OnSET: Ontology and Semantic Exploration Toolkit
- URL: http://arxiv.org/abs/2504.08373v1
- Date: Fri, 11 Apr 2025 09:18:06 GMT
- Title: OnSET: Ontology and Semantic Exploration Toolkit
- Authors: Benedikt Kantz, Kevin Innerebner, Peter Waldert, Stefan Lengauer, Elisabeth Lex, Tobias Schreck,
- Abstract summary: We propose a Semantic system, Ontology and Exploration Toolkit (OnSET)<n>OnSET allows non-expert users to easily build queries with visual user guidance provided by topic modelling and semantic search.<n>OnSET combines efficient and open platforms to deploy the system on commodity hardware.
- Score: 5.1293983340834055
- License: http://creativecommons.org/licenses/by-sa/4.0/
- Abstract: Retrieval over knowledge graphs is usually performed using dedicated, complex query languages like SPARQL. We propose a novel system, Ontology and Semantic Exploration Toolkit (OnSET) that allows non-expert users to easily build queries with visual user guidance provided by topic modelling and semantic search throughout the application. OnSET allows users without any prior information about the ontology or networked knowledge to start exploring topics of interest over knowledge graphs, including the retrieval and detailed exploration of prototypical sub-graphs and their instances. Existing systems either focus on direct graph explorations or do not foster further exploration of the result set. We, however, provide a node-based editor that can extend on these missing properties of existing systems to support the search over big ontologies with sub-graph instances. Furthermore, OnSET combines efficient and open platforms to deploy the system on commodity hardware.
Related papers
- A Socratic RAG Approach to Connect Natural Language Queries on Research Topics with Knowledge Organization Systems [0.3782392304044599]
We propose a Retrieval Augmented Generation (RAG) agent that maps natural language queries about research topics to machine-interpretable semantic entities.
Our approach combines RAG with Socratic dialogue to align a user's intuitive understanding of research topics with established Knowledge Organization Systems.
arXiv Detail & Related papers (2025-02-20T19:58:59Z) - A large collection of bioinformatics question-query pairs over federated knowledge graphs: methodology and applications [0.0838491111002084]
We introduce a large collection of human-written natural language questions and their corresponding SPARQL queries over federated bioinformatics knowledge graphs.
We propose a methodology to uniformly represent the examples with minimal metadata, based on existing standards.
arXiv Detail & Related papers (2024-10-08T13:08:07Z) - The Ontoverse: Democratising Access to Knowledge Graph-based Data Through a Cartographic Interface [33.861478826378054]
We have developed a unique approach to data navigation that leans on geographical visualisation and hierarchically structured domain knowledge.
Our approach uses natural language processing techniques to extract named entities from the underlying data and normalise them against relevant semantic domain references and navigational structures.
This allows end-users to identify entities relevant to their needs and access extensive graph analytics.
arXiv Detail & Related papers (2024-07-22T10:29:25Z) - DiscoverPath: A Knowledge Refinement and Retrieval System for
Interdisciplinarity on Biomedical Research [96.10765714077208]
Traditional keyword-based search engines fall short in assisting users who may not be familiar with specific terminologies.
We present a knowledge graph-based paper search engine for biomedical research to enhance the user experience.
The system, dubbed DiscoverPath, employs Named Entity Recognition (NER) and part-of-speech (POS) tagging to extract terminologies and relationships from article abstracts to create a KG.
arXiv Detail & Related papers (2023-09-04T20:52:33Z) - PyRCA: A Library for Metric-based Root Cause Analysis [66.72542200701807]
PyRCA is an open-source machine learning library of Root Cause Analysis (RCA) for Artificial Intelligence for IT Operations (AIOps)
It provides a holistic framework to uncover the complicated metric causal dependencies and automatically locate root causes of incidents.
arXiv Detail & Related papers (2023-06-20T09:55:10Z) - GAIA Search: Hugging Face and Pyserini Interoperability for NLP Training
Data Exploration [97.68234051078997]
We discuss how Pyserini can be integrated with the Hugging Face ecosystem of open-source AI libraries and artifacts.
We include a Jupyter Notebook-based walk through the core interoperability features, available on GitHub.
We present GAIA Search - a search engine built following previously laid out principles, giving access to four popular large-scale text collections.
arXiv Detail & Related papers (2023-06-02T12:09:59Z) - Spacerini: Plug-and-play Search Engines with Pyserini and Hugging Face [104.2943594704532]
Spacerini is a tool that integrates the Pyserini toolkit for reproducible information retrieval research with Hugging Face.
Spacerini makes state-of-the-art sparse and dense retrieval models more accessible to non-IR practitioners.
arXiv Detail & Related papers (2023-02-28T12:44:10Z) - Retrieval-Enhanced Machine Learning [110.5237983180089]
We describe a generic retrieval-enhanced machine learning framework, which includes a number of existing models as special cases.
REML challenges information retrieval conventions, presenting opportunities for novel advances in core areas, including optimization.
REML research agenda lays a foundation for a new style of information access research and paves a path towards advancing machine learning and artificial intelligence.
arXiv Detail & Related papers (2022-05-02T21:42:45Z) - Graph Enhanced BERT for Query Understanding [55.90334539898102]
query understanding plays a key role in exploring users' search intents and facilitating users to locate their most desired information.
In recent years, pre-trained language models (PLMs) have advanced various natural language processing tasks.
We propose a novel graph-enhanced pre-training framework, GE-BERT, which can leverage both query content and the query graph.
arXiv Detail & Related papers (2022-04-03T16:50:30Z) - Web of Scholars: A Scholar Knowledge Graph [38.49685673193518]
Web of Scholars integrates state-of-the-art mining techniques to search, mine, and visualize complex networks behind scholars in the field of Computer Science.
Web of Scholars takes advantage of knowledge graph, which means that it will be able to access more knowledge if more search exist.
arXiv Detail & Related papers (2022-02-23T05:10:19Z) - A New Neural Search and Insights Platform for Navigating and Organizing
AI Research [56.65232007953311]
We introduce a new platform, AI Research Navigator, that combines classical keyword search with neural retrieval to discover and organize relevant literature.
We give an overview of the overall architecture of the system and of the components for document analysis, question answering, search, analytics, expert search, and recommendations.
arXiv Detail & Related papers (2020-10-30T19:12:25Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.