Abstract: A method for text mining from one or more tables is provided. The method includes the steps of: receiving one or more tables, the tables having one or more table labels, and one or more cells to be processed, transforming each of the cells into cell vector representations; encoding the one or more cell vector representations with a sequential 2D model; obtaining one or more table-level vector representations by summarising the semantics of the cell vector representations by an image classification model; and mapping the output of to an output vector which represents the probability of each of the table labels.

Abstract: A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest selected from an. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more general concept. Similarity measures between profiles may then be calculated based on suitable distance formulas within this space.

Abstract: A knowledge-based system and methods to matchmaking and social network extension are disclosed. The system is configured to allow users to specify knowledge profiles, which are collections of concepts that indicate a certain topic or area of interest selected from an. The system utilizes the knowledge model as the semantic space within which to compare similarities in user interests. The knowledge model is hierarchical so that indications of interest in specific concepts automatically imply interest in more general concept. Similarity measures between profiles may then be calculated based on suitable distance formulas within this space.