PARE: Profile-Applied Reasoning Engine for Context-Aware System
Context reasoning is an important issue for a context-aware system. Generally, context reasoning is adopted to deduce new context based on the available contexts. The rule-based reasoning is one of the most well-known methods for context reasoning. However, it is difficult for the rule-based algorit...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2016-07-01
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| Series: | International Journal of Distributed Sensor Networks |
| Online Access: | https://doi.org/10.1177/155014775389091 |
| _version_ | 1826826050433187840 |
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| author | M. Robiul Hoque M. Humayun Kabir Hyungyu Seo Sung-Hyun Yang |
| author_facet | M. Robiul Hoque M. Humayun Kabir Hyungyu Seo Sung-Hyun Yang |
| author_sort | M. Robiul Hoque |
| collection | DOAJ |
| description | Context reasoning is an important issue for a context-aware system. Generally, context reasoning is adopted to deduce new context based on the available contexts. The rule-based reasoning is one of the most well-known methods for context reasoning. However, it is difficult for the rule-based algorithm to reason personalized context, because it requires a large number of rules to apply the user's preferences. To address this weakness, in this paper we suggest the Profile-Applied Reasoning Engine (PARE). PARE is an enhanced rule-based reasoning method which uses profiles while reasoning contexts. By using profiles, PARE can become aware of the context that is preferred by a specific individual. To validate the effectiveness of the proposed reasoning engine, we compared the reasoning result of PARE with traditional rule-based reasoning in smart home domain. PARE shows better outcome for reasoning the personalized contexts than the traditional rule-based reasoning. In addition, by using profiles, a significant number of rules have been omitted and consequently the running time is also decreased. Moreover, PARE occupies less memory space which is restricted with number of variables of a rule. Therefore, PARE optimizes both runtime and memory space, which is valuable when making embedded context-aware system. |
| first_indexed | 2024-03-12T06:05:19Z |
| format | Article |
| id | doaj.art-f9a646c1420d407c8e59069a1835142d |
| institution | Directory Open Access Journal |
| issn | 1550-1477 |
| language | English |
| last_indexed | 2025-02-16T08:05:16Z |
| publishDate | 2016-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Distributed Sensor Networks |
| spelling | doaj.art-f9a646c1420d407c8e59069a1835142d2025-02-03T05:55:24ZengWileyInternational Journal of Distributed Sensor Networks1550-14772016-07-011210.1177/155014775389091PARE: Profile-Applied Reasoning Engine for Context-Aware SystemM. Robiul Hoque0M. Humayun Kabir1Hyungyu Seo2Sung-Hyun Yang3Department of Electronic Engineering, Kwangwoon University, 447-1 Wolgye-dong, Nowon-gu, Seoul 139-701, Republic of KoreaDepartment of Electronic Engineering, Kwangwoon University, 447-1 Wolgye-dong, Nowon-gu, Seoul 139-701, Republic of KoreaDepartment of Electronic Engineering, Kwangwoon University, 447-1 Wolgye-dong, Nowon-gu, Seoul 139-701, Republic of KoreaDepartment of Electronic Engineering, Kwangwoon University, 447-1 Wolgye-dong, Nowon-gu, Seoul 139-701, Republic of KoreaContext reasoning is an important issue for a context-aware system. Generally, context reasoning is adopted to deduce new context based on the available contexts. The rule-based reasoning is one of the most well-known methods for context reasoning. However, it is difficult for the rule-based algorithm to reason personalized context, because it requires a large number of rules to apply the user's preferences. To address this weakness, in this paper we suggest the Profile-Applied Reasoning Engine (PARE). PARE is an enhanced rule-based reasoning method which uses profiles while reasoning contexts. By using profiles, PARE can become aware of the context that is preferred by a specific individual. To validate the effectiveness of the proposed reasoning engine, we compared the reasoning result of PARE with traditional rule-based reasoning in smart home domain. PARE shows better outcome for reasoning the personalized contexts than the traditional rule-based reasoning. In addition, by using profiles, a significant number of rules have been omitted and consequently the running time is also decreased. Moreover, PARE occupies less memory space which is restricted with number of variables of a rule. Therefore, PARE optimizes both runtime and memory space, which is valuable when making embedded context-aware system.https://doi.org/10.1177/155014775389091 |
| spellingShingle | M. Robiul Hoque M. Humayun Kabir Hyungyu Seo Sung-Hyun Yang PARE: Profile-Applied Reasoning Engine for Context-Aware System International Journal of Distributed Sensor Networks |
| title | PARE: Profile-Applied Reasoning Engine for Context-Aware System |
| title_full | PARE: Profile-Applied Reasoning Engine for Context-Aware System |
| title_fullStr | PARE: Profile-Applied Reasoning Engine for Context-Aware System |
| title_full_unstemmed | PARE: Profile-Applied Reasoning Engine for Context-Aware System |
| title_short | PARE: Profile-Applied Reasoning Engine for Context-Aware System |
| title_sort | pare profile applied reasoning engine for context aware system |
| url | https://doi.org/10.1177/155014775389091 |
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