Abstract: A system and method for identifying hidden connections among non-sentiment phrases are presented. The method includes identifying all connections among a plurality of non-sentiment phrases based on at least one proximity rule; determining direct connections among the identified connections, wherein each direct connection meets a predetermined correlation; filtering out the determined direct connections from the identified connections to yield hidden connections among the identified connections; analyzing the hidden connections to identify a common phrase, wherein the common phrase is associated with at least two hidden connections; generating a new hidden connection among the plurality of non-sentiment phrases based on the common phrase; and associating a sentiment phrase with at least two non-sentiment phrases having a hidden connection, wherein the association is a term taxonomy.

Abstract: A method for real-time monitoring of changes in a sentiment respective of an input non-sentiment phrase. The method comprises receiving the input non-sentiment phrase and at least one tendency parameter respective of the input non-sentiment phrase; identifying in a data storage at least one of a term taxonomy that includes the input non-sentiment phrase, wherein the data storage contains a plurality of phrases including sentiment phrases, non-sentiment phrases, and a plurality of term taxonomies; computing a sentiment trend for the at least one term taxonomy; monitoring the sentiment trend to detect real-time changes in a direction of the sentiment trend with respect to the at least one tendency parameter; and generating at least a notification when a change in the direction of the sentiment trend with respect to the input tendency parameter has occurred.

Abstract: A system and method for identifying hidden connections among non-sentiment phrases are presented. The method includes identifying all connections among a plurality of non-sentiment phrases based on at least one proximity rule; determining direct connections among the identified connections, wherein each direct connection meets a predetermined correlation; filtering out the determined direct connections from the identified connections to yield hidden connections among the identified connections; analyzing the hidden connections to identify a common phrase, wherein the common phrase is associated with at least two hidden connections; generating a new hidden connection among the plurality of non-sentiment phrases based on the common phrase; and associating a sentiment phrase with at least two non-sentiment phrases having a hidden connection, wherein the association is a term taxonomy.

Abstract: A system for identifying hidden connections between non-sentiment phrases. The system comprises a network interface enabling an access to one or more data sources; a data warehouse storage for at least storing a plurality of phrases including sentiment phrases and non-sentiment phrases; an analysis unit for identifying hidden connections between non-sentiment phrases based on at least one proximity rule and for generating at least an association between at least two non-sentiment phrases having a hidden connection and a sentiment phrase, wherein an association between the at least two non-sentiment phrases having the hidden connection and the corresponding sentiment phrase is a term taxonomy.

Abstract: A method for generating a trend report for a non-sentiment phrase. The method comprises generating a plurality of term taxonomies between non-sentiment phrases and sentiment phrases; storing the plurality of term taxonomies in a database; performing periodically at least a statistical analysis respective of the plurality of term taxonomies in the database; receiving a request for a report with respect of at least a non-sentiment phrase in the database; generating a trend report based at least on the at least statistical analysis; and providing the report to the requestor of the report.

Abstract: A system for creation of term taxonomies by mining web based user generated content according. The system includes a network interface enabling access to one or more data sources; a mining unit for collecting textual content from the one or more sources and generating phrases, the generated phrases include sentiment phrases and non-sentiment phrases; an analysis unit for generating at least associations between a non-sentiment phrase and a sentiment phrase based on the generated phrases, wherein an association between a non-sentiment phrase and at least one corresponding sentiment phrase is a taxonomy; and storing the taxonomies in a data warehouse storage connected to the network wherein responsive to a query the system provides a sentiment to a non-sentiment phrase provided in the query.

Abstract: A system for identifying hidden connections between non-sentiment phrases. The system comprises a network interface enabling an access to one or more data sources; a data warehouse storage for at least storing a plurality of phrases including sentiment phrases and non-sentiment phrases; an analysis unit for identifying hidden connections between non-sentiment phrases based on at least one proximity rule and for generating at least an association between at least two non-sentiment phrases having a hidden connection and a sentiment phrase, wherein an association between the at least two non-sentiment phrases having the hidden connection and the corresponding sentiment phrase is a term taxonomy.

Abstract: A method for real-time monitoring of changes in a sentiment respective of an input non-sentiment phrase. The method comprises receiving the input non-sentiment phrase and at least one tendency parameter respective of the input non-sentiment phrase; identifying in a data storage at least one of a term taxonomy that includes the input non-sentiment phrase, wherein the data storage contains a plurality of phrases including sentiment phrases, non-sentiment phrases, and a plurality of term taxonomies; computing a sentiment trend for the at least one term taxonomy; monitoring the sentiment trend to detect real-time changes in a direction of the sentiment trend with respect to the at least one tendency parameter; and generating at least a notification when a change in the direction of the sentiment trend with respect to the input tendency parameter has occurred.

Abstract: A method for generating a trend report for a non-sentiment phrase. The method comprises generating a plurality of term taxonomies between non-sentiment phrases and sentiment phrases; storing the plurality of term taxonomies in a database; performing periodically at least a statistical analysis respective of the plurality of term taxonomies in the database; receiving a request for a report with respect of at least a non-sentiment phrase in the database; generating a trend report based at least on the at least statistical analysis; and providing the report to the requestor of the report.

Abstract: A system for creation of term taxonomies by mining web based user generated content according. The system includes a network interface enabling access to one or more data sources; a mining unit for collecting textual content from the one or more sources and generating phrases, the generated phrases include sentiment phrases and non-sentiment phrases; an analysis unit for generating at least associations between a non-sentiment phrase and a sentiment phrase based on the generated phrases, wherein an association between a non-sentiment phrase and at least one corresponding sentiment phrase is a taxonomy; and storing the taxonomies in a data warehouse storage connected to the network wherein responsive to a query the system provides a sentiment to a non-sentiment phrase provided in the query.