Yongliang Sun

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As a fingerprint match method, k-nearest neighbors (KNN) has been widely applied for indoor location in Wireless Local Area Networks (WLAN), but its performance is sensitive to number of neighbors k and positions of reference points (RPs). So fuzzy c-means (FCM) clustering algorithm is applied to improve KNN, which is the KNN-FCM hybrid algorithm presented(More)
A Kalman/map filtering (KMF)-aided fast normalized cross correlation (FNCC)-based Wi-Fi fingerprinting location sensing system is proposed in this paper. Compared with conventional neighbor selection algorithms that calculate localization results with received signal strength (RSS) mean samples, the proposed FNCC algorithm makes use of all the on-line RSS(More)
This paper describes an improved method for relation identification, which is the last step of unsupervised relation extraction. Similar entity pairs maybe grouped into the same cluster. It is also important to select a key word to describe the relation accurately. Therefore, an improved DF feature selection method is employed to rearrange low-frequency(More)
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