TY - GEN
T1 - A method for extracting attractive sentences from an electronic book based on reviews for effective browsing
AU - Murai, Soichi
AU - Ushiama, Taketoshi
PY - 2011/9/29
Y1 - 2011/9/29
N2 - Recently, electronic book(e-book) market is growing rapidly and people become able to choice e-books that they would like to read from a large amount of e-books. Therefore, systems for finding efficiently one or more sufficient books that have something worth reading from vast numbers of e-books are demanded. In order to support users to select books, many techniques for searching and recommending books have been proposed. However the users would have to judge whether each book in candidates is worth reading. We think that stand reading is effective for the selecting actual books at bookstores in the real world. In this paper, we introduce a method for supporting stand reading on e-books on the Web. Our method recommends a user sentences which would attract and/or interest the user in a book. In our method, firstly, the attractiveness of each term in a book is calculated based on reviews about the book on the Web. Then, the attractiveness of each sentence in the book is calculated based on the attractiveness of the terms. Furthermore, this paper shows the experimental results of our method and discusses its effectiveness.
AB - Recently, electronic book(e-book) market is growing rapidly and people become able to choice e-books that they would like to read from a large amount of e-books. Therefore, systems for finding efficiently one or more sufficient books that have something worth reading from vast numbers of e-books are demanded. In order to support users to select books, many techniques for searching and recommending books have been proposed. However the users would have to judge whether each book in candidates is worth reading. We think that stand reading is effective for the selecting actual books at bookstores in the real world. In this paper, we introduce a method for supporting stand reading on e-books on the Web. Our method recommends a user sentences which would attract and/or interest the user in a book. In our method, firstly, the attractiveness of each term in a book is calculated based on reviews about the book on the Web. Then, the attractiveness of each sentence in the book is calculated based on the attractiveness of the terms. Furthermore, this paper shows the experimental results of our method and discusses its effectiveness.
UR - http://www.scopus.com/inward/record.url?scp=80053155810&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80053155810&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-23866-6_3
DO - 10.1007/978-3-642-23866-6_3
M3 - Conference contribution
AN - SCOPUS:80053155810
SN - 9783642238659
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 24
EP - 33
BT - Knowledge-Based and Intelligent Information and Engineering Systems - 15th International Conference, KES 2011, Proceedings
T2 - 15th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2011
Y2 - 12 September 2011 through 14 September 2011
ER -