Abstract: Systems, methods, and other embodiments associated with a visual guidance model are described. In one embodiment, a method includes generating, via a graphical user interface (GUI), a multi-process scenario including creating one or more process goals, where each define a stage in a lifecycle of the multi-process scenario, and creating one or more objectives within each process goal that defines a task for accomplishing the corresponding process goal, and configuring at least one objective to display a description of the task performed by the objective. The example method may also include configuring, via the GUI, the objectives to include guided actions that partition the task to be performed into a sequence of guided actions for the corresponding objective, and for a selected objective, configuring, via the GUI, the guided action to display an explanation for how to perform the associated guided action upon being selected.

Abstract: Techniques for enterprise data aggregation and collective insights generation are disclosed, including: receiving multiple sets of enterprise-specific customer relationship management (CRM) data, respectively, from enterprise-specific CRMs; aggregating the sets of enterprise-specific CRM data, to obtain collective CRM data; receiving a request to generate a collective insight that is applicable to a particular subset of the collective CRM data; responsive to the request, selecting a particular machine learning model from multiple machine learning models, wherein each machine learning model is configured to generate collective insights for a respective subset of the collective CRM data; generating the collective insight that is applicable to the particular subset of the collective CRM data, using the particular machine learning model.

Abstract: Techniques for initiating system actions based on text content are disclosed. A system applies a semantic analysis model at run-time to human-understandable text to identify actionable content within the human-understandable text. The system analyzes metadata associated with the text to identify a mapping between one or more data objects associated and the semantic content in the text. The system identifies one or more contact lists associated, respectively, with the one or more data objects. Using a database schema, the system analyzes the contact lists to determine whether to modify the contact lists.

Abstract: Techniques for modifying rules for completing requests using a conversational interface are disclosed. A conversational interface receives a user request to perform a particular function. A system extracts semantic content from the request and obtains contextual metadata associated with the request. Using the semantic content and contextual metadata, the system generates a data set of attribute values. The system determines whether the data set matches a data set of required data attributes associated with the request. If the provided data set is different than the required data set, the system determines whether to modify a set of rules associated with the request. The set of rules specifies which attribute values are required to complete the request. When the system modifies the rules associated with the request, the system also determines whether to apply the rule modification to subsequent requests by the same user and other users.

Abstract: Techniques for modifying rules for completing requests using a conversational interface are disclosed. A conversational interface receives a user request to perform a particular function. A system extracts semantic content from the request and obtains contextual metadata associated with the request. Using the semantic content and contextual metadata, the system generates a data set of attribute values. The system determines whether the data set matches a data set of required data attributes associated with the request. If the provided data set is different than the required data set, the system determines whether to modify a set of rules associated with the request. The set of rules specifies which attribute values are required to complete the request. When the system modifies the rules associated with the request, the system also determines whether to apply the rule modification to subsequent requests by the same user and other users.

Abstract: A system filters a data set for the efficient execution of queries by removing at least some irrelevant records to generate a reduced data set. The records are determined to be irrelevant based on the values of the records for the particular attribute(s) corresponding to the filtering operation. The system filters out records within a data set that do not include any of the values defined for the particular attribute by a set of queries that are to be executed on the filtered set of records.

Abstract: A system filters a data set for the efficient execution of queries by removing at least some irrelevant records to generate a reduced data set. The records are determined to be irrelevant based on the values of the records for the particular attribute(s) corresponding to the filtering operation. The system filters out records within a data set that do not include any of the values defined for the particular attribute by a set of queries that are to be executed on the filtered set of records.

Abstract: Techniques are provided for designing, deploying, and executing mashups that integrate human workflows with automated processes. In an example embodiment, a system for executing mashups comprises a human interaction module, an event manager module, and a process orchestration module. The human interaction module is configured to receive user input while a human workflow included in a mashup is being executed, and to raise an event in response to the user input. The event manager module is configured to: receive the event from the human interaction module; based on the event, identify a particular automated process from one or more automated processes that are included in the mashup; and invoke the process orchestration module to execute the particular automated process based on the event. The process orchestration module is configured to execute the particular automated process in response to being invoked by the event manager module.

Abstract: A method for transporting an image file over a network is provided. The network may include two or more computers, and the image file may include a control stream, a data stream, and a cluster map stream. The method may include parsing the image file into two or more segments. A first segment may include the control stream, the cluster map stream and a first portion of the data stream. A second segment includes a second portion of the data stream. The method may also include sending the first segment from a first computer to a second computer, and sending the second segment from the first computer to the second computer.

Abstract: A method and system for managing stored data on a computer network organizes data into logical volumes, and each logical volume has a friendly name associated with it. A domain controller keeps track of the friendly names of the logical volumes and associates those friendly names with the actual physical paths of the logical volumes. When a client computer on the network wishes to access a logical volume, it sends a look-up request having the friendly name to the domain controller. The domain controller may fulfill the request by sending the path of the logical volume to the client computer.

Abstract: A method and system for managing stored data on a computer network organizes data into logical volumes, and each logical volume has a friendly name associated with it. A domain controller keeps track of the friendly names of the logical volumes and associates those friendly names with the actual physical paths of the logical volumes. When a client computer on the network wishes to access a logical volume, it sends a look-up request having the friendly name to the domain controller. The domain controller may fulfill the request by sending the path of the logical volume to the client computer.