Abstract:
An analysis service may crawl communication events occurring on an organization-wide application. The analysis service may analyze the events to determine communication events that are relevant to a record of a management application of the organization. The analysis service may generate data points for the record based on analysis of the communication events of the organization. The relevant communication events and data points may provide contexts to users of the management application.
Abstract:
System, method, and/or computer program product embodiments for automatic removal of sensitive data items from records are disclosed. In one or more embodiments, a record with a sensitive field (for storing a sensitive data item) is linked to a self-removal data policy that includes a condition set. When the condition set is true, the sensitive data item is automatically removed from the record without deleting the record and without removing other data items stored in other fields of the record. Conditions may be associated with a time period following the upload or storage of the sensitive date item, the occurrence of an event that requires the sensitive date item, a read or approval of the sensitive data item, etc. A user may modify a condition in the condition set to make the condition more stringent or less stringent.
Abstract:
A method of identifying topics in a corpus that includes a plurality of text-based items begins by extracting keytext from each of the plurality of text-based items, resulting in sets of keytext. The method continues by processing the keytext sets to generate a respective semantic footprint for each of the text-based items, resulting in a plurality of semantic footprints. The semantic footprints are used to calculate similarity values for the text-based items, wherein the similarity values indicate commonality between pairs of the text-based items. The method continues by clustering the text-based items into a number of topic groups, wherein the clustering is influenced by the similarity values, and by generating a topic heading for each of the number of topic groups, resulting in a number of topic headings. Next, the text-based items are grouped into accessible topic groups associated with the topic headings.