Using FCA for Visual Browsing
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The document proposes using concept lattices and information visualization techniques to navigate large databases. It discusses (1) challenges of scalability in data storage and visualization, (2) relevant state-of-the-art in information visualization and formal concept analysis (FCA), and (3) a visual browsing method using FCA and spatialization algorithms to provide overviews and local views of concept lattices representing document collections. The method aims to extract structure from indexed documents and assist navigation through emphasized concept relationships and semantic document maps.
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Efficient Navigation in Temporal, Multi-Dimensional Point Sets (April 2013)
1. The document discusses algorithms and techniques for efficient navigation of temporal, multi-dimensional point set data.
2. A goal is to develop visualization algorithms that support user navigation through time-series data, including real-time rendering, user-centered browsing, and navigation via visual summaries.
3. The research will focus on scalable rendering and visualization of time-dependent point sets, efficient browsing of time-dependent datasets, and navigation using visual summaries to guide users through important events.
Improving the Accuracy of Object Based Supervised Image Classification using ...
A lot of research has been undertaken and is being carried out for developing an accurate classifier for extraction of objects with varying success rates. Most of the commonly used advanced classifiers are based on neural network or support vector machines, which uses radial basis functions, for defining the boundaries of the classes. The drawback of such classifiers is that the boundaries of the classes as taken according to radial basis function which are spherical while the same is not true for majority of the real data. The boundaries of the classes vary in shape, thus leading to poor accuracy. This paper deals with use of new basis functions, called cloud basis functions (CBFs) neural network which uses a different feature weighting, derived to emphasize features relevant to class discrimination, for improving classification accuracy. Multi layer feed forward and radial basis functions (RBFs) neural network are also implemented for accuracy comparison sake. It is found that the CBFs NN has demonstrated superior performance compared to other activation functions and it gives approximately 3% more accuracy.
SYNOPSIS on Parse representation and Linear SVM.
1. The document discusses a thesis on using sparse feature parameterization and multi-kernel SVM for large scale scene classification. The objective is to improve accuracy for large datasets using sparse representations and machine learning algorithms.
2. Key challenges include high dimensionality reducing accuracy for large datasets, nonlinear distributions, and computational costs of deep learning models. The research aims to address these issues.
3. The motivation from literature shows that multi-kernel SVMs have proved effective but could be improved by minimizing redundancy and optimizing kernel parameters for feature sets.
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This document provides an overview and roadmap for a presentation on evaluating data quality and identifying orbits from scatterometer data products using modern computing techniques. The presentation covers an introduction to scatterometers and data products, the problem of relating level-0 and level-1B data and performing retrospective analysis without metadata, a literature survey of existing data quality evaluation (DQE) systems and their limitations, a proposal for new approaches including fuzzy logic-based and pattern-based orbit identification and a neural network approach to DQE using flag bits, and the implementation and results of these new approaches. The approaches demonstrated improvements in clarity, speed and accuracy for DQE and orbit identification tasks over traditional techniques.
A simplified and novel technique to retrieve color images from hand-drawn sk...
This document presents a novel technique for retrieving color images from hand-drawn sketches. The proposed method uses K-means clustering and bag-of-attributes approaches to extract key information from sketches. It introduces a unique indexing scheme to make the retrieval process faster and more accurate. The study implemented the technique in MATLAB and found it offered better accuracy and faster processing times than existing feature extraction methods.
Visualisation for ontology sense-making: A tree-map based algorithmic approach
Ontology sense-making or visual comprehension of the ontological schemata and structure are vital for cross-validation purposes of the ontology increment during the process of applied ontology construction. Also, it is important to query the ontology in order to verify the accuracy of the stored knowledge embeddings. This will boost the interactions between domain specialists and ontologists in applied ontology construction processes. Hence existing mechanisms have numerous of deficiencies (discussed in the paper), a new algorithm is proposed in this research to boost the efficiency of usage of tree-maps for effective ontology sense making. Proposed algorithm and prototype are quantitatively and qualitatively assessed for their accuracy and efficacy.
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This document discusses different approaches for outlier detection in data mining. It begins by defining outliers and describing the importance of outlier detection. It then reviews previous work on outlier detection, which includes statistical, distance-based, deviation-based, and density-based approaches for classic outlier detection, as well as space-based and graph-based approaches for spatial outlier detection. The document goes on to describe classic and spatial outlier detection approaches in more detail. It concludes by discussing some recent advancements in outlier detection techniques like SLOF and non-parametric composite outlier detection.
Integrating GIS utility data in the UK
The VISTA project aimed to integrate utility data from various UK organizations to improve coordination and reduce costs of street works. It developed methods for syntactically and semantically integrating heterogeneous utility data through a common data model and global thesaurus. Visualization techniques were also explored that incorporated uncertainty and were driven by an ontology. While the project proved the concept, further work is needed to develop the ontology and address implementation challenges regarding data currency, security, and impact on organizational systems.
using a semantic approach for a cataloguing service
1) The document presents a semantic approach for improving an environmental data cataloguing service called MDweb by leveraging thematic and spatial reference bases.
2) It aims to address issues with existing cataloguing tools not exploiting thesauri or the interaction between thematic and spatial aspects. The approach develops mechanisms for query expansion, filtering, and semantic visualization of results.
3) Future work includes transitioning from a thesaurus to an ontology, developing user profiles, and enabling searches directly from the semantic network visualization.
Recognition and Detection of Real-Time Objects Using Unified Network of Faste...
Region based proposals regularly depend on the features which are economical prudent derivation schemes. The proposed network includesa Region Proposal Network (RPN) which accepts a picture of any size as input and yields an arrangement of rectangular object recommendations, which includes an objectness score. The RPN is prepared end-to-end to produce great quality object recommendations, which are then utilized by Faster R-CNN for object recognition. Further the trained RPN is additionally converged with Faster R-CNN into a solitary system by sharing their convolutional highlights utilizing the as of late famous wording of neural systems with "attention" techniques and the RPN segment advises the brought together system where to look for the object in input. This strategy empowers a unified, profound learning region based proposals for object detection system. The scholarly RPN additionally enhances area proposition quality and accordingly increases the accuracy in object recognition.
Project proposal geospatialweb'asedcis
This document presents a project proposal for developing a geospatial web-based community information system (CIS) to facilitate efficient social service delivery in lower local governments of Uganda. The proposal includes an introduction, literature review, related work, methodology and conclusion. The objectives are to construct a CIS spatial database, develop a user-friendly website, and integrate geospatial technologies. The methodology discusses requirements analysis, system design, implementation, testing, packaging and documentation. The conclusion is that a geospatial CIS will contribute to CIS aims by increasing availability of user-friendly community information.
Vivarana literature survey
The document provides a literature survey on data visualization and complex event processing rule generation. It discusses various multidimensional data visualization techniques such as scatter plots, parallel coordinates, radial visualization, mosaic plots, self-organizing maps and sunburst visualization. It also discusses techniques for complex event processing (CEP) rule generation including the iCEP framework and tuning rule parameters using a prediction-correction paradigm. The document contains various figures to illustrate the different visualization techniques and includes references at the end.
IRJET - Object Detection using Hausdorff Distance
This document proposes using Hausdorff distance for object detection as it can better handle noise compared to other methods like Euclidean distance. The document discusses preprocessing images using Gaussian filtering for noise cancellation. It then represents shapes as point sets for feature extraction before using Hausdorff distance to match shapes between reference and test images for object recognition. Encouraging results were obtained when testing on MNIST, COIL and private handwritten digit datasets.
Mixed Methods Analysis: Navigating Tomorrow's Web
This document summarizes a study that used mixed methods to evaluate the visual exploration tool VisGets. 763 participants explored the tool through unmoderated remote using, generating both quantitative interaction data and qualitative feedback. The study aimed to understand the benefits, challenges, and performance of visual exploration systems. Results found potential benefits like supporting multiple search dimensions and comparative information seeking, but also challenges like learning curves and empty results. Performance analysis found the system could be slow. The mixed methods approach provided a multi-faceted view of users' needs, system performance, and explained unexpected findings. Limitations included a limited population and potential variations in participation. Overall, the study provided initial insights into visual search and directions for future research.
Designing Guidelines for Visual Analytics System to Augment Organizational An...
This document presents a two-stage framework for designing visual analytics systems for organizational environments.
The first stage involves observing the domain to characterize it and generalize the analytical workflows. This informs the design artifacts and specifications.
The second stage refines the system based on formative user evaluations. Usage patterns are analyzed to customize the visualization and update the data model. The goal is to augment organizational analysis while modeling individual user reasoning.
The framework bridges high-level concepts with specific implementations. It also considers evaluation metrics to assess knowledge gain from using visual analytics in organizational settings.
IRJET- Object Detection using Hausdorff Distance
This document proposes a new object recognition system using Hausdorff distance. The system aims to improve on existing methods like YOLO that struggle with small objects and can capture garbage data. The document outlines preprocessing steps like noise cancellation, representing shapes as point sets, and extracting features. It then describes using Hausdorff distance and shape context to find the best match between input and reference shapes. Testing on datasets showed encouraging results for recognizing handwritten digits.
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Using FCA for Visual Browsing
- 1. Using Concept Lattices for Visual Navigation Assistance in Large Databases Application to a Patent Database Jean Villerd , Sylvie Ranwez, Michel Crampes, David Carteret LGI2P – É cole des Mines d’Alès, France I-Nova Company, Villeurbanne – Lyon, France
- 7. overview : collection of formal concepts 1. Context and Problem Setting | 2. State of the Art | 3. Expected Visualization | 4. Proposal for a Visual Browsing Method | 5. Perspectives 3. Objective: Expected Visualization local view : focus on a particular concept : intent = { plasma display , display panel }
- 8. 4. Proposal for a Visual Browsing Method Boolean features numerical features document indexation vector in raw data document x = 1. Context and Problem Setting | 2. State of the Art | 3. Expected Visualization | 4. Proposal for a Visual Browsing Method | 5. Perspectives plasma_display display_panel plasma p1 = x1 p2 = x2 p0 = x0
- 9. overview : collection of clusters i.e. the concept lattice local view : one cluster’s content (i.e. one formal concept’s extent) document / document distance matrix raw data Boolean features numerical features 4. Proposal for a Visual Browsing Method 1. Context and Problem Setting | 2. State of the Art | 3. Expected Visualization | 4. Proposal for a Visual Browsing Method | 5. Perspectives document / term matrix resulting lattice selection by user
- 13. 329 patents indexed by 10 terms 0.8 average term per patent
- 14. plasma_display
- 20. 4.3 Synthesis 1. Context and Problem Setting | 2. State of the Art | 3. Expected Visualization | 4. Proposal for a Visual Browsing Method | 5. Perspectives formal concept extraction from indexed documents extract the structure emphasize current concept’s neighbours on the overview propose navigation paths through the structure display documents in a concept intent with respect to a semantic distance on their numerical features focus on a structure element content (local view) display the lattice with a semantic distance on edges overview the structure Solutions Goals
- 22. Using Concept Lattices for Visual Navigation Assistance in Large Databases Application to a Patent Database [email_address] [email_address] [email_address] [email_address] É cole des Mines d’Alès – http://www.ema.fr I-Nova Company, Villeurbanne – http://www.i-nova.fr