Asynchronous Word Frequency List Generation via Distributed Sampling
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Solution Overview
Problem
Existing email systems lack an efficient method to generate and maintain a list of frequently used words in a user's mailbox, which is crucial for improving voice mail transcription accuracy and personalized advertising, as current methods are either inefficient or outdated.
Innovation Solution
A server-based system that uses distributed random sampling to parse email messages, generate, and update a word frequency list asynchronously, ensuring the list is current and reducing I/O intensity by regenerating it when necessary, with heuristics to filter irrelevant words.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a word frequency list is generated by parsing all email messages, then the accuracy of transcription and advertising is improved, but the I/O intensity and processing time increase significantly
Solution Approach 1:
The patent applies partial action by parsing only a predetermined number of email messages (e.g., 100 messages) rather than all messages in the mailbox. This sampling approach generates a word frequency list that is sufficiently accurate for transcription and advertising purposes while dramatically reducing the I/O intensity and processing time compared to analyzing the complete message set.
2Reliability
If the word frequency list is updated frequently to maintain current data, then the relevance for user behavior prediction is improved, but the operational impact on the mailbox server increases
Solution Approach 1:
The system implements periodic action by updating the word frequency list only when triggered by specific conditions: when a new email message is received or when the existing list exceeds an age threshold (e.g., 30 days). This conditional periodic updating maintains data currentness and reliability for user behavior prediction while minimizing unnecessary processing operations that would impact server productivity.
Solution Approach 2:
The patent applies preliminary action by generating the word frequency list in advance and storing it for future use. The list is created before it is needed for transcription or advertising tasks, allowing the system to quickly retrieve pre-computed frequency data rather than performing intensive parsing operations at the moment of need, thus reducing operational impact on server efficiency.
3Productivity
If distributed random sampling is used to parse email messages, then the efficiency of reading and parsing is improved, but the complexity of the sampling process increases
Solution Approach 1:
The system applies self-service by implementing an automatic distributed random sampling mechanism that selects and parses email messages without requiring manual intervention. The sampling process autonomously chooses predetermined numbers of messages from the mailbox, parses them to generate word frequency lists, and manages the entire workflow independently, thereby improving parsing efficiency while keeping the operational complexity manageable through automation.
Data Source
AI summary
A method is presented for generating a list of frequently used words for an email application on a server computer. When a request is received for a word frequency list for emails stored in a user's mailbox, a word frequency list is returned if one exists. If the word frequency list does not exist, an asynchronous process is started on the server computer to generate a word frequency list. If the word frequency list exists but it is older than an aging limit, an asynchronous process is started on the server computer to regenerate the word frequency list. The word frequency list is stored in the user's mailbox along with a timestamp indicating the date and time that the list was created or updated.