Related papers: A user-friendly SPARQL query editor powered by lig…
The continuous development of Question Answering (QA) datasets has drawn the research community's attention toward multi-domain models. A popular approach is to use multi-dataset models, which are models trained on multiple datasets to…
An increasing amount of information is generated from the rapidly increasing number of sensor networks and smart devices. A wide variety of sources generate and publish information in different formats, thus highlighting interoperability as…
The importance of geo-spatial data in critical applications such as emergency response, transportation, agriculture etc., has prompted the adoption of recent GeoSPARQL standard in many RDF processing engines. In addition to large…
NoSQL databases support semi-structured data, typically modeled as JSON. They also provide limited (but expanding) query languages. Their idiomatic, non-SQL language constructs, the many variations, and the lack of formal semantics inhibit…
This paper describes the design and implementation of CRAQL (Composable Repository Analysis and Query Language), a new query language for source code. The growth of source code mining and its applications suggest the need for a query…
Deep Web databases contain more than 90% of pertinent information of the Web. Despite their importance, users don't profit of this treasury. Many deep web services are offering competitive services in term of prices, quality of service, and…
We envision a publish/subscribe ontology system that is able to index millions of user subscriptions and filter them against ontology data that arrive in a streaming fashion. In this work, we propose a SPARQL extension appropriate for a…
Explaining the decisions of AI has become vital for fostering appropriate user trust in these systems. This paper investigates explanations for a structured prediction task called ``text-to-SQL Semantic Parsing'', which translates a natural…
The current state-of-the-art generative models for open-domain question answering (ODQA) have focused on generating direct answers from unstructured textual information. However, a large amount of world's knowledge is stored in structured…
RDF has become very popular for semantic data publishing due to its flexible and universal graph-like data model. Yet, the ever-increasing size of RDF data collections makes it more and more infeasible to store and process them on a single…
Accurate question answering over real spreadsheets remains difficult due to multirow headers, merged cells, and unit annotations that disrupt naive chunking, while rigid SQL views fail on files lacking consistent schemas. We present SQuARE,…
Enterprises rely on RDF knowledge graphs and SPARQL to expose operational data through natural language interfaces, yet public KGQA benchmarks do not reflect proprietary schemas, prefixes, or query distributions. We present PIPE-RDF, a…
Though recent advances in machine learning have led to significant improvements in natural language interfaces for databases, the accuracy and reliability of these systems remain limited, especially in high-stakes domains. This paper…
In modern enterprises, Business Processes (BPs) are realized over a mix of workflows, IT systems, Web services and direct collaborations of people. Accordingly, process data (i.e., BP execution data such as logs containing events,…
Neural Machine Translation (NMT) models from English to SPARQL are a promising development for SPARQL query generation. However, current architectures are unable to integrate the knowledge base (KB) schema and handle questions on knowledge…
Text-to-SQL converts natural language questions into executable SQL queries, enabling non-technical users to access relational databases for analytics and intelligent data services. In real-world scenarios, performance is often constrained…
Efficient usage of the knowledge provided by the Linked Data community is often hindered by the need for domain experts to formulate the right SPARQL queries to answer questions. For new questions they have to decide which datasets are…
LLMs have advanced text-to-SQL generation, yet monolithic architectures struggle with complex reasoning and schema diversity. We propose AGENTIQL, an agent-inspired multi-expert framework that combines a reasoning agent for question…
The ranked retrieval model has rapidly become the de-facto way for search query processing in web databases. Despite the extensive efforts on designing better ranking mechanisms, in practice, many such databases fail to address the diverse…
Edge computing emerges as an innovative platform for services requiring low latency decision making. Its success partly depends on the existence of efficient data management systems. We consider that knowledge graph management systems have…