Extracting actionable information from emails

A system for improving efficiency of a computing device in extracting actionable information from a message, comprising:

• a parser, operable to receive a message and break the message into nodes based on a structure of the message, wherein the nodes are organized according to a tree structure;
• a domain dictionary, in communication with the parser;
• a template library, in communication with the parser;
• wherein the parser is further operable to identify keywords in nodes of the message matching entries in the domain dictionary and assign node scores to each of the nodes based on keyword presence;
• wherein the parser is further operable to identify an area of interest in the message comprising a given node and child nodes of the given node based on the given node having a highest node score that is furthest from a root of the tree structure;
• wherein the parser is further operable to identify a template for the message from the template library;
• and
• wherein the parser is further operable to extract actionable information from the area of interest based on the template.

A computer readable storage device including instructions, which when executed by a processor are operable to:

• defining a plurality of nodes of an email message, the plurality of nodes arranged in a tree structure based on a structure of the email message;
• parse the email message according to a domain dictionary to identify keywords from the domain dictionary included in leaf nodes in the tree structure;
• increment a node score for each leaf node that includes at least one keyword;
• combine node scores of each child node of the tree structure at a parent node;
• identify a node in the tree structure having a highest node score;
• define the node having the highest node score and child nodes of the node having the highest node score as an core region in the email message;
• identify one or more sub-templates having tree structures and node scores matching tree structures and node scores of one or more portions of the core region;
• identify an ur-template that includes the one or more sub-templates;
• and
• extract actionable information from the core region based on the ur-template.