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Searching the query matching keyword based on a probabilistic approach is attractive in most of the application areas, viz. spell checking and data cleaning, because it allows approximate search. A probabilistic approach with maximum likelihood estimation is used to handle real-world problems; however, it suffers from overfitting data. In this paper, a rule-based approach is presented for keyword searching. The process consists of two phases called the rule generation phase and the learning phase. The rule generation phase uses a new technique called N-Gram based Edit distance (NGE) to generate the rule dictionary. The Turing machine model is implemented to describe the rule generation using the NGE technique. In the learning phase, a log model with maximum-a-posterior estimation is used to select the best rule. When evaluated in real time, our system produces the best result in terms of efficiency and accuracy.<\/jats:p>","DOI":"10.1515\/jisys-2016-0067","type":"journal-article","created":{"date-parts":[[2017,4,13]],"date-time":"2017-04-13T06:00:53Z","timestamp":1492063253000},"page":"555-563","source":"Crossref","is-referenced-by-count":1,"title":["Log Posterior Approach in Learning Rules Generated using N-Gram based Edit distance for Keyword Search"],"prefix":"10.1515","volume":"27","author":[{"given":"M.","family":"Priya","sequence":"first","affiliation":[{"name":"Bharathiyar College of Engineering and Technology , Department of Computer Science and Engineering , Karaikal, Puduchery , India"}]},{"given":"R.","family":"Kalpana","sequence":"additional","affiliation":[{"name":"Pondicherry Engineering College , Department of Computer Science and Engineering , Pillaichavady, Puducherry , India"}]}],"member":"374","published-online":{"date-parts":[[2017,4,13]]},"reference":[{"key":"2025120523275902401_j_jisys-2016-0067_ref_001_w2aab3b7b1b1b6b1ab1b5b1Aa","doi-asserted-by":"crossref","unstructured":"A. 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