Abstract: A computer system and computer implemented method for extracting data set from data clusters that comprises of rows and columns of heterogeneous data values. A plurality of random data groups comprising of at least one of a plurality of contiguous row or columns of data values are selected. Each data value has a data type. A table template type is identified based on detection of a pattern between the data cells of the contiguous rows or columns. A table template header is identified that comprises of a starting position, and ending position and a width. A reference row or reference column indicating a start of a table body is determined. The data cells of the subsequent rows or columns in the table body are compared to the data cells of the reference rows to identify noise rows or columns that are removed from the table body.

Abstract: A computer system and computer implemented method for extracting data set from data clusters that comprises of rows and columns of heterogeneous data values. A plurality of random data groups comprising of at least one of a plurality of contiguous row or columns of data values are selected. Each data value has a data type. A table template type is identified based on detection of a pattern between the data cells of the contiguous rows or columns. A table template header is identified that comprises of a starting position, and ending position and a width. A reference row or reference column indicating a start of a table body is determined. The data cells of the subsequent rows or columns in the table body are compared to the data cells of the reference rows to identify noise rows or columns that are removed from the table body.

Abstract: Various embodiments may operate to access individual lines of information included in a file stored in an electronic storage medium, to detect the existence of data clusters in the file based on neighboring cell content in a horizontal direction (corresponding to the individual lines), and in a vertical direction (orthogonal to the horizontal direction), to identify at least some of the data clusters as being associated with predefined table types (comprising vertical tables, horizontal tables, or cross tables), to merge some of the data clusters into section tables having common properties, and to transform the tables resulting from the merging activity, as well as remaining un-merged data clusters, into a single flat table. The stored file may comprise a spreadsheet file.

Abstract: Various embodiments may operate to access individual lines of information included in a file stored in an electronic storage medium, to detect the existence of data clusters in the file based on neighboring cell content in a horizontal direction (corresponding to the individual lines), and in a vertical direction (orthogonal to the horizontal direction), to identify at least some of the data clusters as being associated with predefined table types (comprising vertical tables, horizontal tables, or cross tables), to merge some of the data clusters into section tables having common properties, and to transform the tables resulting from the merging activity, as well as remaining un-merged data clusters, into a single flat table. The stored file may comprise a spreadsheet file.

Abstract: Various embodiments may operate to access individual lines of information included in a file stored in an electronic storage medium, to detect the existence of data clusters in the file based on neighboring cell content in a horizontal direction (corresponding to the individual lines), and in a vertical direction (orthogonal to the horizontal direction), to identify at least some of the data clusters as being associated with predefined table types (comprising vertical tables, horizontal tables, or cross tables), to merge some of the data clusters into section tables having common properties, and to transform the tables resulting from the merging activity, as well as remaining un-merged data clusters, into a single flat table. The stored file may comprise a spreadsheet file.

Abstract: Apparatus, systems, and methods may operate to access individual lines of information included in a file stored in an electronic storage medium, to detect the existence of data clusters in the file based on neighboring cell content in a horizontal direction (corresponding to the individual lines), and in a vertical direction (orthogonal to the horizontal direction), to identify at least some of the data clusters as being associated with predefined table types (comprising vertical tables, horizontal tables, or cross tables), to merge some of the data clusters into section tables having common properties, and to transform the tables resulting from the merging activity, as well as remaining un-merged data clusters, into a single flat table. The stored file may comprise a spreadsheet file. Additional apparatus, systems, and methods are disclosed.