Related papers: From webtables to datatables
Most of the world's data is stored in relational databases. Accessing these requires specialized knowledge of the Structured Query Language (SQL), putting them out of the reach of many people. A recent research thread in Natural Language…
Reasoning is an essential skill to enable Large Language Models (LLMs) to interact with the world. As tasks become more complex, they demand increasingly sophisticated and diverse reasoning capabilities for sequential decision-making,…
This paper introduces NLDS-QL, a translator of data science questions expressed in natural language (NL) into data science queries on graph databases. Our translator is based on a simplified NL described by a grammar that specifies…
Documents are core carriers of information and knowl-edge, with broad applications in finance, healthcare, and scientific research. Tables, as the main medium for structured data, encapsulate key information and are among the most critical…
With the proliferation of machine learning (ML) libraries and frameworks, and the programming languages that they use, along with operations of data loading, transformation, preparation and mining, ML model development is becoming a…
A foundation is investigated for the application of loosely structured data on the Web. This area is often referred to as Linked Data, due to the use of URIs in data to establish links. This work focuses on emerging W3C standards which…
A data graph is a convenient paradigm for supporting keyword search that takes into account available semantic structure and not just textual relevance. However, the problem of constructing data graphs that facilitate both efficiency and…
Spreadsheet tools are widely accessible to and commonly used by K-12 students and teachers. They have an important role in data collection and organization. Beyond data organization, spreadsheets also make data visible and easy to interact…
The large size and fast growth of data repositories, such as data lakes, has spurred the need for data discovery to help analysts find related data. The problem has become challenging as (i) a user typically does not know what datasets…
Table-to-text generation aims at automatically generating natural text to help people to conveniently obtain the important information in tables. Although neural models for table-to-text have achieved remarkable progress, some problems…
Although researchers have devoted considerable attention to helping database users formulate queries, many users still find it challenging to specify queries that involve joining tables. To help users construct join queries for exploring…
The data warehousing is becoming increasingly important in terms of strategic decision making through their capacity to integrate heterogeneous data from multiple information sources in a common storage space, for querying and analysis. So…
Enterprise level data is often distributed across multiple sources and identifying the correct set-of data-sources with relevant information for a knowledge request is a fundamental challenge. In this work, we define the novel task of…
The game Starcraft is one of the most interesting arenas to test new machine learning and computational intelligence techniques; however, StarCraft matches take a long time and creating a good dataset for training can be hard. Besides,…
Contemporary approaches to data management are increasingly relying on unified analytics and AI platforms to foster collaboration, interoperability, seamless access to reliable data, and high performance. Data Lakes featuring open standard…
Machine Learning Operations (MLOps) is becoming a highly crucial part of businesses looking to capitalize on the benefits of AI and ML models. This research presents a detailed review of MLOps, its benefits, difficulties, evolutions, and…
The Web of Linked Data is composed of tons of RDF documents interlinked to each other forming a huge repository of distributed semantic data. Effectively querying this distributed data source is an important open problem in the Semantic Web…
When spreadsheets are filled freely by knowledge workers, they can contain rather unstructured content. For humans and especially machines it becomes difficult to interpret such data properly. Therefore, spreadsheets are often converted to…
Question Answering over Tabular Data (Table QA) presents unique challenges due to the diverse structure, size, and data types of real-world tables. The SemEval 2025 Task 8 (DataBench) introduced a benchmark composed of large-scale,…
Since the use of computers in the business world, data collection has become one of the most important issues due to the available knowledge in the data; such data has been stored in the database. The database system was developed which led…