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Related papers: Mining Frequent Structures in Conceptual Models

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In software system design, one of the purposes of diagrammatic modeling is to explain something (e.g., data tables) to others. Very often, syntax of diagrams is specified while the intended meaning of diagrammatic constructs remains…

Software Engineering · Computer Science 2022-10-05 Sabah Al-Fedaghi

Patents provide a rich source of information about design innovations. Patent mining techniques employ various technologies, such as text mining, machine learning, natural language processing, and ontology-building techniques. An automated…

Databases · Computer Science 2024-02-05 Manal E. Helal , Mohammed E. Helal

The demands on visual recognition systems do not end with the complexity offered by current large-scale image datasets, such as ImageNet. In consequence, we need curious and continuously learning algorithms that actively acquire knowledge…

Computer Vision and Pattern Recognition · Computer Science 2016-12-20 Christoph Käding , Erik Rodner , Alexander Freytag , Joachim Denzler

When we speak, write or listen, we continuously make predictions based on our knowledge of a language's grammar. Remarkably, children acquire this grammatical knowledge within just a few years, enabling them to understand and generalise to…

Computation and Language · Computer Science 2024-11-26 Jaap Jumelet

Modelling musical structure is vital yet challenging for artificial intelligence systems that generate symbolic music compositions. This literature review dissects the evolution of techniques for incorporating coherent structure, from…

Sound · Computer Science 2024-03-14 Keshav Bhandari , Simon Colton

The previously introduced Modular Ontology Modeling methodology (MOMo) attempts to mimic the human analogical process by using modular patterns to assemble more complex concepts. To support this, MOMo organizes organizes ontology design…

Artificial Intelligence · Computer Science 2024-03-01 Andrew Eells , Brandon Dave , Pascal Hitzler , Cogan Shimizu

Extracting structured information from unstructured text is crucial for modeling real-world processes, but traditional schema mining relies on semi-structured data, limiting scalability. This paper introduces schema-miner, a novel tool that…

Recent pre-trained language models (PLMs) equipped with foundation reasoning skills have shown remarkable performance on downstream complex tasks. However, the significant structure reasoning skill has been rarely studied, which involves…

Computation and Language · Computer Science 2023-07-18 Siyuan Wang , Zhongyu Wei , Jiarong Xu , Taishan Li , Zhihao Fan

Simulation models are an absolute necessity in the human and social sciences, which can only very exceptionally use experimental science methods to construct their knowledge. Models enable the simulation of social processes by replacing the…

Computers and Society · Computer Science 2020-01-06 J. Raimbault , D. Pumain

[Spreadsheet] Models are invaluable tools for strategic planning. Models help key decision makers develop a shared conceptual understanding of complex decisions, identify sensitivity factors and test management scenarios. Different…

Human-Computer Interaction · Computer Science 2024-12-31 Paula Jennings

Despite the remarkable success of large large-scale neural networks, we still lack unified notation for thinking about and describing their representational spaces. We lack methods to reliably describe how their representations are…

Machine Learning · Computer Science 2025-06-02 Henry Conklin

Frequent sequence mining methods often make use of constraints to control which subsequences should be mined. A variety of such subsequence constraints has been studied in the literature, including length, gap, span, regular-expression, and…

Databases · Computer Science 2016-10-14 Kaustubh Beedkar , Rainer Gemulla

Molecular property prediction and generative design via deep learning models has been the subject of intense research given its potential to accelerate development of new, high-performance materials. More recently, these workflows have been…

Artificial Intelligence · Computer Science 2024-12-16 Nathaniel H. Park , Tiffany J. Callahan , James L. Hedrick , Tim Erdmann , Sara Capponi

Dynamic topic modeling is widely used to analyze evolving trends in scientific literature, medical records, and social media. Traditional topic models represent each topic through a single probability vector on the multinomial simplex and…

Machine Learning · Computer Science 2026-05-28 Hanjia Gao , Hanwen Ye , Qing Nie , Annie Qu

This paper presents a novel method for structural data recognition using a large number of graph models. In general, prevalent methods for structural data recognition have two shortcomings: 1) Only a single model is used to capture…

Machine Learning · Computer Science 2020-04-15 Tomo Miyazaki , Shinichiro Omachi

Recently, considerable research effort has been devoted to developing deep architectures for topic models to learn topic structures. Although several deep models have been proposed to learn better topic proportions of documents, how to…

Information Retrieval · Computer Science 2018-11-05 He Zhao , Lan Du , Wray Buntine , Mingyuan Zhou

Language enables humans to share knowledge, reason about the world, and pass on strategies for survival and innovation across generations. At the heart of this process is not just the ability to communicate but also the remarkable…

Computation and Language · Computer Science 2026-02-25 Jan Philip Wahle

The availability of large idea repositories (e.g., the U.S. patent database) could significantly accelerate innovation and discovery by providing people with inspiration from solutions to analogous problems. However, finding useful…

Computation and Language · Computer Science 2017-06-20 Tom Hope , Joel Chan , Aniket Kittur , Dafna Shahaf

Reasoning, the ability to logically draw conclusions from existing knowledge, is a hallmark of human. Together with perception, they constitute the two major themes of artificial intelligence. While deep learning has pushed the limit of…

Artificial Intelligence · Computer Science 2024-10-18 Zhaocheng Zhu

Probabilistic graphical models combine the graph theory and probability theory to give a multivariate statistical modeling. They provide a unified description of uncertainty using probability and complexity using the graphical model.…

Machine Learning · Statistics 2011-11-30 Yang Zhou