This study proposes a rule-generation model in an imbalanced situation to classify student entrepreneurship based on the Theory of Planned Behavior (TPB). The result is a ruleset that is used for the early detection of student entrepreneurial potential. The proposed method consists of three main stages, namely preprocessing data to classify data based on TPB variables, generating a dataset by clustering and selecting attributes by sampling to balance the data, and finally generating a ruleset. Furthermore, the results of the detecting ruleset have been evaluated with actual data from the student tracer study as ground truth. The evaluation results show high accuracy so that the ruleset can be applied to the higher education environment in the future.

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Opoku, Samuel King. "A Robust Mechanism for Categorizing Context-Aware Applications into Generations." European Journal of Electrical Engineering and Computer Science 5, no. 6 (November 24, 2021): 10–16. http://dx.doi.org/10.24018/ejece.2021.5.6.371.

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The hunt to categorize context-aware applications has been a prevalent issue to developers of context-aware applications. The previous categorizations were based on the functions of the applications. These mechanisms yielded limited results since many applications could not be categorized. This paper categorizes applications into four generations based on developmental trends through a literature survey. The first generation applications focused on data acquisition and used hardware sensors. The second generation applications focused on knowledge acquisition and used software sensors, semantic language and ontology-based modelling languages. The third generation applications focused on intelligent reasoning and used mechanisms to handle information uncertainty. The fourth generation applications deprecate cumbersome ruleset implementations and focus on artificial intelligence whilst taking into consideration the effect of the dynamics of users’ background and preference on contextual information. The study demonstrated that when applications, methods or technologies can be categorized over some time, it is better to classify them into generations.

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Coscia, Antonio, Vincenzo Dentamaro, Stefano Galantucci, Antonio Maci, and Giuseppe Pirlo. "Automatic decision tree-based NIDPS ruleset generation for DoS/DDoS attacks." Journal of Information Security and Applications 82 (May 2024): 103736. http://dx.doi.org/10.1016/j.jisa.2024.103736.

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Capasso-Ballesteros, Italo Felipe, and Fernando De la Rosa-Rosero. "Semi-automatic construction of video game design prototypes with MaruGen." Revista Facultad de Ingeniería Universidad de Antioquia, no. 99 (March 27, 2020): 9–20. http://dx.doi.org/10.17533/udea.redin.20200369.

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Machinations Ruleset Generator (MaruGen) is a semi-automatic system for the generation of mechanics, rules, spaces (environments), and missions for video games. The objective of this system is to offer an expression mechanism for the video game designer role based on the definition of rules, and the ability to explore the concepts of progression and emergence in video games by using a formal, usable, and defined tool to design games with innovative and complex elements, and behaviors defined from combinations of basic elements. Based on the expressed designs and with the participation of programmers and video game artists, MaruGen allows the generation of agile video game prototypes in the Unity game engine. These prototypes can be analyzed by the entire workgroup to look for games with diverse complexities that make them attractive to their users. MaruGen is based on the expression of rules on elements of interest in video games and the rewriting mechanism using L-Systems for the generation of procedural content. MaruGen was evaluated in the construction of the Cubic Explorer video game and tested by gamers and video game developers during the Game Jam Ludum Dare 38.

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Gerussi, Alessio, Damiano Verda, Claudio Cappadona, Laura Cristoferi, Davide Paolo Bernasconi, Sandro Bottaro, Marco Carbone, Marco Muselli, Pietro Invernizzi, and Rosanna Asselta. "LLM-PBC: Logic Learning Machine-Based Explainable Rules Accurately Stratify the Genetic Risk of Primary Biliary Cholangitis." Journal of Personalized Medicine 12, no. 10 (September 26, 2022): 1587. http://dx.doi.org/10.3390/jpm12101587.

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Background: The application of Machine Learning (ML) to genetic individual-level data represents a foreseeable advancement for the field, which is still in its infancy. Here, we aimed to evaluate the feasibility and accuracy of an ML-based model for disease risk prediction applied to Primary Biliary Cholangitis (PBC). Methods: Genome-wide significant variants identified in subjects of European ancestry in the recently released second international meta-analysis of GWAS in PBC were used as input data. Quality-checked, individual genomic data from two Italian cohorts were used. The ML included the following steps: import of genotype and phenotype data, genetic variant selection, supervised classification of PBC by genotype, generation of “if-then” rules for disease prediction by logic learning machine (LLM), and model validation in a different cohort. Results: The training cohort included 1345 individuals: 444 were PBC cases and 901 were healthy controls. After pre-processing, 41,899 variants entered the analysis. Several configurations of parameters related to feature selection were simulated. The best LLM model reached an Accuracy of 71.7%, a Matthews correlation coefficient of 0.29, a Youden’s value of 0.21, a Sensitivity of 0.28, a Specificity of 0.93, a Positive Predictive Value of 0.66, and a Negative Predictive Value of 0.72. Thirty-eight rules were generated. The rule with the highest covering (19.14) included the following genes: RIN3, KANSL1, TIMMDC1, TNPO3. The validation cohort included 834 individuals: 255 cases and 579 controls. By applying the ruleset derived in the training cohort, the Area under the Curve of the model was 0.73. Conclusions: This study represents the first illustration of an ML model applied to common variants associated with PBC. Our approach is computationally feasible, leverages individual-level data to generate intelligible rules, and can be used for disease prediction in at-risk individuals.

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Gowda, Shashi, Yingbo Ma, Alessandro Cheli, Maja Gwóźzdź, Viral B. Shah, Alan Edelman, and Christopher Rackauckas. "High-performance symbolic-numerics via multiple dispatch." ACM Communications in Computer Algebra 55, no. 3 (September 2021): 92–96. http://dx.doi.org/10.1145/3511528.3511535.

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As mathematical computing becomes more democratized in high-level languages, high-performance symbolic-numeric systems are necessary for domain scientists and engineers to get the best performance out of their machine without deep knowledge of code optimization. Naturally, users need different term types either to have different algebraic properties for them, or to use efficient data structures. To this end, we developed Symbolics.jl, an extendable symbolic system which uses dynamic multiple dispatch to change behavior depending on the domain needs. In this work we detail an underlying abstract term interface which allows for speed without sacrificing generality. We show that by formalizing a generic API on actions independent of implementation, we can retroactively add optimized data structures to our system without changing the pre-existing term rewriters. We showcase how this can be used to optimize term construction and give a 113x acceleration on general symbolic transformations. Further, we show that such a generic API allows for complementary term-rewriting implementations. Exploiting this feature, we demonstrate the ability to swap between classical term-rewriting simplifiers and e-graph-based term-rewriting simplifiers. We illustrate how this symbolic system improves numerical computing tasks by showcasing an e-graph ruleset which minimizes the number of CPU cycles during expression evaluation, and demonstrate how it simplifies a real-world reaction-network simulation to halve the runtime. Additionally, we show a reaction-diffusion partial differential equation solver which is able to be automatically converted into symbolic expressions via multiple dispatch tracing, which is subsequently accelerated and parallelized to give a 157x simulation speedup. Together, this presents Symbolics.jl as a next-generation symbolic-numeric computing environment geared towards modeling and simulation.

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Liu, Zhen Yu, Zhi Hui Song, Rui Qing Yan, and Zeng Zhang. "The Optimization Algorithm of Association Rules Mining." Applied Mechanics and Materials 614 (September 2014): 405–8. http://dx.doi.org/10.4028/www.scientific.net/amm.614.405.

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Frequent itemsets mining is the core part of association rule mining. At present most of the research on association rules mining is focused on how to improve the efficiency of mining frequent itemsets , however, the rule sets generated from frequent itemsets are the final results presented to decision makers for making, so how to optimize the rulesets generation process and the final rules is also worthy of attention. Based on encoding the dataset, this paper proposes a encoding method to speed up the generation process of frequent itemsets and proposes a subset tree to generate association rules which can simplify the generation process of rules and narrow the rulesets presented to decision makers.

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Hee Chang, Park. "Generation Method of Association Rules by Symmetric Hellinger Measure." Korean Data Analysis Society 19, no. 5 (October 31, 2017): 2323–29. http://dx.doi.org/10.37727/jkdas.2017.19.5.2323.

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Sakai, Hiroshi, and Michinori Nakata. "An Application of Discernibility Functions to Generating Minimal Rules in Non-Deterministic Information Systems." Journal of Advanced Computational Intelligence and Intelligent Informatics 10, no. 5 (September 20, 2006): 695–702. http://dx.doi.org/10.20965/jaciii.2006.p0695.

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Minimal rule generation in Non-deterministic Information Systems (NISs), which follows rough sets based rule generation in Deterministic Information Systems (DISs), is presented. According to certain rules and possible rules in NISs, minimal certain rules and minimal possible rules are defined. Discernibility functions are also introduced into NISs for generating minimal certain rules. Like minimal rule generation in DISs, the condition part of a minimal certain rule is given as a solution of an introduced discernibility function. As for generating minimal possible rules, there may be lots of discernibility functions to be solved. So, an algorithm based on an order of attributes is proposed. A tool, which generates minimal certain rules and minimal possible rules, has also been implemented.

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Дисертації з теми "Ruleset generation"

Haq, Ikram. "Fraud detection for online banking for scalable and distributed data." Thesis, Federation University Australia, 2020. http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/171977.

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Online fraud causes billions of dollars in losses for banks. Therefore, online banking fraud detection is an important field of study. However, there are many challenges in conducting research in fraud detection. One of the constraints is due to unavailability of bank datasets for research or the required characteristics of the attributes of the data are not available. Numeric data usually provides better performance for machine learning algorithms. Most transaction data however have categorical, or nominal features as well. Moreover, some platforms such as Apache Spark only recognizes numeric data. So, there is a need to use techniques e.g. One-hot encoding (OHE) to transform categorical features to numerical features, however OHE has challenges including the sparseness of transformed data and that the distinct values of an attribute are not always known in advance. Efficient feature engineering can improve the algorithm’s performance but usually requires detailed domain knowledge to identify correct features. Techniques like Ripple Down Rules (RDR) are suitable for fraud detection because of their low maintenance and incremental learning features. However, high classification accuracy on mixed datasets, especially for scalable data is challenging. Evaluation of RDR on distributed platforms is also challenging as it is not available on these platforms. The thesis proposes the following solutions to these challenges: • We developed a technique Highly Correlated Rule Based Uniformly Distribution (HCRUD) to generate highly correlated rule-based uniformly-distributed synthetic data. • We developed a technique One-hot Encoded Extended Compact (OHE-EC) to transform categorical features to numeric features by compacting sparse-data even if all distinct values are unknown. • We developed a technique Feature Engineering and Compact Unified Expressions (FECUE) to improve model efficiency through feature engineering where the domain of the data is not known in advance. • A Unified Expression RDR fraud deduction technique (UE-RDR) for Big data has been proposed and evaluated on the Spark platform. Empirical tests were executed on multi-node Hadoop cluster using well-known classifiers on bank data, synthetic bank datasets and publicly available datasets from UCI repository. These evaluations demonstrated substantial improvements in terms of classification accuracy, ruleset compactness and execution speed.
Doctor of Philosophy

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Gundavarapu, Madhavi. "RuleGen – A Rule Generation Application Using Multiset Decision Tables." University of Akron / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=akron1140111266.

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Koh, Yun Sing, and n/a. "Generating sporadic association rules." University of Otago. Department of Computer Science, 2007. http://adt.otago.ac.nz./public/adt-NZDU20070711.115758.

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Association rule mining is an essential part of data mining, which tries to discover associations, relationships, or correlations among sets of items. As it was initially proposed for market basket analysis, most of the previous research focuses on generating frequent patterns. This thesis focuses on finding infrequent patterns, which we call sporadic rules. They represent rare itemsets that are scattered sporadically throughout the database but with high confidence of occurring together. As sporadic rules have low support the minabssup (minimum absolute support) measure was proposed to filter out any rules with low support whose occurrence is indistinguishable from that of coincidence. There are two classes of sporadic rules: perfectly sporadic and imperfectly sporadic rules. Apriori-Inverse was then proposed for perfectly sporadic rule generation. It uses a maximum support threshold and user-defined minimum confidence threshold. This method is designed to find itemsets which consist only of items falling below a maximum support threshold. However imperfectly sporadic rules may contain items with a frequency of occurrence over the maximum support threshold. To look for these rules, variations of Apriori-Inverse, namely Fixed Threshold, Adaptive Threshold, and Hill Climbing, were proposed. However these extensions are heuristic. Thus the MIISR algorithm was proposed to find imperfectly sporadic rules using item constraints, which capture rules with a single-item consequent below the maximum support threshold. A comprehensive evaluation of sporadic rules and current interestingness measures was carried out. Our investigation suggests that current interestingness measures are not suitable for detecting sporadic rules.

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Ma, Liangjun, and Shouchuan Zhang. "Generating Fuzzy Rules For Case-based Classification." Thesis, Mälardalens högskola, Akademin för innovation, design och teknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-16444.

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As a technique to solve new problems based on previous successful cases, CBR represents significant prospects for improving the accuracy and effectiveness of unstructured decision-making problems. Similar problems have similar solutions is the main assumption. Utility oriented similarity modeling is gradually becoming an important direction for Case-based reasoning research. In this thesis, we propose a new way to represent the utility of case by using fuzzy rules. Our method could be considered as a new way to estimate case utility based on fuzzy rule based reasoning. We use modified WANG’s algorithm to generate a fuzzy if-then rule from a case pair instead of a single case. The fuzzy if-then rules have been identified as a powerful means to capture domain information for case utility approximation than traditional similarity measures based on feature weighting. The reason why we choose the WANG algorithm as the foundation is that it is a simpler and faster algorithm to generate if-then rules from examples. The generated fuzzy rules are utilized as a case matching mechanism to estimate the utility of the cases for a given problem. The given problem will be formed with each case in the case library into pairs which are treated as the inputs of fuzzy rules to determine whether or to which extent a known case is useful to the problem. One case has an estimated utility score to the given problem to help our system to make decision. The experiments on several data sets have showed the superiority of our method over traditional schemes, as well as the feasibility of learning fuzzy if-then rules from a small number of cases while still having good performances.

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Johnson, Christopher Wayne Bagai Rajiv. "Mechanical generation of concrete syntax rules for the Schütz semantic editor." Diss., A link to full text of this thesis in SOAR, 2007. http://soar.wichita.edu/dspace/handle/10057/1141.

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Thesis (M.S.)--Wichita State University, College of Liberal Arts and Sciences., Dept. of Computer Science.
"May 2007." Title from PDF title page (viewed on Dec. 26, 2007). Thesis adviser: Rajiv Bagai. Includes bibliographical references (65-66 leaves).

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Powell, Anastasia. "Generation Y : re-writing the rules on sex,love and consent /." Connect to thesis, 2007. http://eprints.unimelb.edu.au/archive/00004035.

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Fry, John, T. Galla, and J. M. Binner. "Quantitative decision-making rules for the next generation of smarter evacuations." Springer, 2015. http://hdl.handle.net/10454/17563.

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Hall, A. R. "Automatic speech recognition using morpheme structure rules for word hypothesis and dictionary generation." Thesis, London South Bank University, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.352963.

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Bakshi, Arjun. "Methodology For Generating High-Confidence Cost-Sensitive Rules For Classification." University of Cincinnati / OhioLINK, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1377868085.

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Kuri, Bless. "Sustainable generation mix as a reference in effective design of electricity market structures and rules." Thesis, University of Bath, 2006. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.440360.

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Книги з теми "Ruleset generation"

Westheimer, Julius. Generation of wealth: Time-tested rules for worry-free investing. Baltimore, Md: Bancroft Press, 1997.

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Andrianopoulos, G. An environment for the verification and code generation of temporal rules. Manchester: UMIST, 1993.

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Kell, Michael. An assessment of fiscal rules in the United Kingdom. [Washington, D.C.]: International Monetary Fund, 2001.

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Ouhalla, Jamal. Introducing transformational grammar: From rules to principles and parameters. London: E. Arnold, 1994.

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Vachon, Marc. Equally shared parenting: Rewriting the rules for a new generation of parents. New York: Penguin Group, 2010.

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Chris, Sherry. Next generation real estate: New rules for smarter home buying & faster selling. Hoboken, New Jersey: John Wiley & Sons, Inc., 2014.

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Amy, Vachon, ed. Equally shared parenting: Rewriting the rules for a new generation of parents. New York: Penguin Group, 2010.

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Fanselow, John F. Breaking rules: Generating and exploring alternatives in language teaching. New York: Longman, 1987.

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Southwick, Karen. Silicon gold rush: The next generation of high-tech stars rewrites the rules of business. New York: Wiley, 1999.

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P, Avis Joan, ed. The women who broke all the rules: How the choices of a generation changed our lives. Naperville, IL: Sourcebooks, 1999.

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Частини книг з теми "Ruleset generation"

Cook, Michael. "Generating Rules." In Procedural Generation in Game Design, 265–69. Boca Raton : Taylor & Francis, CRC Press, 2017.: A K Peters/CRC Press, 2017. http://dx.doi.org/10.1201/9781315156378-29.

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Nelson, Mark J., Julian Togelius, Cameron Browne, and Michael Cook. "Rules and Mechanics." In Procedural Content Generation in Games, 99–121. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-42716-4_6.

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Tsay, Li-Shiang, and Seunghyun Im. "Mining Non-redundant Reclassification Rules." In Next-Generation Applied Intelligence, 806–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02568-6_82.

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Michalewicz, Maciej, and Zbigniew Michalewicz. "Generation of classification rules." In Lecture Notes in Computer Science, 389–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 1991. http://dx.doi.org/10.1007/3-540-54563-8_102.

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Liu, Han, Alexander Gegov, and Mihaela Cocea. "Generation of Classification Rules." In Studies in Big Data, 29–42. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23696-4_3.

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Golani, Mati, and Opher Etzion. "Temporal Active Rules." In Next Generation Information Technologies and Systems, 159–72. Berlin, Heidelberg: Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/3-540-48521-x_12.

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Rayner, Tim. "The hacker generation." In Hacker Culture and the New Rules of Innovation, 9–29. 1 Edition. | New York : Routledge, 2018.: Routledge, 2018. http://dx.doi.org/10.4324/9781315103662-2.

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Meddouri, Nida, and Mondher Maddouri. "Boosting Formal Concepts to Discover Classification Rules." In Next-Generation Applied Intelligence, 501–10. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02568-6_51.

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Suzuki, Einoshin. "Compression-Based Measures for Mining Interesting Rules." In Next-Generation Applied Intelligence, 741–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02568-6_75.

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Wang, Shyue-Liang, Ting-Zheng Lai, Tzung-Pei Hong, and Yu-Lung Wu. "Hiding Predictive Association Rules on Horizontally Distributed Data." In Next-Generation Applied Intelligence, 133–41. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02568-6_14.

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Тези доповідей конференцій з теми "Ruleset generation"

Ostropolski-Nalewaja, Piotr, and Sebastian Rudolph. "The Sticky Path to Expressive Querying: Decidability of Navigational Queries under Existential Rules." In 21st International Conference on Principles of Knowledge Representation and Reasoning {KR-2023}, 574–84. California: International Joint Conferences on Artificial Intelligence Organization, 2024. http://dx.doi.org/10.24963/kr.2024/54.

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Extensive research in the field of ontology-based query answering has led to the identification of numerous fragments of existential rules (also known as tuple-generating dependencies) that exhibit decidable answering of atomic and conjunctive queries. Motivated by the increased theoretical and practical interest in navigational queries, this paper considers the question for which of these fragments decidability of querying extends to regular path queries (RPQs). In fact, decidability of RPQs has recently been shown to generally hold for the comprehensive family of all fragments that come with the guarantee of universal models being reasonably well-shaped (that is, being of finite cliquewidth). Yet, for the second major family of fragments, known as finite unification sets (short: fus), which are based on first-order-rewritability, corresponding results have been largely elusive so far. We complete the picture by showing that RPQ answering over arbitrary fus rulesets is undecidable. On the positive side, we establish that the problem is decidable for the prominent fus subclass of sticky rulesets, with the caveat that a very mild extension of the RPQ formalism turns the problem undecidable again.

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Wang, Yutong, Jiyuan Zheng, Qijiong Liu, Zhou Zhao, Jun Xiao, and Yueting Zhuang. "Weak Supervision Enhanced Generative Network for Question Generation." In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/528.

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Automatic question generation according to an answer within the given passage is useful for many applications, such as question answering system, dialogue system, etc. Current neural-based methods mostly take two steps which extract several important sentences based on the candidate answer through manual rules or supervised neural networks and then use an encoder-decoder framework to generate questions about these sentences. These approaches still acquire two steps and neglect the semantic relations between the answer and the context of the whole passage which is sometimes necessary for answering the question. To address this problem, we propose the Weakly Supervision Enhanced Generative Network (WeGen) which automatically discovers relevant features of the passage given the answer span in a weakly supervised manner to improve the quality of generated questions. More specifically, we devise a discriminator, Relation Guider, to capture the relations between the passage and the associated answer and then the Multi-Interaction mechanism is deployed to transfer the knowledge dynamically for our question generation system. Experiments show the effectiveness of our method in both automatic evaluations and human evaluations.

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Jensen, Simon Holm, Suresh Thummalapenta, Saurabh Sinha, and Satish Chandra. "Test Generation from Business Rules." In 2015 IEEE 8th International Conference on Software Testing, Verification and Validation (ICST). IEEE, 2015. http://dx.doi.org/10.1109/icst.2015.7102608.

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Berramla, Karima, El Abbassia Deba, Mohamed El Kamel, and Abou El Hassen. "Semi-Automatic Generation of Transformation Rules." In the 2nd International Conference. New York, New York, USA: ACM Press, 2019. http://dx.doi.org/10.1145/3320326.3320373.

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Relue, Richard, Xindong Wu, and Hao Huang. "Efficient runtime generation of association rules." In the tenth international conference. New York, New York, USA: ACM Press, 2001. http://dx.doi.org/10.1145/502585.502664.

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Xu, Yue, and Yuefeng Li. "Generating concise association rules." In the sixteenth ACM conference. New York, New York, USA: ACM Press, 2007. http://dx.doi.org/10.1145/1321440.1321549.

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Liu, Xianggen, Wenqiang Lei, Jiancheng Lv, and Jizhe Zhou. "Abstract Rule Learning for Paraphrase Generation." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. California: International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/593.

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In early years, paraphrase generation typically adopts rule-based methods, which are interpretable and able to make global transformations to the original sentence. But they struggle to produce fluent paraphrases. Recently, deep neural networks have shown impressive performances in generating paraphrases. However, the current neural models are black boxes and are prone to make local modifications to the inputs. In this work, we combine these two approaches into RULER, a novel approach that performs abstract rule learning for paraphrasing. The key idea is to explicitly learn generalizable rules that could enhance the paraphrase generation process of neural networks. In RULER, we first propose a rule generalizability metric to guide the model to generate rules underlying the paraphrasing. Then, we leverage neural networks to generate paraphrases by refining the sentences transformed by the learned rules. Extensive experimental results demonstrate the superiority of RULER over previous state-of-the-art methods in terms of paraphrase quality, generalization ability and interpretability.

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Karklin, Linard N., Micha Oren, Dragos Dudau, and James D. Jordan. "Bridging nanometer design-to-manufacturing gap: automated design rules correction and silicon verification." In Photomask and Next Generation Lithography Mask Technology X, edited by Hiroyoshi Tanabe. SPIE, 2003. http://dx.doi.org/10.1117/12.504251.

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Mielczarski, Wladyslaw, Blazej Olek, and Michal Wierzbowski. "Market rules in optimization of distributed generation." In 2012 9th International Conference on the European Energy Market (EEM 2012). IEEE, 2012. http://dx.doi.org/10.1109/eem.2012.6254747.

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Rodrigues, N., M. Dionísio, A. Gonçalves, L. G. Magalhães, J. P. Moura, and A. Chalmers. "Incorporating legal rules on procedural house generation." In the 24th Spring Conference. New York, New York, USA: ACM Press, 2010. http://dx.doi.org/10.1145/1921264.1921279.

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Звіти організацій з теми "Ruleset generation"

Davies, K., and A. Freytag. Representing Label Generation Rulesets Using XML. RFC Editor, August 2016. http://dx.doi.org/10.17487/rfc7940.

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Freytag, A. Guidance on Designing Label Generation Rulesets (LGRs) Supporting Variant Labels. RFC Editor, August 2017. http://dx.doi.org/10.17487/rfc8228.

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Banga, Karishma, and Alexander Beyleveld. Are Trade Rules Undermining Taxation of the Digital Economy in Africa? Institute of Development Studies, February 2024. http://dx.doi.org/10.19088/ictd.2024.007.

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African countries are currently considering provisions in the AfCFTA and at the WTO to liberalise digital trade. As they face mounting fiscal pressures, it is imperative that they beware the implications of digital trade provisions for their ability to tax their digital economy. In this paper, we develop a comprehensive framework for analysing the impact of trade rules on tax regimes in the digital economy, with a focus on Kenya, Rwanda, and South Africa. We explore how trade rules ostensibly shape tax policies and their implications for revenue generation. By examining rules regulating trade in services and the imposition of customs duties on electronic transmissions, we identify how these rules may directly impact tax policies and limit revenue generation possibilities. Moreover, digital trade rules, such as those related to data flows, localisation, and source code sharing, have the capacity to produce both indirect and administrative effects on tax measures. These rules can alter tax structures, taxation rights, data collection, and the capacity to monitor and implement tax measures. Our findings shed light on the complex interplay between trade rules and tax measures, highlighting potential challenges and opportunities for revenue generation from the digital economy in African countries.

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Jakeman, John Davis, and Akil Narayan. Generation and application of multivariate polynomial quadrature rules. Office of Scientific and Technical Information (OSTI), September 2017. http://dx.doi.org/10.2172/1510651.

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Lyness, J., and W. Newman. A classification of lattice rules using the reciprocal lattice generator matrix. Office of Scientific and Technical Information (OSTI), June 1989. http://dx.doi.org/10.2172/5886138.

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Hunsaker, Jr, D., R. McLean, G. Cada, E. Liebsch, R. Graham, C. Garten, C. Hunsaker, et al. Assessing the potential environmental impacts of proposed rules affecting future electric power generation in the United States. Office of Scientific and Technical Information (OSTI), February 1990. http://dx.doi.org/10.2172/6993330.

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Adame Espinosa, Francisco. Monetary Rules, Financial Stability and Welfare in a non-Ricardian Framework. Banco de México, November 2023. http://dx.doi.org/10.36095/banxico/di.2023.14.

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This work is based on a new Keynesian theoretical model for an advanced economy, which incorporates overlapping generations to analyze a channel through which fluctuations in household financial wealth influence aggregate demand. The optimal monetary policy, corresponding to that of a central planner maximizing households' welfare, aims to mitigate financial fluctuations while simultaneously reducing variability in inflation and the output gap. The model is calibrated for the United States and reproduces the effect of variations in the price of financial assets on aggregate demand. The results show, first, that in the presence of productivity, financial, and demand shocks, optimal monetary policy significantly improves aggregate welfare by stabilizing financial fluctuations that impact households' wealth. Secondly, in the face of productivity and financial shocks, an augmented monetary rule responding explicitly to fluctuations in the price of financial assets, in addition to inflation and output gaps, can reproduce the welfare achieved under optimal monetary policy. However, this is not the case for demand shocks.

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Vickerman, Michael Jay. Sowing the Seeds for a Bountiful Harvest: Shaping the Rules and Creating the Tools for Wisconsin's Next Generation of Wind Farms. Office of Scientific and Technical Information (OSTI), March 2012. http://dx.doi.org/10.2172/1077000.

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Michel, Bob, and Tatiana Falcão. Taxing Profits from International Maritime Shipping in Africa: Past, Present and Future of UN Model Article 8 (Alternative B). Institute of Development Studies (IDS), November 2021. http://dx.doi.org/10.19088/ictd.2021.023.

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International maritime shipping is an essential part of global business. Since the establishment of the current international tax regime in the 1920s, there has been a consensus that profits generated by this business are taxable only in the residence state –the state where the shipowners are located. Source states – the port states where business physically takes place – are generally expected to exempt income from international shipping. This standard is currently reflected in Article 8 of the OECD Model and Article 8 (Alternative A) of the UN Model, and is incorporated in the vast majority of bilateral tax treaties currently in force. Exclusive residence state taxation of shipping profits is problematic when the size of mercantile fleets and shipping flows between two states are of unequal size. This is often the case in relations between a developed and developing country. The latter often lack a substantial domestic mercantile fleet, but serve as an important revenue-generating port state for the fleet of the developed country. To come to a more balanced allocation of taxing rights in such a case, a source taxation alternative has been inserted in UN Model Article 8 (Alternative B). From its inception, Article 8B has been labelled impractical due to the lack of guidance on core issues, like sourcing rules and profit allocation. This gap is said to explain the low adoption rate of Article 8B in global tax treaty practice. In reality, tax treaty practice regarding Article 8B is heavily concentrated and flourishing in a handful of countries in South/South-East Asia – Bangladesh, India, Indonesia, Myanmar, Pakistan, the Philippines, Sri Lanka and Thailand. All these countries subject non-resident shipping income to tax in their domestic income tax laws. Except for India, all countries are able to exercise these domestic tax law rules in relation to shipping enterprises located in the biggest shipowner states, either because they have a treaty in place that provides for source taxation or because there is no treaty at all and thus no restriction of domestic law. None of the relevant tax treaties contain a provision that incorporates the exact wording of Article 8B of the UN Model. If other countries, like coastal countries in sub-Saharan Africa, are looking to implement source taxation of maritime shipping income in the future, they are advised to draw on the South/South-East Asian experience. Best practice can be distilled regarding sourcing rule, source tax limitation, profit attribution and method of taxation (on gross or net basis). In addition to technical guidance on tax, the South/South-East Asian experience also provides important general policy considerations countries should take into account when determining whether source taxation of maritime shipping profits is an appropriate target for their future tax treaty negotiations.

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Bergsen, Pepijn, Carolina Caeiro, Harriet Moynihan, Marianne Schneider-Petsinger, and Isabella Wilkinson. Digital trade and digital technical standards. Royal Institute of International Affairs, January 2022. http://dx.doi.org/10.55317/9781784135133.

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There is increasing impetus for stronger cooperation between the US, EU and UK on digital technology governance. Drivers of this trend include the economic incentives arising from opportunities for digital trade; the ambition for digital technology governance to be underpinned by shared values, including support for a democratic, open and global internet; and the need to respond to geopolitical competition, especially from China. Two specific areas of governance in which there is concrete potential to collaborate, and in which policymakers have indicated significant ambitions to do so, are digital trade and digital technical standards. - To leverage strategic opportunities for digital trade, the US, EU and UK need to continue identifying and promoting principles based on shared values and agendas, and demonstrate joint leadership at the global level, including in the World Trade Organization (WTO) on e-commerce. - Policy actors in the US, EU and UK should work individually and collectively to build on the latest generation of digital trade agreements. This will help to promote closer alignment on digital rules and standards, and support the establishment of more up-to-date models for innovation and governance. - Collaborating on digital technical standards, particularly those underlying internet governance and emerging technologies, offers the US, EU and UK strategic opportunities to build a vision of digital technology governance rooted in multi-stakeholder participation and democratic values. This can provide a strong alternative to standards proposals such as China’s ‘New IP’ system. - Policy actors should seek to expand strategic cooperation on standards development among the US, EU and UK, among like-minded countries, and among states that are undecided on the direction of their technology governance, including in the Global South. They should also take practical steps to incorporate the views and expertise of the technology industry, the broader private sector, academia and civil society. By promoting best-practice governance models that are anticipatory, dynamic and flexible, transatlantic efforts for cooperation on digital regulation can better account for the rapid pace of technological change. Early evidence of this more forward-looking approach is emerging through the EU’s proposed regulation of digital services and artificial intelligence (AI), and in the UK’s proposed legislation to tackle online harms. The recently launched EU-US Trade and Technology Council is a particularly valuable platform for strengthening cooperation in this arena. But transatlantic efforts to promote a model of digital governance predicated on democratic values would stand an even greater chance of success if the council’s work were more connected to efforts by the UK and other leading democracies

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