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All Technical Committee Conferences (Searched in: All Years)
| Committee | Date Time | Place | Paper Title / Authors | Abstract | Paper # | |
| NS, IN (Joint) |
2024-03-01 14:15 |
Okinawa | Okinawa Convention Center | Content Recommendation System Considering Cache State Yuto Murakami, Yuma Fukagawa, Noriaki Kamiyama (Ritsumeikan Univ)  NS2023-223 |
The demand for large-scale content such as music and videos has increased, and it drives up the internet traffic. Conte... [more] |
NS2023-223 pp.300-305 |
| KBSE, SC | 2023-11-18 10:20 |
Miyagi | Sento Kaikan | Towards Standardized Data Model for Service Recommendation Based on User Needs Takuya Nakata, Sinan Chen (Kobe Univ.), Sachio Saiki (Kochi Univ. of Tech.), Masahide Nakamura (Kobe Univ.) KBSE2023-44 SC2023-27 |
Due to the internet's proliferation, digital devices, and COVID-19's impact, online service use has soared, driving dema... [more] | KBSE2023-44 SC2023-27 pp.57-62 |
| HCS, CNR | 2023-11-05 11:15 |
Tokyo | Kogakuin University (Primary: On-site, Secondary: Online) |
Proposal and Evaluation of Recommendation Acceptance Tendency Scale for Overtrust Awareness Yoshinori Hijikata, Reika Miwa, Aika Tsuchida (KGU), Masahiro Hamasaki, Masataka Goto (AIST) CNR2023-10 HCS2023-72 |
As services providing recommendations or judgments of AI (artificial intelligence) become popular, the problem of "recom... [more] | CNR2023-10 HCS2023-72 pp.15-20 |
| IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2023-02-21 09:45 |
Hokkaido | Hokkaido Univ. | Graph Collaborative Filtering for Video Recommendation Luwei Zhang (UTokyo), Noboru Kanazawa (Softbank), Toshihiko Yamasaki (UTokyo) ITS2022-41 IE2022-58 |
The rapid growth in the number of videos on the Internet offers great potential for users to find the content of interes... [more] | ITS2022-41 IE2022-58 pp.1-4 |
| LOIS, ICM | 2023-01-19 15:50 |
Fukuoka | Kitakyushu International Conference Center (Primary: On-site, Secondary: Online) |
Serendipity-aware niche content recommendation system Shogo Kawasaki, Kunio Matsui (KIT) ICM2022-37 LOIS2022-37 |
In recent years, the Internet has seen the proliferation of e-commerce sites such as Amazon and Rakuten, and numerous di... [more] | ICM2022-37 LOIS2022-37 pp.36-41 |
| IBISML | 2022-12-22 14:30 |
Kyoto | Kyoto University (Primary: On-site, Secondary: Online) |
Serendipity-aware niche content recommendation system Shogo Kawasaki, (KIT) IBISML2022-44 |
In recent years, the Internet has seen the proliferation of e-commerce sites such as Amazon and Rakuten, and numerous di... [more] | IBISML2022-44 pp.6-13 |
| ET | 2021-09-10 10:40 |
Online | Online | Implementation of recommendation engine, which uses data from social media, to the course introduction module. Toshikazu Iitaka (Kumamoto Gakuen Univ.) ET2021-8 |
A function which makes possible the realization of recommendations which make use of big data from external systems is ... [more] | ET2021-8 pp.1-6 |
| SC | 2020-03-16 15:45 |
Online | Online | Recommendation of Alternative Services Using Graph Embedding Koki Okubo, Yohei Murakami (Ritsumeikan Univ.) SC2019-48 |
Service clustering based on Web service description file (hereafter referred to as WSDL document) has been proposed to d... [more] | SC2019-48 pp.85-90 |
| ITE-HI, IE, ITS, ITE-MMS, ITE-ME, ITE-AIT [detail] | 2020-02-28 14:40 |
Hokkaido | Hokkaido Univ. (Cancelled but technical report was issued) |
Feature Interaction based Neural Network for Pair Matching Prediction Luwei Zhang, Xueting Wang (UTokyo), Shintaro Kaneko, Yusuke Usui, Mizuki Kobayashi, Hiroki Kojima (eureka), Toshihiko Yamasaki (UTokyo) ITS2019-50 IE2019-88 |
Online dating services have become popular in modern society. Pair matching prediction between two users in these servic... [more] | ITS2019-50 IE2019-88 pp.299-304 |
| MVE | 2019-08-30 09:00 |
Aichi | Factorization Machines based Neural Network for Pair Matching Prediction Luwei Zhang, Xueting Wang, Toshihiko Yamasaki (UTokyo) MVE2019-14 |
Online dating services have become popular in the modern society. Pair matching prediction between two users in these se... [more] | MVE2019-14 pp.49-54 |
|
| KBSE, SC | 2018-11-09 11:30 |
Hyogo | Evaluation of the Effectiveness of Recommendation while Managing the Data Density of the Web Service-User Preference Rupasingha Arachchilage Hiruni Madhusha Rupasingha, Incheon Paik (UOA) KBSE2018-30 SC2018-25 |
Recommender systems become important in the research and commercial society, where many recommendation solutions have b... [more] |
KBSE2018-30 SC2018-25 pp.13-18 |
|
| SC | 2018-06-01 15:20 |
Fukushima | UBIC 3D Theater, University of Aizu | QoS Prediction for Situated Service Recommendation under Rating Scarcity Jiapeng Dai, Donghui Lin, Toru Ishida (Kyoto Univ.) SC2018-6 |
With rapid growth in the number and variety of Web services, how to recommend suitable services to users becomes a big c... [more] | SC2018-6 pp.33-36 |
| IN | 2018-01-22 13:50 |
Aichi | WINC AICHI | Autonomous Distributed Calculation and Storage of Tie Strengths between Contents in Graph System Daichi Kitamura, Kunitake Kaneko (Keio University) IN2017-76 |
Graphs as relation between contents is used to calculate the tie strength between them and it is of- ten used for recomm... [more] | IN2017-76 pp.37-42 |
| HCGSYMPO (2nd) |
2017-12-13 - 2017-12-15 |
Ishikawa | THE KANAZAWA THEATRE | Extraction of Physical Shop Visitor's Preferences based on Taking Action of Flyers
-- Initial Experiment for Sensing of Taking Action of Flyers -- Tomoyo Sasao (Tokushima Univ.), Shin'ichi Konomi (Kyushu Univ.) |
Digital space is possible to collect and store user’s behavior history easily, so that technology for estimating visitor... [more] | |
| NLC, IPSJ-IFAT | 2017-02-10 15:10 |
Osaka | Calculating the Similarity of Hobbies and Preferences by Word2Vec Using Dating Service Data Toshiki Akehata, Kentaro Nakanishi, Takuya Iwamoto (mixi) NLC2016-51 |
Dating Service is a service that users can search for lovers through the Internet. Many of the conventional dating serv... [more] |
NLC2016-51 pp.81-84 |
|
| NS, CQ, ICM, NV (Joint) |
2016-11-24 15:25 |
Yamaguchi | Shimonoseki Chember of Commerce and Industry | [Invited Talk]
Network Services Based on Enterprise Value Coordination Toshihiro Nishizono (Nihon Univ.) NS2016-108 CQ2016-80 ICM2016-26 |
The speaker proposes configuration of a platform for implementing new network services based on coordination of enterpri... [more] | NS2016-108 CQ2016-80 ICM2016-26 pp.39-42(NS), pp.37-40(CQ), pp.9-12(ICM) |
| NLC, TL | 2016-06-05 10:20 |
Hokkaido | Otaru University of Commerce | A Comparative Analysis of Sizzle words for Automatic Extraction of "Palatability" Maki Morita (Wakayama Univ.), Eiji Aramaki (NAIST), Akiyo Nadamoto (Konan Univ.), Mai Miyabe (Wakayama Univ.) TL2016-11 NLC2016-11 |
Nowadays, the restaurant search services on the Internet become popular, people use them when they search the new restau... [more] | TL2016-11 NLC2016-11 pp.53-58 |
| NS, IN (Joint) |
2016-03-04 14:10 |
Miyazaki | Phoenix Seagaia Resort | A Privacy Preserving Recommendation System by Service Providers Coordination and Integration of User Action History Masashi Arashida, Katsunori Oyama, Toshihiro Nishizono (Nihon Univ) IN2015-146 |
This paper proposes a privacy preserving recommendation system which integrates user action history held by multiple ser... [more] | IN2015-146 pp.223-228 |
| SC | 2016-01-15 15:45 |
Kyoto | Kyoto University (Design Innovation Center) | Multi-stage Collaborative Filtering for Composite Service Recommendation Taketo Sasaki, Yohei Murakami, Toru Ishida (Kyoto Univ.) SC2015-21 |
There have been attempts to apply collaborative filtering to service recommendation. Most all of them are for atomic ser... [more] | SC2015-21 pp.37-42 |
| KBSE | 2015-09-24 14:35 |
Osaka | Bldg.A No.110, IST, Suita campus, Osaka University | A Research on similarity between Railway Stations Tomomi Sanjo (NEXT Col., Ltd.), Akito Sakurai (Keio University) KBSE2015-30 |
Recently, real estate portal sites provide recommendation services. The most effective one is thought to be recommendati... [more] | KBSE2015-30 pp.13-17 |
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