Chinese Location Word Recognition Using Service Context Information for Location-Based Service

Abstract

With the development of mobile networks and positioning technology, extensive attention focuses on the location-based service (LBS) which processes the application data including user queries, information searches, and user comments by the location information. In LBS, the recognition of the location word in user messages is meaningful and important. The location word recognition in LBS is different from the traditional named entity recognition, owing to the additional information such as user location coordinates in LBS. This paper proposes a method that adds the service context information including user location coordinates and message timestamps into the machine learning to improve the accuracy of the Chinese location word recognition. The experiment based on microblog datasets in mobile environment proves the viability and effectiveness of this method.

An Adaptive Location-Based Tracking Algorithm Using Wireless Sensor Network for Smart Factory Environment

“…where x is the input of A, and A i is the i th semantic tag for input A. μ Ai (x) is the membership function (MF) for the i th semantic tag of input A. e bell-shaped distribution is the most frequently used MF that has values within the range of 0 to 1, as shown in (11):…”

“…All of these techniques involve transmitting radio wave signals to establish a wireless sensor network for positioning. However, during the transmission process, signals may be influenced by the multipath effect; therefore, information received by the reader may be distorted, influencing the accuracy and stability of localization [9][10][11].…”