TE4-2 30th Fuzzy System Symposium(Kochi,September 1-3,2014) Advertising Slogan Selection System Using Review Comments on the Web. 2 Masafumi Hagiwara

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1 Web Advertising Slogan Selection System Using Review Comments on the Web 1 1 Hiroaki Yamane, 2 2 Masafumi Hagiwara 1 1 Graduate School of Science and Technology, Keio University Abstract: Increased demand for web advertising has resulted in a corresponding increase in the need to develop personalized advertisements targeted at individuals online. We propose an automated advertising slogan selection system that can satisfy this requirement. Many customer reviews and comments are available publicly on online shopping sites. The proposed system uses content mining to extract favorable reports from the web and arranges the data into a specific knowledge representation structure to improve the advantage of the target product. For a particular business, the proposed system first extracts tuples, composed of elements that express the knowledge representation from each user-written review. Then, these tuples are selected using a frequency-based approach and emotion corpus. Subsequently, for each tuple, advertising slogans are chosen from the advertising slogan corpora using a neural network. For verification, we used data from an electronic commerce website for hotels to evaluate two aspects of our system (namely, quality of selected tuples and advertising slogans). The results of the experiments confirm that the proposed system can extract suitable tuples when the given data are sufficient. It can also retrieve slogans even when their meanings are convoluted. 1 EC 2012 Web 1 [1] EC EC EC EC Web (1) (2) (1) (2) EC (: ) (: ) (:,,) 654

2 EC Taisetsuna ano hito to, kitto nanndomo otozureru machi ni naru. Without doubt, you will return many times to this lovely town. 2008/Yomiuri(the Japanese Newspaper Publisher)/the Austrian Airlines/ You can fully enjoy fascinating Vienna in-depth Main Slogan Metadata 2: (=) 1: 2.1 EC [2] 2.2 [3] T j j F t () j n n j=1 F t(t j ) n j=1 F a(t j ) S t S t = ( ) Ft (T j ) n F F j=1 t(t j ) t (T j ) ( ) (1) Fa (T j ) n F j=1 a(t j ) F t (T j ) [4]

3 w j II k II w i II j II w j I k I x i I j I S a S S n Other Slogans Selection Other slogans Pre-constructed Words in slogan Slogan Selection Slogans Metadata Link Metadata Words in Metadata Sentences containing extracted 3-tuples 3: [5] [6] 3 (1) (2) t ji F ki (t ji ) t ji F Metadata (t ji ) w ji k i w ji k I = F ki (t ji ) F Metadata (t ji ) (2) t jii F iii (t jii ) t jii F Slogan (t jii ) w iii j II w iii j II = F i II (t jii ) F Slogan (t jii ) (3) Slogans Other slogans ( Slogans ) i F ii (t ji ) t ji X(i I ) = {x ii 1, x ii 2,..., x ii N ji } x ii j I = F ii (t ji ) (4) X(i I ) w ji k I k S S (i I, k I ) S S (i I, k I ) = N ji j I =1 w ji k I x ii j I = N ji j I =1 F ii (t ji )F ki (t ji ) F Metadata (t ji ) S S (i I, k I ) ( Slogan ) (5) 656

4 2.3.2 ( Other slogans ) S S (i I, k I ) F kiii t jii F kiii (t all ) ( ) ( Other slogans ) w jii k II 1: (1-5) (1-5) (1-5) (s) w jii k II = F ki II (t jii ) F kiii (t all ) (6) F kiii (t all ) S a (S s, k II ) S a (S s, k II ) = = N jii j II =1 N jii j II =1 w iii j II w jii k II S S (7) F iii (t jii )F kiii (t jii ) F Slogan (t jii )F kiii (t all ) S S (8) S a (S s, k II ) (1) (2) [7] 100 ( 85,052 ) KNP [8] [9] 20 (1) : 1 2 (5) (5) 2,000 24,439 () (8) 2,000 (8) 500 (5) (8) () 2, (i) ( 5:-1:) (ii) ( 5:-1:) (iii) ( 5:-1:) ( Slogans ) ( Other slogans ) 2 Other slogans (5) (8) (5) (8) 657

5 3: 1 (1-5) (1-5) (1-5) (s) : 2 (1-5) (1-5) (1-5) (s) [10, 11, 12, 13] 24, [14] [15] 2, (i) ( 5:-1: ) (ii) ( 5:-1:) (iii) ( 5:-1: ) Web bag-of-words [1] Forbes: Online ad spending tops $100 billion in 2012, /01/09/online-ad-spending-tops-100- billion-in-2012/, [2], :,, Vol.49, No.7, pp ,

6 [3] Hiroaki Yamane, Masafumi Hagiwara: Tag line generating system using knowledge extracted from statistical analyses, AI & Society 28 pp.1-11, [4] :,, [5] J. L. Elman: Distributed representations, simple recurrent network, and grammatical structure, pp Machine Learning [6] Tsukasa Sagara, Masafumi Hagiwara: Natural language neural network and its application to question-answering systems, The International Joint Conference on Neural Networks, pp , [7] : tiku/ [8] : KNP, [9], :,, Vol.15, No.2, pp , [10] :,, [11] : 2,, [12] :,, [13] : 3,, [14],,,,,,,,, : 500,, [15] Make1:, copy.make1.jp/index.cgi yamane@soft.ics.keio.ac.jp hagiwara@soft.ics.keio.ac.jp 659