IEICE TRANSACTIONS on Information
Songrium Derivation Factor Analysis: A Web Service for Browsing Derivation Factors by Modeling N-th Order Derivative Creation
Summary :
Creating new content based on existing original work is becoming popular especially among amateur creators. Such new content is called derivative work and can be transformed into the next new derivative work. Such derivative work creation is called “N-th order derivative creation.” Although derivative creation is popular, the reason an individual derivative work was created is not observable. To infer the factors that trigger derivative work creation, we have proposed a model that incorporates three factors: (1) original work's attractiveness, (2) original work's popularity, and (3) derivative work's popularity. Based on this model, in this paper, we describe a public web service for browsing derivation factors called Songrium Derivation Factor Analysis. Our service is implemented by applying our model to original works and derivative works uploaded to a video sharing service. Songrium Derivation Factor Analysis provides various visualization functions: Original Works Map, Derivation Tree, Popularity Influence Transition Graph, Creator Distribution Map, and Creator Profile. By displaying such information when users browse and watch videos, we aim to enable them to find new content and understand the N-th order derivative creation activity at a deeper level.
- Publication
- IEICE TRANSACTIONS on Information Vol.E101-D No.4 pp.1096-1106
- Publication Date
- 2018/04/01
- Publicized
- 2018/01/18
- Online ISSN
- 1745-1361
- DOI
- 10.1587/transinf.2017DAT0001
- Type of Manuscript
- Special Section PAPER (Special Section on Data Engineering and Information Management)
- Category
Authors
Kosetsu TSUKUDA
National Institute of Advanced Industrial Science and Technology (AIST)
Keisuke ISHIDA
National Institute of Advanced Industrial Science and Technology (AIST)
Masahiro HAMASAKI
National Institute of Advanced Industrial Science and Technology (AIST)
Masataka GOTO
National Institute of Advanced Industrial Science and Technology (AIST)
Keyword
Latest Issue
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Kosetsu TSUKUDA, Keisuke ISHIDA, Masahiro HAMASAKI, Masataka GOTO, "Songrium Derivation Factor Analysis: A Web Service for Browsing Derivation Factors by Modeling N-th Order Derivative Creation" in IEICE TRANSACTIONS on Information,
vol. E101-D, no. 4, pp. 1096-1106, April 2018, doi: 10.1587/transinf.2017DAT0001.
Abstract: Creating new content based on existing original work is becoming popular especially among amateur creators. Such new content is called derivative work and can be transformed into the next new derivative work. Such derivative work creation is called “N-th order derivative creation.” Although derivative creation is popular, the reason an individual derivative work was created is not observable. To infer the factors that trigger derivative work creation, we have proposed a model that incorporates three factors: (1) original work's attractiveness, (2) original work's popularity, and (3) derivative work's popularity. Based on this model, in this paper, we describe a public web service for browsing derivation factors called Songrium Derivation Factor Analysis. Our service is implemented by applying our model to original works and derivative works uploaded to a video sharing service. Songrium Derivation Factor Analysis provides various visualization functions: Original Works Map, Derivation Tree, Popularity Influence Transition Graph, Creator Distribution Map, and Creator Profile. By displaying such information when users browse and watch videos, we aim to enable them to find new content and understand the N-th order derivative creation activity at a deeper level.
URL: https://global.ieice.org/en_transactions/information/10.1587/transinf.2017DAT0001/_p
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@ARTICLE{e101-d_4_1096,
author={Kosetsu TSUKUDA, Keisuke ISHIDA, Masahiro HAMASAKI, Masataka GOTO, },
journal={IEICE TRANSACTIONS on Information},
title={Songrium Derivation Factor Analysis: A Web Service for Browsing Derivation Factors by Modeling N-th Order Derivative Creation},
year={2018},
volume={E101-D},
number={4},
pages={1096-1106},
abstract={Creating new content based on existing original work is becoming popular especially among amateur creators. Such new content is called derivative work and can be transformed into the next new derivative work. Such derivative work creation is called “N-th order derivative creation.” Although derivative creation is popular, the reason an individual derivative work was created is not observable. To infer the factors that trigger derivative work creation, we have proposed a model that incorporates three factors: (1) original work's attractiveness, (2) original work's popularity, and (3) derivative work's popularity. Based on this model, in this paper, we describe a public web service for browsing derivation factors called Songrium Derivation Factor Analysis. Our service is implemented by applying our model to original works and derivative works uploaded to a video sharing service. Songrium Derivation Factor Analysis provides various visualization functions: Original Works Map, Derivation Tree, Popularity Influence Transition Graph, Creator Distribution Map, and Creator Profile. By displaying such information when users browse and watch videos, we aim to enable them to find new content and understand the N-th order derivative creation activity at a deeper level.},
keywords={},
doi={10.1587/transinf.2017DAT0001},
ISSN={1745-1361},
month={April},}
Copy
TY - JOUR
TI - Songrium Derivation Factor Analysis: A Web Service for Browsing Derivation Factors by Modeling N-th Order Derivative Creation
T2 - IEICE TRANSACTIONS on Information
SP - 1096
EP - 1106
AU - Kosetsu TSUKUDA
AU - Keisuke ISHIDA
AU - Masahiro HAMASAKI
AU - Masataka GOTO
PY - 2018
DO - 10.1587/transinf.2017DAT0001
JO - IEICE TRANSACTIONS on Information
SN - 1745-1361
VL - E101-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 2018
AB - Creating new content based on existing original work is becoming popular especially among amateur creators. Such new content is called derivative work and can be transformed into the next new derivative work. Such derivative work creation is called “N-th order derivative creation.” Although derivative creation is popular, the reason an individual derivative work was created is not observable. To infer the factors that trigger derivative work creation, we have proposed a model that incorporates three factors: (1) original work's attractiveness, (2) original work's popularity, and (3) derivative work's popularity. Based on this model, in this paper, we describe a public web service for browsing derivation factors called Songrium Derivation Factor Analysis. Our service is implemented by applying our model to original works and derivative works uploaded to a video sharing service. Songrium Derivation Factor Analysis provides various visualization functions: Original Works Map, Derivation Tree, Popularity Influence Transition Graph, Creator Distribution Map, and Creator Profile. By displaying such information when users browse and watch videos, we aim to enable them to find new content and understand the N-th order derivative creation activity at a deeper level.
ER -
English
