| Presentation | 2019-09-27 Caputuring the correlation between consumers' preferences among different domains from E-commerce review data Gaia Suzuki, Masanao Ochi, Ichiro Sakata, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Segmentation is essential for strategical marketing, but it is considered difficult to both divide market needs among different retail domains and reveal the segmentation variables systematically. Recently, deep recommender systems became a practical solution to predict user preference using review texts as input, and has the potential to both divide and comprehend market needs. As an exploratory analysis to achieve this goal, we developed a cross-domain recommender system using Amazon review dataset to grasp the correlation of user preferences between different retail sectors. We then tried to extract essential features from the review text using latent dirichlet allocation. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | E-commerce site / segmentation / feature learning / cross-domain recommendation / LDA |
| Paper # | NLC2019-15 |
| Date of Issue | 2019-09-20 (NLC) |
| Conference Information | |
| Committee | NLC / IPSJ-DC |
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| Conference Date | 2019/9/27(2days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Future Corporation |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | The Thirteenth Text Analytics Symposium |
| Chair | Takeshi Sakaki(Hottolink) / Ryoji Akimoto(Toppan Printing) |
| Vice Chair | Mitsuo Yoshida(Toyohashi Univ. of Tech.) / Kazutaka Shimada(Kyushu Inst. of Tech.) |
| Secretary | Mitsuo Yoshida(Ryukoku Univ.) / Kazutaka Shimada(NTT) / (Future Univ. Hakodate) |
| Assistant | Takeshi Kobayakawa(NHK) / Hiroki Sakaji(Univ. of Tokyo) |
| Paper Information | |
| Registration To | Technical Committee on Natural Language Understanding and Models of Communication / Special Interest Group on Document Communication |
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| Language | JPN |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Caputuring the correlation between consumers' preferences among different domains from E-commerce review data |
| Sub Title (in English) | |
| Keyword(1) | E-commerce site |
| Keyword(2) | segmentation |
| Keyword(3) | feature learning |
| Keyword(4) | cross-domain recommendation |
| Keyword(5) | LDA |
| 1st Author's Name | Gaia Suzuki |
| 1st Author's Affiliation | The University of Tokyo(The Univ. of Tokyo) |
| 2nd Author's Name | Masanao Ochi |
| 2nd Author's Affiliation | The University of Tokyo(The Univ. of Tokyo) |
| 3rd Author's Name | Ichiro Sakata |
| 3rd Author's Affiliation | The University of Tokyo(The Univ. of Tokyo) |
| Date | 2019-09-27 |
| Paper # | NLC2019-15 |
| Volume (vol) | vol.119 |
| Number (no) | NLC-212 |
| Page | pp.pp.35-40(NLC), |
| #Pages | 6 |
| Date of Issue | 2019-09-20 (NLC) |