Search Results for "semantic"

...Traditional approaches often dump entire files into a model’s context, which quickly exceeds token limits; LLM-TLDR instead indexes project structure, traces dependencies, and summarizes code in a way that preserves semantic relevance while shrinking input size by up to 95 %. This makes queries and analysis much faster and cheaper, with dramatic token savings and latency improvements for LLM-driven development workflows. The project supports multiple programming languages and includes utilities for warming an index and then generating LLM-ready contexts or summaries of specific parts of a project.

...Visualization helps end-users understand data. Charts.css help frontend developers turn data into beautiful charts and graphs using simple CSS classes. The data is structured using semantic HTML tags and styled using CSS classes which change the visual representation displayed to the end-user. The framework offers developers flexibility. You choose what components to display and how to style them. Each component offers several CSS classes and CSS variables to customize your style. The key feature is the ability to customize everything using basic CSS. ...

...Seaborn helps you explore and understand your data. Its plotting functions operate on dataframes and arrays containing whole datasets and internally perform the necessary semantic mapping and statistical aggregation to produce informative plots. Its dataset-oriented, declarative API lets you focus on what the different elements of your plots mean, rather than on the details of how to draw them. Behind the scenes, seaborn uses matplotlib to draw its plots. For interactive work, it’s recommended to use a Jupyter/IPython interface in matplotlib mode, or else you’ll have to call matplotlib.pyplot.show() when you want to see the plot.

TextGrapher is a Python project that converts unstructured Chinese text into a structured semantic graph. It extracts high-frequency terms, keywords, named entities, and subject-verb-object phrases from an input document. The system then organizes these elements into connected nodes and relationships for visual inspection. Generated results are saved as an HTML graph that can be opened in a browser. The repository includes parsing, keyword extraction, graph construction, and visualization scripts. ...

Semantics Visualizations enable understanding complex matters in an easy way. The research group “Semantics Visualization” is working on processing, enriching, and visualizing any kind of semantic data to provide visually discoverable information. Thereby processes of knowledge acquisition, human information retrieval, and decision making are supported by a variety of interactive visual representations. The developed visualizations do not only allow to investigate the masses amount of various semantic formats on Web, e.g. ...

We present an approach to generate a 3D model of a building including semantic annotations from image series. In the recent years semantic based modeling, reconstruction of buildings and building recognition became more and more important. Semantic building models have more information than just the geometry, thus making them more suitable for recognition or simulation tasks. The time consuming generation of such models and annotations makes an automatism desirable. ...

The Prajna project is a collection of tools and utility classes combining visualization, geographic displays, data fusion, and semantic reasoning into a cohesive toolkit for enhancing information discovery and reasoning.

OntoModel is a UML-based editor that works with OWL ontologies. The usage of the UML extension mechanism makes it possible to develope and maintain OWL ontologies with MDA technologies. Implemented as NeOn Toolkit (http://www.neon-toolkit.org) plugin.

** IMPORTANT NOTICE ** 10 Feb 2006 Code is being moved to the SMI subversion repository (http://smi-protege.stanford.edu/svn/owl/trunk/) Project will continue to be open source. ProtegeOWL info at: http://protege.stanford.edu/overview/protege-owl.html