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IAES International Journal of Artificial Intelligence (IJ-AI)
Published by Institute of Advanced Engineering and Science
ISSN : 20894872     EISSN : 22528938     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Engineering
IAES International Journal of Artificial Intelligence (IJ-AI) publishes articles in the field of artificial intelligence (AI). The scope covers all artificial intelligence area and its application in the following topics: neural networks; fuzzy logic; simulated biological evolution algorithms (like genetic algorithm, ant colony optimization, etc); reasoning and evolution; intelligence applications; computer vision and speech understanding; multimedia and cognitive informatics, data mining and machine learning tools, heuristic and AI planning strategies and tools, computational theories of learning; technology and computing (like particle swarm optimization); intelligent system architectures; knowledge representation; bioinformatics; natural language processing; multiagent systems; etc.
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Articles 31 Documents
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Search results for , issue "Vol 10, No 4: December 2021" : 31 Documents clear
A prediction model for benefitting e-commerce through usage of regional data: A new framework Shefali Singhal; Poonam Tanwar
IAES International Journal of Artificial Intelligence (IJ-AI) Vol 10, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijai.v10.i4.pp1009-1018

Abstract

Today during ‘Covid-20’, people are more inclined towards online shopping. In general practice, analysis of browsing history and customer’s micro behaviour against online shopping habits have been used for future suggestions. Due to this, the predictions made were suffereing from over-similarity problem and the user was unable to find any novelty in the recommended items. Observing these issues, e-shopping quality can be enhanced by adding a factor other than similarity. The current research suggests and advertise those products which belongs to a person’s region. For this research work the data has been collected on the basis of area-wise, like, country-based seggregation. Here the considered dataset belongs to country, ‘India’, its culture, its handicraft and its citizens. Datasets and their combinations based on multiple attributes are input for the proposed predictive system. In this paper, existing data is also considered for collecting customers demographic details which is further mapped with the area-wise dataset. Also, a framework has been proposed which uses database and user query as input for its predictive system in order to generate default suggestions for the user other than the submitted query also.

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