物聯(lián)網(wǎng)中適用于內(nèi)容搜索的實(shí)體狀態(tài)匹配預(yù)測方法
doi: 10.11999/JEIT150191 cstr: 32379.14.JEIT150191
基金項(xiàng)目:
國家自然科學(xué)基金(61170275)，國家863計(jì)劃項(xiàng)目，民用航天十二五預(yù)研科技項(xiàng)目，北京市高等學(xué)校青年英才計(jì)劃項(xiàng)目和安全生產(chǎn)智能監(jiān)控北京市重點(diǎn)實(shí)驗(yàn)室基金
An Entity State Matching Prediction Method for Content-basedSearch in the Internet of Things
Funds:
The National Natural Science Foundation of China (61170275)
-
摘要: 對(duì)實(shí)體匹配用戶內(nèi)容搜索的狀態(tài)進(jìn)行預(yù)測可顯著提高物聯(lián)網(wǎng)搜索的效率，降低搜索過程的通信開銷。該文提出等時(shí)距與周期內(nèi)實(shí)體狀態(tài)預(yù)測方法，估計(jì)實(shí)體在用戶查詢時(shí)刻的狀態(tài)；設(shè)計(jì)了適用于內(nèi)容搜索的有序驗(yàn)證方法，依據(jù)實(shí)體匹配用戶查詢內(nèi)容的概率對(duì)實(shí)體進(jìn)行排序驗(yàn)證，以保證用戶搜索結(jié)果的可靠性。結(jié)果表明，所提實(shí)體狀態(tài)預(yù)測方法具有較高的精度，結(jié)合所提預(yù)測方法與匹配驗(yàn)證方法的搜索機(jī)制具有較低的通信開銷。
-
關(guān)鍵詞:
- 物聯(lián)網(wǎng) /
- 內(nèi)容搜索 /
- 狀態(tài)預(yù)測 /
- 匹配驗(yàn)證
Abstract: Matching prediction with high accuracy of entity state can cansignificantly improve the efficiency of content-based search in the Internet of Things and reduce communication overhead while searching. The equal-interval and during the period entity state prediction methods are proposed, which are applied to the estimation of the entity state at the moment of querying. Moreover, the ordered verification approach is designed to verify the entities in sequence based on the degree of compliance with the searching content, for the sake of enhancing the reliability of searching results. Numerical results show that the proposed entity state prediction approachescan achieve high accuracy, which combines with the ordered verification approach to dramatically improve the performance of communication overheadduring the searching process.-
Key words:
- Internet of Things /
- Content-based search /
- State prediction /
- Matching verification
-
于海寧, 余翔湛. 物聯(lián)網(wǎng)中基于編碼的多路徑并發(fā)實(shí)體通用搜索算法[J]. 智能計(jì)算機(jī)與應(yīng)用, 2013, 3(2): 25-31. Yu Hai-ning and Yu Xiang-zhan. A multi-path concurrency object universal search (MCOUS) algorithms based on code in internet of things[J]. Intelligent Computerand Applications, 2013, 3(2): 25-31. 茹立云, 李智超, 馬少平. 搜索引擎索引網(wǎng)頁集合選取方法研究[J]. 計(jì)算機(jī)研究與發(fā)展, 2014, 51(10): 2239-2247. Ru Li-yun, Li Zhi-chao, and Ma Shao-ping. Indexing page collection selection method for search engine[J]. Journal of Computer Research and Development, 2014, 51(10): 2239-2247. 李養(yǎng)群, 沈蘇彬, 許斌. 物品萬維網(wǎng)技術(shù)綜述[J].南京郵電大學(xué)學(xué)報(bào)(自然科學(xué)版), 2014, 34(2): 32-42. Li Yang-qun, Shen Su-bin, and Xu Bin. Technology of web of things: asurvey[J]. Journal of Nanjing University of Posts and Telecommunications (Natural Science), 2014, 34(2): 32-42. 于海寧, 張宏莉, 方濱興, 等. 物聯(lián)網(wǎng)中物理實(shí)體搜索服務(wù)的研究[J]. 電信科學(xué), 2012, 28(10): 111-119. Yu Hai-ning, Zhang Hong-li, Fang Bin-xing, et al.. Research on search service for physical entities in the internet of things[J]. Telecommunications Science, 2012, 28(10): 111-119. Benedikt O, Kay R, Friedemann M, et al.. A real-time search engine for the web of things[C]. Internet of Things, Tokyo, 2010: 1-8. Cuong T and Kay R. Content-based sensor search for the web of things[C]. Global Communications Conference, Atlanta, 2013: 2654-2660. 唐舟進(jìn), 彭濤, 王文博. 一種基于相關(guān)分析的局域最小二乘支持向量機(jī)小尺度網(wǎng)絡(luò)流量預(yù)測算法[J]. 物理學(xué)報(bào), 2014, 63(13): 57-66. Tang Zhou-jin, Peng Tao, and Wang Wen-bo. A local least square support vector machine prediction algorithm of small scale network traffic based on correlation analysis[J]. Acta Physica Sinica, 2014, 63(13): 57-66. 李增科, 高井祥, 王堅(jiān), 等. 利用牛頓插值的GPS/INS組合導(dǎo)航慣性動(dòng)力學(xué)模型[J]. 武漢大學(xué)學(xué)報(bào)(信息科學(xué)版), 2014, 39(5): 591-595. Li Zeng-ke, Gao Jing-xiang, Wang Jian, et al.. Inerialdynamic model of GPS/INS integrated navigation based on newton interpolaion[J]. Geomatics and Information Science of Wuhan University, 2014, 39(5): 591-595. 尚軍亮, 方敏. 一種優(yōu)化的高精度灰色GM(1,1)預(yù)測模型[J]. 電子與信息學(xué)報(bào), 2010, 32(6): 1301-1305. Shang Jun-liang and Fang Min. New optimized method of high-precision grey GM(1,1) forecasting model[J]. Journal of Electronics Information Technology, 2010, 32(6): 1301-1305. -
計(jì)量
- 文章訪問數(shù): 1415
- HTML全文瀏覽量: 183
- PDF下載量: 578
- 被引次數(shù): 0
下載:
