2019 results about "Data search" patented technology

The present invention relates to a method, system and server configured to enable a plurality of users to conduct a data search within a database over a data network, comprising: (a) a first software component for enabling one or more of the following: (a.1.) providing a user with a user interface, having a virtual assistant, for enabling said user to conduct a data search over a data network by means of said virtual assistant; and (a.2.) receiving data from said user interface, having said virtual assistant, and conveying corresponding data back to said user to be provided to him by means of said virtual assistant; (b) a second software component for enabling said virtual assistant to interact with said user; and (c) a third software component for: (c.1.) enabling receiving from said user at least one search query by means of said virtual assistant; (c.2.) enabling analyzing and processing said at least one search query for determining one or more data items from a plurality of data items stored and / or indexed within a search database, said one or more data items being relevant to said at least one search query, giving rise to relevant data items being the search results; and (c.3.) enabling providing at least a portion of said search results to said user by means of said virtual assistant, each search result being provided as the relevant data item or as a link to said relevant data item.

A method of automatically narrowing data search space and improving accuracy of data extraction using known constraints in a layout of extracted data elements for classified documented is provided. The method includes: analyzing each document to classify it within a document category, each category having a corresponding set of expected layouts; analyzing each electronic document to automatically extract images and text features; automatically constructing a data structure including a layout of the extracted features and layout relationships amongst the extracted features, wherein each of the extracted features in the layout maintains a reference to neighboring features and wherein closely related features are merged to form a combined feature; automatically narrowing data search space by detecting and removing parts of the layout that are not associated with any data elements using the data structure; and automatically detecting data using the extracted feature layout and the layout relationships amongst the extracted features.

An enhanced multi-point statistical (MPS) simulation is disclosed. A multiple-grid simulation approach is used which has been modified from a conventional MPS approach to decrease the size of a data search template, saving a significant amount of memory and cpu-time during the simulation. Features used to decrease the size of the data search template include: (1) using intermediary sub-grids in the multiple-grid simulation approach, and (2) selecting a data template that is preferentially constituted by previously simulated nodes. The combination of these features allows saving a significant amount of memory and cpu-time over previous MPS algorithms, yet ensures that large-scale training structures are captured and exported to the simulation exercise.

A question answering system includes a question answering unit, an analysis unit, a tree structure generation unit, a feature extraction unit, an evaluation unit and a re-ranking unit. The question answering unit executes search processing based on an input question and acquires answer candidates to the question. The analysis unit executes syntactic analysis processing or syntactic and semantic analysis processing on a passage obtained as a result of the search processing. The tree structure generation unit generates a tree structure based on an analysis result. The feature extraction unit extracts a relation between a search word applied in the search processing and each acquired answer candidate as a feature corresponding to each answer candidate from the tree structure. The evaluation unit determines an evaluation value of each answer candidate based on the feature extracted. The re-ranking unit re-ranks the answer candidates based on the evaluation values.