Abstract:
The present invention provides a method for profiling an object based on search input. The method comprises receiving (305) the search input of the object to be profiled, the inputs include keywords; harvesting (310) data from internet through a data harvesting bot (110); rotating keywords and pages through a spiral keyword processor (120) for hopping between targeted pages/sites for avoiding anti-bot mechanisms on the targeted pages/sites; identifying (330) data relevancy based on semantic similarity of the keywords to get most relevant data from the harvested data; identifying (340) the keywords through named entity recognition, NER, processor (140) to extract most relevance data; and outputting (345) the profile of the object in a structured manner with highly relevant data. An object profiling system is also provided.
Abstract:
Data integration from various and variety of data sources is provided without changing the source of the data itself by connecting synonyms data based on predefined semantic rules and maintaining data originality. The system of the present invention comprising at least one decision support system (DSS) agent (502) comprising at least one rules based data connection engine (503) adapted to generate linked data from a plurality of data retrieved from a plurality of heterogeneous data sources; and at least one semantic based decision support system (DSS) (504) in communication with said decision support system agent and comprising a predefined set of semantic rules; and concepts and relations mapping information. Originality of the data will be maintained as none of the data source will be edited or removed, as compared to traditional algorithms based approach. The methodology of the present invention comprises steps of retrieving a plurality of data from a plurality of heterogeneous data sources (802); pre-defining set of semantic rules (804); forwarding predefined semantic rules into Rules Based Data Connection Engine to link schema-to-schema, property-to-property and schema-to property of said data sources and to map schema and data values from said data sources based on a set of predefined semantic rules (803); generating connected data from said mapped schema and data values (805); and returning relationships between schemas and values to user (806). Accuracy of intermediate and final results as obtained through the present invention is independent from the sequence of algorithms execution.
Abstract:
A system (100) and method to detect an occurrence of a natural disaster comprises of a real time visioning analytic module (110) and a sensor analyser module (120), configured to collect real time data and sensing data on the natural disaster from a target area and from areas surrounding the target area; and an information collector and analyser module (130), configured to collect data related to the natural disaster occurrence in the target area and the areas surrounding the target area from a plurality of data sources. The system (100) further comprises a deep learning analytic module (140), configured to retrieve and process the collected data for determining a natural disaster score on the occurrence of the natural disaster in the target area and the areas surrounding the target area.
Abstract:
The invention provides a method and system for providing a content list based on a search query. The method and system generally require that one or more domains associated with the search query be identified by a data classifier (104), so as to enrich the search query using domain knowledge of the identified domains. Based on the enriched query, contents may be crawled by a data collector (102) from a plurality of websites if they are found to be associated with the enriched query. Later, the crawled contents are classified into various categories based on named entities extracted from the contents. The classified contents are subjected to deduplication, in order to eliminate or remove duplicative contents, before they can be displayed to the user.
Abstract:
The system (100) and method (400) of the present invention provides a decision support system (DSS) 5 which utilizes open standards and information reuse that provides reusable solution for other open standard ontology system. The system's decision making process decouples the sub-systems in the DSS, processes, and data needed for deployment of a new decision making process, algorithms and supporting data without any modification to the system. The distinctiveness of the present invention lies in the following sub systems of the ontology model of the Decision Support System (DSS); Workflow Manager (104) for managing the workflow of a predefined solution; Data Integrator (110) for interacting with a variety of data from internal and external sources; Rule-based Inference Engine (106) for supporting automatic decision making based on pre-defined rules that interoperate with a range of rule-based reasoners in plug-and-play manner; and Algorithm Library (108) for processing customized algorithm to enable deployment of algorithms based on generic methodology defined in the Library without any modification of the ontology; algorithms are shared between heterogeneous implementers wherein each implementer is identified through a unique identification (ID) which is defined in the system; and a lookup directory is used to load and execute the algorithms in the Library.
Abstract:
An Enterprise Application Integration system (102) comprising a workflow module (106), and at least one connector (108) to one or more further modules, wherein data is mapped between different modules (14, 18, 22, 26) by reference to semantic data mapping rules defined by an ontology (110)