Presentation | 2022-08-04 Research on Content Selection Manner by Predicting Users' Interests Focusing on Acquired Web Similarity Takeshi Tsuchiya, Rika Misawa, Ryuichi Mochizuki, Tetsuyasu Yamada, Hiroo Hirose, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This research proposes content selection methods using the characteristics of a user's most recent web content history to predict the current user's interests. Conventional methods involve identifying users on web services and deriving their interests by using similarities between their behavior patterns and those of users in the past, but this is considered to be a problem due to the acquisition of user information, including personal information such as web behavior and history, by third parties. The proposed method constructs a combinable feature model named fog model analyzing the features of the acquired web content, and combines it with the user's history. The fog model is combinable feature model able to predict the characteristics of the user's most recent interests. The proposed method provides information similar to the user's interests from the most similar candidate contents. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Users' Interest / web targetting / distributed learning |
Paper # | IN2022-15 |
Date of Issue | 2022-07-28 (IN) |
Conference Information | |
Committee | IN / CCS |
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Conference Date | 2022/8/4(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Hokkaido University(Centennial Hall) |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | Network Science, Future Network, Cloud/SDN/Virtualization, Contents Delivery/Contents Exchange, and others |
Chair | Kunio Hato(Internet Multifeed) / Megumi Akai(Hokkaido Univ.) |
Vice Chair | Tsutomu Murase(Nagoya Univ.) / Hidehiro Nakano(Tokyo City Univ.) / Masaki Aida(TMU) |
Secretary | Tsutomu Murase(KDDI Research) / Hidehiro Nakano(Nagaoka Univ. of Tech.) / Masaki Aida(NTT) |
Assistant | / Hiroyuki Yasuda(Univ. of Tokyo) / Hiroyasu Ando(Tsukuba Univ.) / Tomoyuki Sasaki(Shonan Inst. of Tech.) / Miki Kobayashi(Rissho Univ.) |
Paper Information | |
Registration To | Technical Committee on Information Networks / Technical Committee on Complex Communication Sciences |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Research on Content Selection Manner by Predicting Users' Interests Focusing on Acquired Web Similarity |
Sub Title (in English) | |
Keyword(1) | Users' Interest |
Keyword(2) | web targetting |
Keyword(3) | distributed learning |
1st Author's Name | Takeshi Tsuchiya |
1st Author's Affiliation | Tokyo International University(Tokyo International Univ.) |
2nd Author's Name | Rika Misawa |
2nd Author's Affiliation | Suwa University of Science(SUS) |
3rd Author's Name | Ryuichi Mochizuki |
3rd Author's Affiliation | Suwa University of Science(SUS) |
4th Author's Name | Tetsuyasu Yamada |
4th Author's Affiliation | Suwa University of Science(SUS) |
5th Author's Name | Hiroo Hirose |
5th Author's Affiliation | Suwa University of Science(SUS) |
Date | 2022-08-04 |
Paper # | IN2022-15 |
Volume (vol) | vol.122 |
Number (no) | IN-146 |
Page | pp.pp.7-10(IN), |
#Pages | 4 |
Date of Issue | 2022-07-28 (IN) |