40 results about "Schema matching" patented technology

A method and system for identifying schemas of web databases is provided. A schema matching system generates a mapping between an interface schema and a result schema of a web database, which is used to represent the underlying database schema. The schema matching system also generates a mapping of the interface attributes and the result attributes of the web database to global attributes of a global schema whose semantics are known. Using these mappings, a search engine service can formulate queries using the global attributes, map those queries to the corresponding interface attributes, submit the query, and retrieve the values from the result attributes that correspond to the desired global attributes.

A system and method for matching one or more source schemas with one or more target schemas is provided. The matching between source and target schemas is performed by gathering inputs pertaining to the source and target schemas, wherein the inputs comprises a set of details in a predefined format. Thereafter, the gathered inputs are processed by comparing the source schemas with the target schemas. The processing is performed to identify a set of matches between the source and target schemas based on the linguistic similarity, structural similarity and functional similarity and relationship between the source and target schemas. Subsequently, the identified matches are stored.

A method and system for comparing two documents, such as XML (Extensible Markup Language) files, where each document is capable of being parsed into a DOM (Document Object Model) trees. Each tree structure is converted into an array of leaf paths containing nodes. These arrays are then compared to identify corresponding matched nodes—either exactly matched nodes or schema matched nodes. In reporting the results of the comparison, unmatched nodes of the source document are reported as “deleted nodes”, that is, existing in the source but not in the target. Similarly all unmatched nodes of the target document are reported as “added nodes”, that is, existing in the target but not in the source. In addition, schema matched nodes are reported as “modified nodes” between source and target documents.

A method matches elements in two schemas for two associated databases using automatic schema matching (ASM), wherein there is one schema for each database, wherein the elements define objects in the databases, and wherein the matching is performed on pairs of the elements by a combined matcher including a set of matchers. A Bayesian network (BN) is constructed for the set of matchers, and for each pair of elements the following steps are performing: obtaining an individual similarity value for each pair of the elements and each matcher, determining a likelihood ratio for each individual similarity value, performing belief updating on the BN using the likelihood ratios to obtain a final similarity value and corresponding probability, and outputting the final similarity value and the probability to indicate whether the pair of the elements match, or not.

Systems and methods for performing schema matching of multiple data dictionaries. Lexical graphs are generated for two or more data dictionaries. The lexical graphs include terms with definitions and identified links between terms. A data processing device determines if matches occur between the generated lexical graphs and outputs the result of the determination.

The invention discloses a visualization system of public opinion big data. The system comprises a data acquisition system and a display module. The data acquisition module comprises a theme setting unit, a public opinion acquisition unit, a storage unit, a target webpage generating unit and an analysis unit. The display module comprises a big data standard interface, a big data visualization engine, a visualization tool library and an intelligent knowledge library. The big data standard interface carries out standardized processing on formats of data in a data word bank output by an analysis unit, and standard big data is obtained. The big data visualization engine carries out visualization processing on the standard big data by calling the visualization tool library to obtain visualized standard big data. The intelligent knowledge library is called to carry out reading mode matching on the visualized standard big data to obtain readable data flow, and the readable data flow is subjected to GIS map presentation processing. Network public opinions can be processed, the processing result can be subjected to visualization display, and users can visually know the propagation state of the public opinions.