Abstract: Much valuable information in documents is presented within tables. However, the information within tables is hard to extract automatically with high accuracy due to the wide variety and low quality of typical tables found in electronic documents. Information extraction technology can provide a method of extracting information from heterogeneous tables by recognizing tables, the header cells, and cells that are merged or should be merged, creating a richer representation of table structure and providing a convenient way of linking cells to their row and column headers. Use of this richer representation allows a few extraction patterns to successfully pull out information from a wide variety of differently formatted tables.

Abstract: The system and methods described herein provide results previewing for an interactive text mining system in order to feedback partial query results to users before all results that are responsive to a query have been found. These partial results allow the user to see the progress of their text mining query much sooner.

Abstract: A system for indexing unstructured or semi-structured data is disclosed. The system may identify regions within the data, such as “Abstract” or “References”. The system may identify linguistic units such as sentences, noun groups, verb groups. The system may also identify concepts such as companies, people, diseases, amounts, and so forth. The query results may be formatted so that similar results from different documents, or from the same document, are clustered together.