Table understanding methods extract, transform, and interpret the information contained in
tabular data embedded in documents/files of different formats. Such automatic …

Spreadsheets are very common for information processing to support decision making by
both professional developers and non-technical end users. Moreover, business intelligence …

The paper discusses issues of rule-based data transformation from arbitrary spreadsheet
tables to a canonical (relational) form. We present a novel table object model and rule …

In most cases, the complexity of expert systems engineering depends on the complexity of
knowledge base engineering. This process includes formalization and programming tasks …

Spreadsheets are widely used in science, engineering, business, and other activities.
Overall, they conceal a large volume of data in a form intended to be interpreted by humans …

Numbers in spreadsheets often have units: metres, grams, dollars, etc. Spreadsheet cells
typically cannot carry unit information, and even where they can, users may not be motivated …

Many software systems require diverse data gathering and handling through processes that
manipulate tabular data, often with a spreadsheet orientation. Variability in tabular data …

Spreadsheet users are often unaware of the risks imposed by poorly designed
spreadsheets. One way to assess spreadsheet quality is to detect smells which attempt to …

This paper presents an approach to rule-based spreadsheet data extraction and
transformation. We determine a table object model and domain-specific language of table …

Many data-intensive applications handle tabular data with more advanced structuring and
processes than spreadsheets, enabling end-users to copy and adapt tabular data and …