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Title of Journal: Soft Comput

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Abbravation: Soft Computing

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Springer Berlin Heidelberg

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DOI

10.1007/bf00394502

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1433-7479

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Similarity recognition using contextbased pattern

Authors: Hoon Ko Kitae Bae Jongsun Choi Sang Heon Kim Jongmyung Choi
Publish Date: 2015/07/08
Volume: 20, Issue: 11, Pages: 4565-4573
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Abstract

To measure the similarity of contexts in smart devices comparison is made of the userdefined contexts and another context which is defined in a server or in a network device that a user has Segev and Toch IEEE Trans Serv Comput 23210–222 2009 While it processes to compare if they find some users who have similarities with them they surely may be interested in the users because they know that they can share their information without the time wasting to search finally getting what they want However according to the characteristics of the registered contexts they are classified into two types a rankdefinitional context and a rankundefined context Also the users usually want to use the two types to get quickly what they want at the same time It means that another algorithm may be needed to get the similarity depending on the contexts because the existing similarity search algorithms usually perform the similarity process without the contexts’ characteristics analysis They assume that all contexts have the same features when they process Now the existing methods that find the similarity usually have an accuracy problem Low accuracy gives invisible services to users This paper has suggested named contextbased pattern measurement method including weight defines for higher accuracy As a result it would be able to get accuracy similarity by applying to the proposed algorithms about 69072  without weight and also 95322  accuracy in case it has a specific weight

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