Construction and Application of Teaching System Based on Crowdsourcing Knowledge Graph

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1. Apparenté Pas pertinent

   Domain-specific Knowledge Graphs: A survey

   Bilal Abu-Salih · 2020 · Bases de données · Résumé IA disponible

   Résumé scientifique

   Knowledge Graphs (KGs) have made a qualitative leap and effected a real revolution in knowledge representation. This is leveraged by the underlying structure of the KG which underpins a better comprehension, reasoning and interpreting of knowledge for both human and machine. Therefore, KGs continue to be used as a main driver to tackle a plethora of real-life problems in dissimilar domains. However, there is no consensus on a plausible and definition to domain KG. Further, in conjunction with several limitations and deficiencies, various domain KG construction approaches are far from perfection. This survey is the first to provide an inclusive definition to the notion of domain KG. Also, a c…

2. Apparenté Pas pertinent

   Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databases

   Hongyu Ren, Mikhail Galkin, Michael Cochez et al. · 2023 · Bases de données · Pas encore résumé

   Résumé scientifique

   Complex logical query answering (CLQA) is a recently emerged task of graph machine learning that goes beyond simple one-hop link prediction and solves a far more complex task of multi-hop logical reasoning over massive, potentially incomplete graphs in a latent space. The task received a significant traction in the community; numerous works expanded the field along theoretical and practical axes to tackle different types of complex queries and graph modalities with efficient systems. In this paper, we provide a holistic survey of CLQA with a detailed taxonomy studying the field from multiple angles, including graph types (modality, reasoning domain, background semantics), modeling aspects (e…

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   Context-based Ontology Modelling for Database: Enabling ChatGPT for Semantic Database Management

   Wenjun Lin, Paul Babyn, Yan yan et al. · 2023 · Bases de données · Résumé IA disponible

   Résumé scientifique

   This research paper explores the use of ChatGPT in database management. ChatGPT, an AI-powered chatbot, has limitations in performing tasks related to database management due to the lack of standardized vocabulary and grammar for representing database semantics. To address this limitation, the paper proposes a solution that involves developing a set of syntaxes that can represent database semantics in natural language. The syntax is used to convert database schemas into natural language formats, providing a new application of ChatGPT in database management. The proposed solution is demonstrated through a case study where ChatGPT is used to perform two tasks, semantic integration, and tables …

4. Apparenté Pas pertinent

   Online Analytical Processsing on Graph Data

   Leticia Gómez, Bart Kuijpers, Alejandro Vaisman · 2019 · Bases de données · Pas encore résumé

   Résumé scientifique

   Online Analytical Processing (OLAP) comprises tools and algorithms that allow querying multidimensional databases. It is based on the multidimensional model, where data can be seen as a cube such that each cell contains one or more measures that can be aggregated along dimensions. In a Big Data scenario, traditional data warehousing and OLAP operations are clearly not sufficient to address current data analysis requirements, for example, social network analysis. Furthermore, OLAP operations and models can expand the possibilities of graph analysis beyond the traditional graph-based computation. Nevertheless, there is not much work on the problem of taking OLAP analysis to the graph data mode…

5. Apparenté Pas pertinent

   The Relational Data Borg is Learning

   Dan Olteanu · 2020 · Bases de données · Résumé IA disponible

   Résumé scientifique

   This paper overviews an approach that addresses machine learning over relational data as a database problem. This is justified by two observations. First, the input to the learning task is commonly the result of a feature extraction query over the relational data. Second, the learning task requires the computation of group-by aggregates. This approach has been already investigated for a number of supervised and unsupervised learning tasks, including: ridge linear regression, factorisation machines, support vector machines, decision trees, principal component analysis, and k-means; and also for linear algebra over data matrices. The main message of this work is that the runtime performance of…

6. Apparenté Pas pertinent

   LLM-Powered Proactive Data Systems

   Sepanta Zeighami, Yiming Lin, Shreya Shankar et al. · 2025 · IEEE Data Engineering Bulletin March 2025 · Résumé IA disponible

   Résumé scientifique

   With the power of LLMs, we now have the ability to query data that was previously impossible to query, including text, images, and video. However, despite this enormous potential, most present-day data systems that leverage LLMs are reactive, reflecting our community's desire to map LLMs to known abstractions. Most data systems treat LLMs as an opaque black box that operates on user inputs and data as is, optimizing them much like any other approximate, expensive UDFs, in conjunction with other relational operators. Such data systems do as they are told, but fail to understand and leverage what the LLM is being asked to do (i.e. the underlying operations, which may be error-prone), the data …

7. Apparenté Pas pertinent

   Jekyll RDF: Template-Based Linked Data Publication with Minimized Effort and Maximum Scalability

   Natanael Arndt, Sebastian Zänker, Gezim Sejdiu et al. · 2021 · Web Engineering. ICWE 2019. Lecture Notes in Computer Science, vol 11496. Springer, Cham · Pas encore résumé

   Résumé scientifique

   Over the last decades the Web has evolved from a human-human communication network to a network of complex human-machine interactions. An increasing amount of data is available as Linked Data which allows machines to "understand" the data, but RDF is not meant to be understood by humans. With Jekyll RDF we present a method to close the gap between structured data and human accessible exploration interfaces by publishing RDF datasets as customizable static HTML sites. It consists of an RDF resource mapping system to serve the resources under their respective IRI, a template mapping based on schema classes, and a markup language to define templates to render customized resource pages. Using th…

8. Apparenté Pas pertinent

   DB-GPT: Empowering Database Interactions with Private Large Language Models

   Siqiao Xue, Caigao Jiang, Wenhui Shi et al. · 2023 · Bases de données · Résumé IA disponible

   Résumé scientifique

   The recent breakthroughs in large language models (LLMs) are positioned to transition many areas of software. Database technologies particularly have an important entanglement with LLMs as efficient and intuitive database interactions are paramount. In this paper, we present DB-GPT, a revolutionary and production-ready project that integrates LLMs with traditional database systems to enhance user experience and accessibility. DB-GPT is designed to understand natural language queries, provide context-aware responses, and generate complex SQL queries with high accuracy, making it an indispensable tool for users ranging from novice to expert. The core innovation in DB-GPT lies in its private LL…