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 and system for generating alerts based on term taxonomies. The method includes analyzing textual content to detect a plurality of phrases in the textual content; identifying each of the detected phrases as any of: a sentiment phrase, and a non-sentiment phrase, wherein each sentiment phrase includes at least one word describing a sentiment; associating each identified non-sentiment phrase with at least one of the identified sentiment phrases to create at least one term taxonomy; analyzing the at least one term taxonomy to determine whether each identified non-sentiment phrase is associated with any of: a highly positive sentiment, and a highly negative sentiment; and generating an alert, when it is determined that one of the non-sentiment phrases is associated with any of: a highly positive sentiment, and a highly negative sentiment.

Abstract: A method and system for predicting user behaviors based on term taxonomies are provided. The system comprises generating phrases respective of user generated content, wherein each phrase is a sentiment phrase or a non-sentiment phrase, each sentiment phrase including at least one word describing a sentiment; identifying at least one connection between at least two of the generated phrases, wherein each connection is a direct connection or a hidden connection; generating at least one term taxonomy based on the identified at least one connection, wherein each term taxonomy is an association between a non-sentiment phrase and at least one of a plurality of sentiment phrases; periodically analyzing the at least one term taxonomy to determine at least one trend of each non-sentiment phrase respective of the associated plurality of sentiment phrases; and generating a prediction of future behavior of the at least one trend with respect to the at least one term taxonomy.

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 and system for predicting user behaviors based on term taxonomies are provided. The system comprises generating phrases respective of user generated content, wherein each phrase is a sentiment phrase or a non-sentiment phrase, each sentiment phrase including at least one word describing a sentiment; identifying at least one connection between at least two of the generated phrases, wherein each connection is a direct connection or a hidden connection; generating at least one term taxonomy based on the identified at least one connection, wherein each term taxonomy is an association between a non-sentiment phrase and at least one of a plurality of sentiment phrases; periodically analyzing the at least one term taxonomy to determine at least one trend of each non-sentiment phrase respective of the associated plurality of sentiment phrases; and generating a prediction of future behavior of the at least one trend with respect to the at least one 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 and system for predicting future trends of terms taxonomies of users generated content are provided. The method includes crawling one or more sources of users generated content to collect phrases mentioned by users of the one or more data sources; periodically analyzing one or more term taxonomies to determine at least a trend of at least a non-sentiment phrase with respect of a plurality of sentiment phrases, wherein a term taxonomy is an association between a non-sentiment phrase and a sentiment phrase, the non-sentiment and sentiment phrases are included in the collected phrases; and generating a prediction of future behavior of the at least trend with respect of the one or more term taxonomies.

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 method and system for predicting future trends of terms taxonomies of users generated content are provided. The method includes crawling one or more sources of users generated content to collect phrases mentioned by users of the one or more data sources; periodically analyzing one or more term taxonomies to determine at least a trend of at least a non-sentiment phrase with respect of a plurality of sentiment phrases, wherein a term taxonomy is an association between a non-sentiment phrase and a sentiment phrase, the non-sentiment and sentiment phrases are included in the collected phrases; and generating a prediction of future behavior of the at least trend with respect of the one or more term taxonomies.

Abstract: A method and system for predicting future trends of terms taxonomies of users generated content. The method comprises crawling one or more sources of users generated content to collect phrases mentioned by users of the one or more data sources; periodically analyzing one or more term taxonomies to determine at least a trend of at least a non-sentiment phrase with respect of a plurality of sentiment phrases, wherein a term taxonomy is an association between a non-sentiment phrase and a sentiment phrase, the non-sentiment and sentiment phrases are included in the collected phrases; and generating a prediction of future behavior of the at least trend with respect of the one or more term taxonomies.

Abstract: A computerized method, apparatus and system for interfacing with one or more advertisement publishers across a network. The method includes receiving an advertisement and associated metadata from a client node over the network using a general purpose application programming interface (GPAPI); determining a list of recommended publishers for the advertisement based on at least the advertisement and the associated metadata; and placing the advertisement with one or more publisher nodes of publishers selected out of the recommended publishers, wherein communication with each publisher node of the selected publishers is performed using an application programming interface (API) of a respective publisher node.

Abstract: A method and system for predicting future trends of terms taxonomies of users generated content. The method comprises crawling one or more sources of users generated content to collect phrases mentioned by users of the one or more data sources; periodically analyzing one or more term taxonomies to determine at least a trend of at least a non-sentiment phrase with respect of a plurality of sentiment phrases, wherein a term taxonomy is an association between a non-sentiment phrase and a sentiment phrase, the non-sentiment and sentiment phrases are included in the collected phrases; and generating a prediction of future behavior of the at least trend with respect of the one or more term taxonomies.

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 bidding for an advertisement placement of an on-line advertisement. The method comprises identifying at least a trend for at least a first term appearing in at least one data source; extracting at least a second term from at least one on-line advertisement; performing a correlation analysis, responsive of a desired trend of the at least first term, between the at least first term and the at least second term; and placing a bid for placement of the at least one on-line advertisement for any one of the at least first term and the at least second term that demonstrates a predefined correlation.

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.