Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents an index structure for retrieving electronic messages that contain mistyped words or spelling errors. Given a query string (e.g., a search key),  want to find those messages that approximately contain the query, i.e., certain inserts, deletes and mismatches are allod when matching the query with a word (or phrase) in the messages. Our approach is to store the messages sequentially in a database and hash their "fingerprints" into a number of "fingerprint files." When the query is given, its fingerprints are also hashed into the files and a histogram of votes is constructed on the messages.  derive a lor bound, based on which one can prune a large number of nonqualifying messages (i.e., those whose votes are below the lor bound) during searching. The paper presents some experimental results, which demonstrate the effectiveness of the index structure and the lor bound.
['Jason Tsong-li Wang', 'Chia-Yo Chang']
I am writing a research paper on a idea Fast retrieval of electronic messages that contain mistyped words or spelling errors
[{"from": "human", "value": "I am writing a research paper on a idea Fast retrieval of electronic messages that contain mistyped words or spelling errors"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents an index structure for retrieving electronic messages that contain mistyped words or spelling errors. Given a query string (e.g., a search key),  want to find those messages that approximately contain the query, i.e., certain inserts, deletes and mismatches are allod when matching the query with a word (or phrase) in the messages. Our approach is to store the messages sequentially in a database and hash their \"fingerprints\" into a number of \"fingerprint files.\" When the query is given, its fingerprints are also hashed into the files and a histogram of votes is constructed on the messages.  derive a lor bound, based on which one can prune a large number of nonqualifying messages (i.e., those whose votes are below the lor bound) during searching. The paper presents some experimental results, which demonstrate the effectiveness of the index structure and the lor bound."}]