Abstract: A system for detection of potential legal liability is presented. The system uses factual information that has triggered liability based on any number of legal theories, and compares the words expressing those facts to customer and employee communications in order to identify potential liability to an enterprise by reviewing of the enterprise's emails. The system generates seeding information based on the factual information and words expressing certain sentiments, and provides the seeding information to a document fracturing engine which scans the email archives and identifies emails with words that potentially give rise to a liability risk. The identified emails may then be reviewed by authorized personnel so that appropriate proactive and/or corrective action may be taken before the legal liability occurs.

Abstract: A system for detection of potential legal liability is presented. The system uses factual information that has triggered liability based on any number of legal theories, and compares the words expressing those facts to customer and employee communications in order to identify potential liability to an enterprise by reviewing of the enterprise's emails. The system generates seeding information based on the factual information and words expressing certain sentiments, and provides the seeding information to a document fracturing engine which scans the email archives and identifies emails with words that potentially give rise to a liability risk. The identified emails may then be reviewed by authorized personnel so that appropriate proactive and/or corrective action may be taken before the legal liability occurs.

Abstract: In one embodiment the present invention includes a method for standardizing certain textual elements of an unstructured text to enhance the use of the unstructured text as a data source for an analytical processing tool. In accordance with one or more user-defined pre-processing directives, a pre-processing logic identifies textual elements of a certain type, and converts the underlying textual elements to conform to user-defined standards for the particular type. The converted textual element is then inserted into the unstructured text, or an index based on the unstructured text, thereby improving the use of the unstructured text as a data source for conventional analytical processing (e.g., querying) tools.

Abstract: In one embodiment, the present invention includes a method for conditioning semi-structured text to enhance its use as a data source for an analytical processing tool. In general, the method involves analyzing the semi-structured text to identify portions of text (referred to herein as sub-documents) that exhibit a repetitive characteristic. Next, for each sub-document identified, the semi-structured text is integrated, for example, by filtering the text for relevant words, removing stop words, stemming certain words, adding or replacing certain words with synonyms, modifying the spelling of certain words, and/or resolving certain homonyms based on a document class assigned to the semi-structured text, and so on. Once integrated, the sub-documents are mapped to existing structures defined for the document class and/or sub-document type.