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| 講演名 | 2012-06-21 14:00 A Study on Generating Rules in a Situational Aware Smart Room ○Yu-Cheng Lin（Univ. of Aizu）・Rung-Ching Chen（Chao-Yang Univ. of Tech.）・Qiangfu Zhao（Univ. of Aizu）  AI2012-2 |
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| 抄録 | （和） | Ontology is a semantic technology. It can be used to describe knowledge and resources. In recent years, ontology-based systems are becoming very popular. They have been used in different domains (e.g., medication and mobile computing). An ontology-based system consists of an ontology model, an inference engine, and a rule base. In this architecture, users can easily use their ontology models and rules to solve their problems. Therefore, how to build the ontology model and generate the rules are very important. In context-awareness domain, several ontology models and systems have been proposed. These systems can automatically execute or change services based on the ontology model and the rule base. But existing method for generating the rules are still not efficient enough. The purpose of this paper is to study and provide a more efficient method for generating rules using basic context information. The basic context information includes four kinds of data, namely identifier, time, activity and location. In this paper, we investigate a basic method containing four steps. First, we define situation of the service (e.g. turn-on or turn-off the light). Second, we define the relationship between the situation and basic context information (e.g. the situation "user is in the room and time is evening" is related to the service "turn-on the light"). Third, we generate rules according to the relation found in the second step (e.g. if user is at room and time is evening, then turn-on the light). Fourth, we define priority of rules and resolve the conflicts between rules. We can define some special rules and control the service according to the priority of rules (e.g. energy saving rule). However, since each environment can be different from others, the rules should be adjusted according to the specific environment. If we can obtain other information, then we will add the information in basic context information and repeat step 2 to 4. Simulation results will be provided in the paper to show the efficiency of the above method. |
| （英） | Ontology is a semantic technology. It can be used to describe knowledge and resources. In recent years, ontology-based systems are becoming very popular. They have been used in different domains (e.g., medication and mobile computing). An ontology-based system consists of an ontology model, an inference engine, and a rule base. In this architecture, users can easily use their ontology models and rules to solve their problems. Therefore, how to build the ontology model and generate the rules are very important. In context-awareness domain, several ontology models and systems have been proposed. These systems can automatically execute or change services based on the ontology model and the rule base. But existing method for generating the rules are still not efficient enough. The purpose of this paper is to study and provide a more efficient method for generating rules using basic context information. The basic context information includes four kinds of data, namely identifier, time, activity and location. In this paper, we investigate a basic method containing four steps. First, we define situation of the service (e.g. turn-on or turn-off the light). Second, we define the relationship between the situation and basic context information (e.g. the situation "user is in the room and time is evening" is related to the service "turn-on the light"). Third, we generate rules according to the relation found in the second step (e.g. if user is at room and time is evening, then turn-on the light). Fourth, we define priority of rules and resolve the conflicts between rules. We can define some special rules and control the service according to the priority of rules (e.g. energy saving rule). However, since each environment can be different from others, the rules should be adjusted according to the specific environment. If we can obtain other information, then we will add the information in basic context information and repeat step 2 to 4. Simulation results will be provided in the paper to show the efficiency of the above method. | |
| キーワード | （和） | Context-aware service / ontology / reasoning engine / C4.5 / / / / |
| （英） | Context-aware service / ontology / reasoning engine / C4.5 / / / / | |
| 文献情報 | 信学技報, vol. 112, no. 94, AI2012-2, pp. 7-12, 2012年6月. | |
| 資料番号 | AI2012-2 | |
| 発行日 | 2012-06-14 (AI) | |
| ISSN | Print edition: ISSN 0913-5685 Online edition: ISSN 2432-6380 | |
| 著作権に ついて |
技術研究報告に掲載された論文の著作権は電子情報通信学会に帰属します．(許諾番号：10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) | |
| PDFダウンロード | AI2012-2 |
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| 研究会情報 | |
| 研究会 | AI |
| 開催期間 | 2012-06-21 - 2012-06-21 |
| 開催地（和） | 京都大学 東京オフィス |
| 開催地（英） | |
| テーマ（和） | 「Webインテリジェンス」および一般 |
| テーマ（英） | Web Intelligence |
| 講演論文情報の詳細 | |
| 申込み研究会 | AI |
| 会議コード | 2012-06-AI |
| 本文の言語 | 英語 |
| タイトル（和） | |
| サブタイトル（和） | |
| タイトル（英） | A Study on Generating Rules in a Situational Aware Smart Room |
| サブタイトル（英） | |
| キーワード(1)（和/英） | Context-aware service / Context-aware service |
| キーワード(2)（和/英） | ontology / ontology |
| キーワード(3)（和/英） | reasoning engine / reasoning engine |
| キーワード(4)（和/英） | C4.5 / C4.5 |
| キーワード(5)（和/英） | / |
| キーワード(6)（和/英） | / |
| キーワード(7)（和/英） | / |
| キーワード(8)（和/英） | / |
| 第1著者 氏名（和/英/ヨミ） | Yu-Cheng Lin / Yu-Cheng Lin / |
| 第1著者 所属（和/英） | The University of Aizu (略称： 会津大) The University of Aizu (略称： Univ. of Aizu) |
| 第2著者 氏名（和/英/ヨミ） | Rung-Ching Chen / Rung-Ching Chen / |
| 第2著者 所属（和/英） | Chao-Yang University of Technology (略称： Chao-Yang Univ. of Tech.) Chao-Yang University of Technology (略称： Chao-Yang Univ. of Tech.) |
| 第3著者 氏名（和/英/ヨミ） | Qiangfu Zhao / Qiangfu Zhao / |
| 第3著者 所属（和/英） | The University of Aizu (略称： 会津大) The University of Aizu (略称： Univ. of Aizu) |
| 講演者 | 第1著者 |
| 発表日時 | 2012-06-21 14:00:00 |
| 発表時間 | 30分 |
| 申込先研究会 | AI |
| 資料番号 | AI2012-2 |
| 巻番号（vol） | vol.112 |
| 号番号（no） | no.94 |
| ページ範囲 | pp.7-12 |
| ページ数 | 6 |
| 発行日 | 2012-06-14 (AI) |
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