MESSAGE RECOMMENDATION USING WORD ISOLATION AND CLUSTERING

摘要

Network system provides a real-time adaptive recommendation set of documents with a high statistical measure of relevancy to the requestor device. The recommendation set is optimized based on analyzing text of documents of the interest set, categorizing these documents into clusters, extracting keywords representing the themes or concepts of documents in the clusters, and filtering a population of eligible documents accessible to the system utilizing site and or Internet-wide search engines. The system is either automatically or manually invoked and it develops and presents the recommendation set in real-time. The recommendation set may be presented as a greeting, notification, alert, HTML fragment, fax, voicemail, or automatic classification or routing of customer e-mail, personal e-mail, job postings, and offers for sale or exchange.

主权项

1. A method for recommending email messages for further user action, the method comprising:
storing a plurality of email messages in memory of a computing device, the email messages having been previously responded to by a user and the computing device including a processor and executable instructions stored in the memory; and executing the instructions stored in the memory, wherein execution of the instructions by the processor:
computes a plurality of similarity scores between the email messages previously responded to by the user, each of the similarity scores indicating a level of similarity between one or more words in a first email message from among the plurality of email messages and one or more words in a second email message from among the plurality of email messages,groups the plurality of email messages into a plurality of clusters based on the computed similarity scores, andrecommends an email message received subsequent to the clustering of the email messages for further user action, wherein recommending the subsequently received email message includes calculating a relevance score for the subsequently received email message based on the plurality of clusters and one or more words in the subsequently received email message.