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Exploring Scale-Measures of data Sets 16th

Exploring Scale-Measures of Data Sets

引用

16th International Conference on Formal Concept Analysis, ICFCA 2021

作者： Hanika, Tom Hirth, Johannes Knowledge and Data Engineering Group University of Kassel Kassel Germany Interdisciplinary Research Center for Information System Design University of Kassel Kassel Germany

ISBN: (纸本)9783030778668

Measurement is a fundamental building block of numerous scientific models and their creation in data driven science. Due to the high complexity and size of modern data sets, it is necessary to develop understandable and efficient scaling methods. A profound theory for scaling data is scale-measures from formal concept analysis. Recent developments indicate that the set of all scale-measures for a given data set constitutes a lattice. In this work we study the properties of said lattice and propose a novel and efficient scale-measure exploration algorithm, motivating multiple applications for (semi-)automatic scaling. © 2021, Springer Nature Switzerland AG.

关键词： Formal concept analysis

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Intelligent Assistant for Multivariant Analysis 26

Intelligent Assistant for Multivariant Analysis

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26th International Conference of the Catalan Association for Artificial Intelligence, CCIA 2024

作者： Angerri, Xavier Delgado, Oscar Gibert, Karina Knowledge Engineering and Machine Learning Group Intelligent Data Science and Artificial Intelligence Research Center Universtitat Politècnica de Catalunya Spain

ISBN: (纸本)9781643685434

When a knowledge Discovery from data (KDD) (Fayyad, Piatetsky-Shapiro, & Smyth, 1996) process is being applied to get knowledge, several methods could be used (Gibert, et al., 2018). A simple and fast way to obtain preliminary insights from data before using KDD models is by generating a basic descriptive analysis. It is one of the most popular ways to describe experimental data and should be the beginning of all data projects. Nevertheless some of the main knowledge that can be extracted in a descriptive analysis is hidden due to underlying multivariate structures which could be elicited through multivariate analysis techniques. Moreover, the domain expert is key for a proper interpretation of descriptive results. At the same time, there is a lack of automatic reporting techniques that can report and help in the interpretation of complex patterns and the use of advanced multivariate techniques. This paper shows the tool developed to generate automatic interpretation of Multiple Correspondence Analysis (MCA) and Principal Components Analysis (PCA) by using RMarkdown. This tool generates a Word document which contains the automatic interpretation of the results, built on the basis of regular expressions ellaborating over the R analytical outputs (either numerical or graphical results). The proposal is being applied with some real data, like INSESS database on social vulnerabilities of the Catalan population. In conclusion, the developed tool contributes to facilitate the factorial methods results, avoiding the misinterpretation of the results and the involuntary skipping of conclusions due to the large amount of knowledge that can be extracted from a complete factorial analysis. Also, this software enables non-expert users to read multivariate analysis results in a friendly way. Moreover, this tool saves time in the interpretation step and is a basis to support the expert to start the report with the results, even the output of the software could become the report or

关键词： automatic interpretation Automatic reporting explainability

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Boolean Substructures in Formal Concept Analysis 16th

Boolean Substructures in Formal Concept Analysis

引用

16th International Conference on Formal Concept Analysis, ICFCA 2021

作者： Koyda, Maren Stumme, Gerd Knowledge and Data Engineering Group University of Kassel Kassel Germany Interdisciplinary Research Center for Information System Design University of Kassel Kassel Germany

ISBN: (纸本)9783030778668

It is known that a (concept) lattice contains an n-dimensional Boolean suborder if and only if the context contains an n-dimensional contra-nominal scale as subcontext. In this work, we investigate more closely the interplay between the Boolean subcontexts of a given finite context and the Boolean suborders of its concept lattice. To this end, we define mappings from the set of subcontexts of a context to the set of suborders of its concept lattice and vice versa and study their structural properties. In addition, we introduce closed-subcontexts as an extension of closed relations to investigate the set of all sublattices of a given lattice. © 2021, Springer Nature Switzerland AG.

关键词： Formal concept analysis

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Force-Directed Layout of Order Diagrams Using Dimensional Reduction 16th

Force-Directed Layout of Order Diagrams Using Dimensional Re...

引用

16th International Conference on Formal Concept Analysis, ICFCA 2021

作者： Dürrschnabel, Dominik Stumme, Gerd Knowledge and Data Engineering Group University of Kassel Kassel Germany Interdisciplinary Research Center for Information System Design University of Kassel Kassel Germany

ISBN: (纸本)9783030778668

Order diagrams allow human analysts to understand and analyze structural properties of ordered data. While an expert can create easily readable order diagrams, the automatic generation of those remains a hard task. In this work, we adapt force-directed approaches, which are known to generate aesthetically-pleasing drawings of graphs, to the realm of order diagrams. Our algorithm ReDraw thereby embeds the order in a high dimension and then iteratively reduces the dimension until a two-dimensional drawing is achieved. To improve aesthetics, this reduction is equipped with two force-directed steps where one step optimizes the distances of nodes and the other one the distances of lines in order to satisfy a set of a priori fixed conditions. By respecting an invariant about the vertical position of the elements in each step of our algorithm we ensure that the resulting drawings satisfy all necessary properties of order diagrams. Finally, we present the results of a user study to demonstrate that our algorithm outperforms comparable approaches on drawings of lattices with a high degree of distributivity. © 2021, Springer Nature Switzerland AG.

关键词： Iterative methods

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Triadic Exploration and Exploration with Multiple Experts 16th

Triadic Exploration and Exploration with Multiple Experts

引用

16th International Conference on Formal Concept Analysis, ICFCA 2021

作者： Felde, Maximilian Stumme, Gerd Knowledge and Data Engineering Group University of Kassel Kassel Germany Interdisciplinary Research Center for Information System Design University of Kassel Kassel Germany

ISBN: (纸本)9783030778668

Formal Concept Analysis (FCA) provides a method called attribute exploration which helps a domain expert discover structural dependencies in knowledge domains that can be represented by a formal context (a cross table of objects and attributes). Triadic Concept Analysis is an extension of FCA that incorporates the notion of conditions. Many extensions and variants of attribute exploration have been studied but only few attempts at incorporating multiple experts have been made. In this paper we present triadic exploration based on Triadic Concept Analysis to explore conditional attribute implications in a triadic domain. We then adapt this approach to formulate attribute exploration with multiple experts that have different views on a domain. © 2021, Springer Nature Switzerland AG.

关键词： Formal concept analysis

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Acute MI Detection Derived from ECG Parameters Distribution

Acute MI Detection Derived from ECG Parameters Distribution

引用

2019 Computing in Cardiology, CinC 2019

作者： Aranda, Alfonso Karel, Joël Bonizzi, Pietro Peeters, Ralf Maastricht University Department of Data Science and Knowledge Engineering Netherlands Medtronic Bakken Research Center Endepolsdomein 5 Maastricht6229GW Netherlands

ISBN: (纸本)9781728169361

Several studies in the past have evaluated the use of different ECG-based features to diagnose acute myocardial infarction (AMI). This was generally done by looking at how well a feature reflects differences between baseline (no AMI) and AMI situations. This approach tends to overlook the progress of AMI and to underestimate false positives when implemented into a continuous monitoring setting and therefore appears inadequate for it. This has hindered the adoption of those methods in the clinical practice. In this research, we present a novel set of parameters for the dynamic assessment of AMI condition. Those parameters are obtained by analyzing the changes over time in the distribution properties of ECG-based features. © 2019 Creative Commons.

关键词： Electrocardiograms

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Web-service-based crop simulation system: A case study of geo-service in crop simulation system 4

Web-service-based crop simulation system: A case study of ge...

引用

4th International Symposium on Intelligent Information Technology in Agriculture, ISIITA 2007

作者： Jian, Wang Zhiqiang, Wang Gan, Guohui Xu, Yong Ma, Guoxia National Engineering Research Center for Information Technology in Agriculture Beijing China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China Research Center on Data Technology and Knowledge Economy CAS Beijing China

Applying web service technology into the crop simulation system, the author brings forward an integrated system framework established on the basis of web service and GIS the author also accomplished the web service to simulate crop yield and developed a system under the framework successfully, which has been applied into the Yangou basin in China the practice shows that it is feasible to put the web service into the use of crop simulation, which is in favor of system integration and share of the crop models for the whole society..

关键词： Web services

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SLMP: A Scientific Literature Management Platform Based on Large Language Models 15

SLMP: A Scientific Literature Management Platform Based on L...

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15th IEEE International Conference on knowledge Graph, ICKG 2024

作者： Guo, Menghao Jiang, Jinling Wu, Fan Sun, Shanxin Zhang, Chen Li, Wenhui Sun, Zeyi Chen, Guangyong Wu, Xindong Research Center for Life Sciences Computing Zhejiang Lab Hangzhou China Research Center for Data Hub and Security Zhejiang Lab Hangzhou China Research Center for High Efficiency Computing System Zhejiang Lab Hangzhou China Hefei University of Technology Key Laboratory of Knowledge Engineering With Big Data Hefei China

ISBN: (纸本)9798331508821

This paper presents a Scientific Literature Management Platform (SLMP, demo link1 ) based on large language models (LLMs). The platform consists of four modules: literature management, literature extraction, literature retrieval, and question answering. The core techniques used to support the four modules across the platform include a fine-tuned model PaperExtractGPT and a continual pre-training model ChatPaperGPT based on ChatGLM2 using the data from scientific research literature, responsible for information extraction and communication, respectively. Due to their powerful capabilities in natural language understanding and generation, LLMs can understand complex scientific concepts based on the provided contexts, and thus generate high-quality texts and conduct in-depth information retrieval and question answering. Our platform can help researchers manage and utilize literature more effectively and efficiently for finding relevant literature, obtaining required information, and generating new knowledge. © 2024 IEEE.

关键词： Question answering

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Adaptive class association rule mining for human activity recognition 6

Adaptive class association rule mining for human activity re...

引用

6th International Workshop on Mining Ubiquitous and Social Environments, MUSE 2015

作者： Atzmueller, Martin Kibanov, Mark Hayat, Naveed Trojahn, Matthias Kroll, Dennis University of Kassel Research Center for Information System Design Knowledge and Data Engineering Group Kassel Germany Volkswagen AG Wolfsburg Germany University of Kassel Research Center for Information System Design Department for Communication Technology Kassel Germany

The analysis of human activity data is an important research area in the context of ubiquitous and social environments. Using sensor data obtained by mobile devices, e. g., utilizing accelerometer sensors contained in mobile phones, behavioral patterns and models can then be obtained. However, the utilized models are often not simple to interpret by humans in order to facilitate assessment, evaluation and validation, e. g., in computational social science or in medical contexts. In this paper, we propose a novel approach for generating interpretable rule sets for classification: We present an adaptive framework for mining class association rules using subgroup discovery, and analyze different techniques for obtaining the final classifier. The approach is investigated in the context of human activity recognition. For our evaluation, we apply real-world activity data collected using mobile phone sensors. Copyright © 2015 by the paper's authors.

关键词： Cellular telephones

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Image schemas and conceptual dependency primitives: A comparison

Image schemas and conceptual dependency primitives: A compar...

引用

2017 Joint Ontology Workshops Episode 3: The Tyrolean Autumn of Ontology, JOWO 2017

作者： Macbeth, Jamie C. Gromann, Dagmar Hedblom, Maria M. Department of Electrical and Computer Systems Engineering Fairfield University FairfieldCT06824 United States Bellaterra Spain Research Center for Knowledge and Data Free University of Bozen-Bolzano Italy

A major challenge in natural language understanding research in artificial intelligence (AI) has been and still is the grounding of symbols in a representation that allows for rich semantic interpretation, inference, and deduction. Across cognitive linguistics and other disciplines, a number of principled methods for meaning representation of natural language have been proposed that aim to emulate capacities of human cognition. However, little cross-fertilization among those methods has taken place. A joint effort of human-level meaning representation from AI research and from cognitive linguistics holds the potential of contributing new insights to this profound challenge. To this end, this paper presents a first comparison of image schemas to an AI meaning representation system called Conceptual Dependency (CD). Restricting our study to the domain of physical and spatial conceptual primitives, we find connections and mappings from a set of action primitives in CD to a remarkably similar set of image schemas. We also discuss important implications of this connection, from formalizing image schemas to improving meaning representation systems in AI. © 2017 CEUR-WS. All rights reserved.

关键词： Image enhancement

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