| Presentation | 2012-06-21 A Study on Generating Rules in a Situational Aware Smart Room Yu-Cheng Lin, Rung-Ching Chen, Qiangfu Zhao, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | 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 rales to solve their problems. Therefore, how to build the ontology model and generate the rales 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 rale base. But existing method for generating the rales are still not efficient enough. The purpose of this paper is to study and provide a more efficient method for generating rales 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 rales 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 rales and resolve the conflicts between rales. We can define some special rales and control the service according to the priority of rales (e.g. energy saving rale). However, since each environment can be different from others, the rales 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. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | Context-aware service / ontology / reasoning engine / C4.5 |
| Paper # | AI2012-2 |
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| Conference Information | |
| Committee | AI |
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| Conference Date | 2012/6/14(1days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
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| Paper Information | |
| Registration To | Artificial Intelligence and Knowledge-Based Processing (AI) |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study on Generating Rules in a Situational Aware Smart Room |
| Sub Title (in English) | |
| Keyword(1) | Context-aware service |
| Keyword(2) | ontology |
| Keyword(3) | reasoning engine |
| Keyword(4) | C4.5 |
| 1st Author's Name | Yu-Cheng Lin |
| 1st Author's Affiliation | University of Aizu() |
| 2nd Author's Name | Rung-Ching Chen |
| 2nd Author's Affiliation | Chaoyang University of Technology |
| 3rd Author's Name | Qiangfu Zhao |
| 3rd Author's Affiliation | University of Aizu |
| Date | 2012-06-21 |
| Paper # | AI2012-2 |
| Volume (vol) | vol.112 |
| Number (no) | 94 |
| Page | pp.pp.- |
| #Pages | 6 |
| Date of Issue | |