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AN IMPROVED hybrid SEMANTIC matching algorithm WITH LEXICAL SIMILARITY

Journal of Electronics(China) 2010年第6期27卷 838-847页

作者： Peng Rongqun Mi Zhengkun Wang Lingjiao Broadband Wireless Communication and Sensor Network Technology Key Lab of Ministry of Education Nanjing University of Posts and Telecommunications Nanjing 210003 China

In this paper, we proposed an improved hybrid semantic matching algorithm combining Input/Output (I/O) semantic matching with text lexical similarity to overcome the disadvantage that the existing semantic matching algorithms were unable to distinguish those services with the same I/O by only performing I/O based service signature matching in semantic web service discovery techniques. The improved algorithm consists of two steps, the first is logic based I/O concept ontology matching, through which the candidate service set is obtained and the second is the service name matching with lexical similarity against the candidate service set, through which the final precise matching result is concluded. Using Ontology Web Language for Services (OWL-S) test collection, we tested our hybrid algorithm and compared it with OWL-S Matchmaker-X (OWLS-MX), the experimental results have shown that the proposed algorithm could pick out the most suitable advertised service corresponding to user's request from very similar ones and provide better matching precision and efficiency than OWLS-MX.

关键词： hybrid matching algorithm Semantic matching Lexical similarity WordNet Ontology Web Language for Services (OWL-S)

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Forward matching Fusion algorithm for PDR based on Geomagnetic Fingerprint Map 22

Forward Matching Fusion Algorithm for PDR based on Geomagnet...

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22nd International Conference on Control, Automation and Systems (ICCAS)

作者： Li, Yuke Wang, Pengju Li, Tong Liu, Yinxuan Tateno, Shigeyuki WASEDA Univ Grad Sch Informat Prod & Syst Kitakyushu Fukuoka Japan

ISBN: (纸本)9788993215243

Aiming at the problem that indoor positioning using pedestrian dead reckoning (PDR) algorithm will lead to error accumulation and the precision of built-in sensors of smartphones is not high enough, indoor positioning research based on the fusion of geomagnetic positioning and PDR positioning algorithm is proposed. A Kriging interpolation based fusion matching algorithm was used to construct geomagnetic fingerprint map to reduce the time spent in data sampling. The fusion positioning is realized by combining the PDR positioning with the hybrid matching algorithm of lattice matching and sequence matching. The improved algorithm solves the problems of global search for geomagnetic sequence matching and PDR positioning error accumulation in traditional methods, improves the positioning accuracy and solves the problems that through the wall or even out of the map caused by the error accumulation. Experimental results show that the maximum positioning error of the proposed algorithm is less than 1m in the complex movement of 120 steps for 60m. The probability of positioning accuracy less than 0.5m is 85%. This can meet the needs of ordinary indoor positioning.

关键词： indoor positioning pedestrian dead reckoning (PDR) geomagnetic fingerprint map hybrid matching algorithm

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