Abstract: A system for generating data from social media messages for the real-time evaluation of publicly traded assets includes an ingest component for ingesting the social media messages and a filter module eliminating expressions not considered useful language from social media messages and configuring input social media message into useful formats to form filtered social media messages. The system also includes a language processor processing the filtered social media messages based upon lexical databases to form filter and processed social media messages. The system further includes a sentiment calculator applying rules to the filtered and processed social media messages so as to compute a representation of sentiment values associated with the social media messages. A graphical user interface displaying the sentiment values is also provided.

Abstract: A system for generating data from social media messages for the real-time evaluation of publicly traded assets includes an ingest component for ingesting the social media messages and a filter module eliminating expressions not considered useful language from social media messages and configuring input social media message into useful formats to form filtered social media messages. The system also includes a language processor processing the filtered social media messages based upon lexical databases to form filter and processed social media messages. The system further includes a sentiment calculator applying rules to the filtered and processed social media messages so as to compute a representation of sentiment values associated with the social media messages. A graphical user interface displaying the sentiment values is also provided.

Abstract: A computer-implemented system for real time topic detection in a social media message includes a knowledge base of keywords used to ingest the social media message and a partial parser deriving a syntax-semantic parse tree. The system also includes a topic calculator compositionally deriving the topic of the social media message by computing a topic value for given entities in the event described by the social media message. The topic value is derived from a first set of rules assigning Restrictor R-value to prominent R-expressions compositionally in the syntax-semantic parse tree and a second set of rules assigning a numeric Strength S-value to the R-expressions according to whether or not they are part of anaphoric chains in the social media message, and whether or not the R-expressions include name entities that are part of the knowledge base of keywords.

Abstract: A sentiment calculator uses social media messages for the real-time evaluation of publicly assets, in particular traded equities and commodities wherein a sentiment is an integer computed based upon pairs of lexical items in local syntactic context. The sentiment calculator includes a mechanism for determining polarity in social media messages and a mechanism for determining a strength value of lexical items used in social media messages.

Abstract: A system for generating data from social media messages for the real-time evaluation of publicly traded assets includes an ingest component for ingesting the social media messages and a filter module eliminating expressions not considered useful language from social media messages and configuring input social media message into useful formats to form filtered social media messages. The system also includes a language processor processing the filtered social media messages based upon lexical databases to form filter and processed social media messages. The system further includes a sentiment calculator applying rules to the filtered and processed social media messages so as to compute a representation of sentiment values associated with the social media messages. A graphical user interface displaying the sentiment values is also provided.

Abstract: A reaction indicator in the form of a graphical user interface is disclosed. The reaction indicator combines sentiment and intensity data relating to an asset for use in real-time evaluation of publicly traded assets, in particular equities and commodities. The reaction indicator includes graphic objects displayed upon a monitor that depict social media market sentiment, a timeline slider object, and a vertical bar chart object. The sentiment is derived based upon pairs of lexical items in local syntactic context found in a volume of social media messages.

Abstract: A sentiment calculator uses social media messages for the real-time evaluation of publicly assets, in particular traded equities and commodities wherein a sentiment is an integer computed based upon pairs of lexical items in local syntactic context. The sentiment calculator includes a mechanism for determining polarity in social media messages and a mechanism for determining a strength value of lexical items used in social media messages.

Abstract: A method for retrieving and modifying data elements on a shared medium following request from multiple client computers, such that data retrieval transactions on a data element, originating from one or more clients, are not compromised by data update transactions on the same data element originating from other clients. The shared medium controller receives from multiple clients transaction requests for reading or writing a data element stored on the shared medium. The transactions requests are added to an execution queue in order. All read transaction requests are then retrieved and executed in parallel, up to a write transaction request on the data element. The write transaction request is then executed while all incoming read transaction requests for the same data element are queued until the write transaction request is completed.

Abstract: A method for executing a write request in a clustered computing environment, comprising a plurality of computers connected in a network, including at least one client computer accessing data blocks stored on a first storage device of a shared aggregated pool of storage devices. Data blocks stored on the first storage device are linked to data blocks stored on at least one second storage device of the pool by error recovery data stored on a third storage device of the pool. When a client computer sends a write request to the first storage device for a new data block to be stored at an address on the first storage device, the new data block is written at the address on the first storage device. New error recovery data is calculated for the data block and is written to the third storage device.

Abstract: The data storage system comprises a scalable number of routing processors (RPs) through which clients of a network communicate. The storage system also includes a scalable number of storage processors (SPs) connected to a scalable number of storage units (SUs). This data storage system provides a new and hybrid approach which lies in between conventional NAS and SAN environments. It creates a unified and scalable storage pool accessible through a single consistent directory without the need for a metadata controller (MDC). There is thus no table lookup at a central node and no single point of failure. It allows a dissociation of the relationship between the physical path and the actual location where the data objects are stored.

Abstract: A method for retrieving and modifying data elements on a shared medium following request from multiple client computers, such that data retrieval transactions on a data element, originating from one or more clients, are not compromised by data update transactions on the same data element originating from other clients. The shared medium controller receives from multiple clients transaction requests for reading or writing a data element stored on the shared medium. The transactions requests are added to an execution queue in order. All read transaction requests are then retrieved and executed in parallel, up to a write transaction request on the data element. The write transaction request is then executed while all incoming read transaction requests for the same data element are queued until the write transaction request is completed.

Abstract: The data storage system comprises a scalable number of routing processors (RPs) through which clients of a network communicate. The storage system also includes a scalable number of storage processors (SPs) connected to a scalable number of storage units (SUs). This data storage system provides a new and hybrid approach which lies in between conventional NAS and SAN environments. It creates a unified and scalable storage pool accessible through a single consistent directory without the need for a metadata controller (MDC). There is thus no table lookup at a central node and no single point of failure. It allows a dissociation of the relationship between the physical path and the actual location where the data objects are stored.