Abstract: A method and system for summarizing messages from a message stream is disclosed in which association analysis is applied to stream of short data messages comprising words in a spoken language, such as English. Clusters of words are identified that provide a summary of the several conversations (short data messages originating from different human sources) that are imbedded in the message stream. Each word cluster may represent a set of messages that are its instances. The word clusters may collectively constitute a summary of the entire message stream. The word clusters that have been extracted from message stream may also be grouped into topics. Also, an identity of one or more message originators may be listed based on their influence on the messages being analyzed. The short data messages may also be sorted based on a geographical location of one or more originators of messages.

Abstract: Relevant queries of a database may be determined by: receiving data from a table in a database and reviewing the data and forming a K=2 graph. A K=2 graph is one which identifies relationships between two items in rows of the table in the database. If two items occur in the a same row in a database, then these two items are considered to have a relationship represented by an arc between each node which represents each data item or point. Each arc may be assigned a weight equal to the number of rows in which the two items appear together. Next, the K=2 graph may be compacted. Subsequently, cliques of up to a predetermined number, like seven nodes from the K=2 graph may be identified. For each clique that is identified, it may be determined if the clique meets a super clique threshold. The resultant super cliques are ranked.