Abstract:
A semantic web constructor system (100) supported by a plurality of web crawlers (112) in a World Wide Web upon declaring a plurality of trustworthy websites is provided, characterized in that, the system (100) includes at least one web crawler controller (110) engagable to manage the plurality of web crawlers (112), a semantic web database (116) connectable to the plurality of web crawlers (112) and a plurality of data building editors (122, 124, 126) connectable to the at least one web crawler controller (110) wherein a semantic browser (120) is further connectable to the semantic web database (116) to receive at least one natural language query from at least one user.
Abstract:
The present invention relates to a system and method for semantic level sentiment analysis. The system (100) comprises of a graph generator component (10), a semantic sentiment analyser component (20), a sentiment processor component (30), a sentiment dictionary (40), a sentiment taxonomy (50), a semantic sentiment patterns repository (60) and a propagation rules repository (70). The system (100) accepts text data as input and analyses sentiment in the text. The method enables semantically valid sentiment in terms of the entire text as well as the individual entities in the text. The most illustrative drawing:
Abstract:
A SYSTEM (100) FOR DISTRIBUTED QUERYING OF LINKED SEMANTIC WEBS (110) COMPRISING AT LEAST ONE LOD ONTOLOGIES INDEX (120) COMPRISING LOD ONTOLOGIES AND METADATA RELATING TO SAID LOD ONTOLOGIES; AT LEAST ONE CONCEPT INDEX (130) COMPRISING CONCEPTS AND CORRESPONDING URIs; AT LEAST ONE RELATION INDEX (140) COMPRISING RELATIONS AND CORRESPONDING URIs; QUERY INTERFACE (160) FOR ENTERING SPARQL QUERIES; AND A DISTRIBUTED QUERY ENGINE (150) IN COMMUNICATION WITH SAID LOD ONTOLOGIES INDEX (120), CONCEPT INDEX (130) AND RELATIONS INDEX (140) AND ADAPTED TO RECEIVE QUERIES FROM SAID QUERY INTERFACE (160); CHARACTERISED IN THAT SAID DISTRIBUTED QUERY ENGINE (150) IS ADAPTED TO: PARSE AND REWRITE QUERIES RECEIVED FROM SAID QUERY INTERFACE (160) AND GENERATE A PLURALITY OF SUB-QUERIES; IDENTIFY DEPENDENCIES WITHIN SAID SUB-QUERIES AND CHUNK SUB-QUERIES BASED ON ONTOLOGY; EXECUTE SUB-QUERIES BY SENDING TO RELEVANT SOURCE ONTOLOGY; AND MERGE RESULTS OBTAINED FROM EXECUTION OF SAID SUB-QUERIES. THE MOST ILLUSTRATIVE DRAWING IS
Abstract:
The present invention relates to a method for reasoning knowledge that is distributed across a plurality of linked knowledge bases. It handles queries in two ways. First, it handles a query by determining whether or not a fact is true. Secondly, it handles a query by returning query results that are not directly explicit within the triples of the queries knowledge bases which are the subjects, predicates and objects. The most illustrative drawing: FIG. 1
Abstract:
A method (100) of generating knowledge cubes from multiple heterogeneous data sources comprises the steps of analyzing all the data sources to identify potential data cubes and parameters (S202), defining (S208) cubes through the use of natural language description (S201) to obtain query results (S503) using the identified data cubes and parameters (S202), aggregating (S510) the query results upon normalization of the query results with parameters, and populating (S508) the data cubes from the heterogeneous data sources by aggregating (S510) and harmonizing the measurements of the data source. The populated cube is stored (S509) in the harmonized results database (608) for sharing and reusability.
Abstract:
[0064] There is disclosed a system for assessing risk and identify at least one individual carrying out suspicious activities based on each posting over a network; comprising: creating a context knowledge base (15) based on each posting, said knowledge base (15) can contain concepts associated to suspicious activities (110); gathering information based on the concepts from the knowledge base (15) and providing filtered data; and performing semantic profiling. In one embodiment, the method further includes performing risk assessment on the filtered data using risk assessment based on knowledge base rule (500) and based on network analysis (600) Each risk assessment process generates a watch list; to which the lists are consolidated and then the ranking the individual of interest based on the individual presence on both lists (150) is provided; and finally generating a final watch list containing details of the individuals with highest ranking (150A). The finalised list is used accordingly identify the precarious or risky individual carrying out the suspicious activities.
Abstract:
A method (100) and a system (200) for an extendable semantic query interpretation, the system (200) comprises an intelligent word sense (202), a semantic query interpreter (206), a query transformer (208), a query enricher (210) and a natural language generator (218). The intelligent word sense (202) comprises means for receiving a structured natural language user query (102). The semantic query interpreter (206) comprises means for interpreting the structured natural language user query (104). The query transformer (208) comprises means for generating from the structured natural language user query, an internal query representation statement (106). The query enricher (210) comprises means for performing query enrichment (108) to generate at least one enriched internal query representation statement, generating from the at least one enriched internal query representation statement, a knowledge base compliant query (110) to provide for searching at least one query result from an ontology knowledge base (220) and generating at least one internal query result representation statement (112). The natural language generator (218) comprises means for converting the at least one internal query result representation statement to a structures natural language result (114). The most illustrative drawing: FIGs. 1 & 2
Abstract:
A system (100) for distributed querying of linked semantic webs (110) comprising at least one LOD ontologies index (120) comprising LOD ontologies and metadata relating to said LOD ontologies; at least one concept index (130) comprising concepts and corresponding URIs; at least one relation index (140) comprising relations and corresponding URIs; query interface (160) for entering SPARQL queries; and a distributed query engine (150) in communication with said LOD ontologies index (120), concept index (130) and relations index (140) and adapted to receive queries from said query interface (160); characterised in that said distributed query engine (150) is adapted to: parse and rewrite queries received from said query interface (160) and generate a plurality of sub-queries; identify dependencies within said sub-queries and chunk sub-queries based on ontology; execute sub-queries by sending to relevant source ontology; and merge results obtained from execution of said sub-queries.
Abstract:
A method (100) and an apparatus for user assisted deductive reasoning using a plurality of semantic network refinement iterations (102) comprises performing a user assisted query (104) to ascertain at least one valid node from a plurality of nodes of a semantic network, reducing a solution space of the semantic network (106) by disregarding at least one invalid node from the plurality of nodes of the semantic network and pruning the semantic network (108) based on the at least one valid node from the plurality of nodes of the semantic network. Pruning the semantic network (108) further comprises querying a knowledge base (200) to ascertain a plurality of hypothesis and a corresponding plurality of antecedents for the at least one valid node and constructing a refined semantic network (214) based on the plurality of hypothesis and the corresponding plurality of antecedents for the at least one valid node.