Marlon P. Davis and Miracle C. Padre.  4  0   <br/><br/>
Further enhancement of Daerau-Levenshtein Distance algorithm applied in plagiarism detection /        6 
       6     
Marlon P. Davis and Miracle C. Padre. 
 -   
 -     
 - 89 pp.     28 cm.     
 -   
 -   
 - 
 - 
 -         .
 -     .
 -          0   .
 -         .
 -  0       .
<br/><br/>   Undergraduate Thesis: (BSCS major in Computer Science)-  Pamantasan ng Lungsod ng Maynila, 2016. 
<br/><br/>
<br/><br/>      
<br/><br/>   5 
<br/><br/>      
<br/><br/> ABSTRACT:  	Damerau-Levenshtein Distance algorithm is a great tool detect plagiarism, it will compare two strings and compute their edit distance. The less the edit distance, the more similar strings are.  	The Damerau-Levenshtein distance differs from the classical Levenshtein distance by including transposition among its allowable operations. The classical Levenshtein distance only allows insertion, deletion, and substitution operations. Modifying this distance by including transpositions of adjacent symbols produces a different distance measure, known as the Damerau-Levenshtein distance.  	Many people think of plagiarism as copying another's work or borrowing someone else's original ideas. But terms like copying and borrowing can disguise the seriousness of the offense. Plagiarism is the act of taking another person's writing, conversation, song, or even idea and passing it off as your own. According to U.S. law, the answer is yes. The expression  of original ideas is considered intellectual property and is protected by copyright laws, just like original inventions. Almost all forms of expression fall under copyright protection as long as they are recorded in some way (such as a book or a computer file). The purpose of the study is to further enhance the Damerau-Levenshtein Distance Algorithm so that it can be more correct in terms of providing the right result if one of the compared strings is plagiarized.       
<br/><br/>      
<br/><br/><br/> <br/> <br/> <br/> <br/> <br/> <br/> 
<br/><br/><br/>5     
<br/><br/><br/> <br/>   
<br/><br/><label>ISBN: </label>  
<br/><br/><label>ISSN: </label>2 
 =   
 =   
<br/><br/><label>Standard No.: </label>        
<br/><br/><label>Publisher. No.: </label>  
<br/><br/><label>Source: </label>        
<br/><br/><label>LCCN: </label>
<br/><br/><label>Nat. Bib. No.: </label> 2 
<br/><br/><label>Nat. Bib. Agency Control No.: </label>    
<br/><br/><label>Subjects--Personal Names: </label><br/>     2     --0------
<br/><br/><label>Subjects--Corporate Names: </label><br/>     6 --0-- 2 --------
<br/><br/><label>Subjects--Meeting Names: </label><br/><br/> 0    2 --
<br/><br/><label>Subjects--Uniform Titles: </label><br/>  --20------
<br/><br/><label>Subjects--Chronological Terms: </label><br/> 
<br/><br/><label>Subjects--Topical Terms: </label><br/>    --------20--
<br/><br/><label>Subjects--Geographic Terms: </label><br/>--------20--
<br/><br/><label>Index Terms--Genre/Form: </label><br/>----2
<br/><br/><label>LC Class. No.: </label> / 2 
<br/><br/><label>Dewey Class. No.: </label> / 2 
<br/><br/><label>National Agricultural Library Call No.: </label> /  
<br/><br/><label>National Library of Medicine Call No.: </label> /  
<br/><br/><label>Gov. Doc. Class. No.: </label>