DocumentCode :
2062694
Title :
Recommendation by composition style
Author :
Karmakar, Saurav ; Zhu, Ying
Author_Institution :
Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA, USA
fYear :
2010
fDate :
Nov. 29 2010-Dec. 1 2010
Firstpage :
818
Lastpage :
822
Abstract :
Composition style is often an important factor in readers\´ selection of reading materials. For example, a reader may seek out articles written in similar style as his or her favorite writer. We present a new method for providing recommendations based on the composition style. Our algorithm analyzes and encodes the readability index and syntactical structure of a model document, and then searches for articles with similar readability index and structure. The text readability and syntactical structures are visualized to help readers compare the documents and make the selection. Our method adds a "search by style" component to the traditional keyword based search, and provides recommendation that fits the user\´s personal preferences better. We demonstrate our method by applying it to product review recommendation based on user preferred composition style.
Keywords :
information filtering; recommender systems; text analysis; keyword based search; model document; personal preferences; product review recommendation; readability structure; reader selection; reading materials; search by style component; similar readability index; syntactical structures; text readability; user preferred composition style; Composition style; Matrix; Recommendation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Systems Design and Applications (ISDA), 2010 10th International Conference on
Conference_Location :
Cairo
Print_ISBN :
978-1-4244-8134-7
Type :
conf
DOI :
10.1109/ISDA.2010.5687163
Filename :
5687163
Link To Document :
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