An Enhancement on Mobile Social Network using Social Link Prediction with Improved Human Trajectory Internet Data Mining
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2019, Vol 10, Issue 3
Abstract
Generally, the mobile social network has missing and unauthentic links. The prediction of those links is one of the major problems to understand the relationship between two nodes and recommends the potential links to the users derived from the history of user-link interactions and their contextual information. The recommendation problem can be modeled as prediction of the future links between users. Many research works have been developed to understand the relationship between the nodes and construct the models for missing or suspicious links prediction. Among those, Improved Multi-Context Trajectory Embedding Model with Service Usage Classification Model (IMC-TEM-SUCM) has better enhancement on human trajectory data mining by classifying the internet traffic. However, this method requires the prediction of the relationship between the nodes and social links. Hence in this article, the IMC-TEM-SUCM is proposed with the Social Link Prediction (SLP) mechanism for identifying the relationship between two nodes and predicting the stable links. In this technique, a number of nodal features are considered and their influence on the link prediction problem of Foursquare and Gowalla are examined. This extended network is used for computing two features such as optimism and reputation that depict node’s characteristics in a signed network. After that, meta-path-based features are considered and their influence of the route length on the problem of link prediction is examined. Moreover, a link prediction process is performed by using the machine learning classification algorithms that use the extracted node-based and meta-path-based features. Also, Cosine coefficient and Jaccard coefficient similarity-based techniques are used for computing the similarity index between any two nodes. A higher similarity indicates a higher chance of forming links between them. Finally, the performance effectiveness of the proposed model is evaluated through the experimental results using different real-world datasets.
Authors and Affiliations
B. Suryakumar, Dr. E. Ramadevi
Keywords
Related Articles
- EP ID EP498429
- DOI 10.14569/IJACSA.2019.0100318
- Views 65
- Downloads 0
Computer Science Approach to Information-Like Artifacts as Exemplified by Memes
Providing information can be expanded to include systems that deliver information-like artifacts. They provide such “things” as advertisements, propaganda pieces, and meme artifacts. Memes are the subject of extensive in...
Evaluation of the Segmentation by Multispectral Fusion Approach with Adaptive Operators : Application to Medical Images
With the development of acquisition image techniques, more and more image data from different sources of image become available. Multi-modality image fusion seeks to combine information from different images to obtain mo...
A New Steganography Technique using JPEG Images
Steganography is a form of security technique that using ambiguity to hide a secret message within an ordinary message between senders and receivers. In this paper, we propose a new steganography technique for hiding dat...
Multi-Criteria Wind Turbine Selection using Weighted Sum Approach
Wind energy is becoming a potential source for renewable and clean energy. An important factor that contributes to efficient generation of wind power is the use of appropriate wind turbine. However, the task of selecting...
Map Reduce: A Survey Paper on Recent Expansion
A rapid growth of data in recent time, Industries and academia required an intelligent data analysis tool that would be helpful to satisfy the need to analysis a huge amount of data. MapReduce framework is basically desi...