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Deep learning based feature extraction and a bidirectional hybrid optimized model for location based advertising

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Abstract

The Location based advertising (LBA) is a new and commercial scheme for advertisers to get the information via personalized texts which is sent openly to mobile phones by their geographic location. Because of the enhanced interaction with the marketer and the user, there is an increasing challenge about privacy among the concerns of mobile users and personalization. This paper presents a deep learning based bidirectional hybrid optimized model for LBA. Initially, the location data is attained by the Geographical Information System (GIS) for receiving the accurate information about the location. The input collected location information is send to the word embedding approach. This generates a vector associated with each word and it creates a matrix. Afterwards, the features are extracted using deep sparse auto encoder (DSAE) approach. Finally, Bidirectional optimized hybrid model i.e. Bidirectional Long-Short Term Memory-Deep Neural Network and Adaptive Sunflower Optimization Algorithm (BLSTM-DNN-ASOA) is used for the better classification. In order to effectively provide the location based services, a hybrid model named BLSTM-DNN is utilized and the optimal solution is obtained by the proposed ASOA algorithm. The proposed LBA with GIS is simulated in JAVA platform. The performance of the proposed algorithm is assessed depends on the metrics named as Accuracy (98.97%), Precision (99.7%), F-measure (99.48%), computational time (99.8 ms), Area under the curve (AUC) (82.23%) and Recall (99.52%) in terms of different number of documents. The simulation result of the proposed algorithm provides better performance in LBA than the existing approaches.

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Authors and Affiliations

  1. Department of Computer Science & Engineering, Maharaja Surajmal Institute of Technology, Janakpuri, New Delhi, 110058, India

    Vinita Rohilla

  2. Department of Computer Science and Engineering, School of Engineering and Technology, Sharda University, Greater Noida, Uttar Pradesh, 201306, India

    Sudeshna Chakraborty

  3. Department of Computer Science and Engineering, G.L. Bajaj Institute of Technology and Management, Greater Noida, Uttar Pradesh, 201306, India

    Rajiv Kumar

Authors
  1. Vinita Rohilla
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  2. Sudeshna Chakraborty
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  3. Rajiv Kumar
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Correspondence to Vinita Rohilla.

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Rohilla, V., Chakraborty, S. & Kumar, R. Deep learning based feature extraction and a bidirectional hybrid optimized model for location based advertising. Multimed Tools Appl 81, 16067–16095 (2022). https://doi.org/10.1007/s11042-022-12457-3

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  • DOI: https://doi.org/10.1007/s11042-022-12457-3

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