{"title":"User dictionary merge for enhancing smart phone auto prediction","authors":"Abhijit Prakash Bhatnagar, A. Sehgal","doi":"10.1109/NCC.2015.7084844","DOIUrl":null,"url":null,"abstract":"Smart phone keyboards render a device based text prediction system which is usually built around the keyboard application under use. Withal, they infer a restriction since the techniques used in the system are mostly confined to device in scope. In this paper, we formulate a method to merge various user dictionaries so as to increase keystroke savings on average for a smart phone user. The method described in this paper takes into account relations among a multitude of users, and applies it to merge the user dictionary at a level derived from the relations. We show an increase in percentage keystroke savings for experimental data by applying this algorithm to context insensitive variation of word prediction.","PeriodicalId":302718,"journal":{"name":"2015 Twenty First National Conference on Communications (NCC)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Twenty First National Conference on Communications (NCC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCC.2015.7084844","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Smart phone keyboards render a device based text prediction system which is usually built around the keyboard application under use. Withal, they infer a restriction since the techniques used in the system are mostly confined to device in scope. In this paper, we formulate a method to merge various user dictionaries so as to increase keystroke savings on average for a smart phone user. The method described in this paper takes into account relations among a multitude of users, and applies it to merge the user dictionary at a level derived from the relations. We show an increase in percentage keystroke savings for experimental data by applying this algorithm to context insensitive variation of word prediction.