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A novel multi agent recommender system for user interests extraction

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Abstract

In this paper, a multi agent recommender system is designed and developed for user interests extraction The system consists of eight agents such as age, identity, personality, social, financial, location, and needs. The agents works with each others in a collaborative way to make recommendation to the users according to their interest. The relation between the agents and the users are controlled by a well developed protocol and pre-defined senses. The information between the users and the agents are collected in information center agent (ICA). The data collected in ICA can be used to rearrange the videos in way such that it is more relative to the user depending on his interest. This interest can be extracted from the information that the user initially provides to the system which can be then analyzed from the multi agent system to decide whether the user is interested in a video or not. This is done by creating video -important term matrix, user important term matrix and agent -feature matrix. Then, theses matrices are used by the multi-agent system to get video-Agent effective matrix for the users which leads to most ordered videos in order to be presented to the user. The proposed model was verified by intensive simulations using eight agents using JADE platform. The results show that the accuracy of the system for 50 videos that were well arranged for 40 users is 87%.

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The data that support the findings of this study are available from the corresponding author.

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Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

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Authors and Affiliations

  1. Department of Computer and Communications Engineering, College of Engineering, Tafila Technical University, Tafila, 66110, Jordan

    Ayman M. Mansour

  2. Department of Electrical Engineering, College of Engineering, Al-Ahliyya Amman University, Amman, Jordan

    Mohammad A. Obeidat

  3. Department of Electrical Power and Mechatronics Engineering, College of Engineering, Tafila Technical University, Tafila, 66110, Jordan

    Mohammad A. Obeidat

  4. Faculty of Science and IT, Al-Zaytoonah University of Jordan, Amman, Jordan

    Bilal Hawashin

Authors
  1. Ayman M. Mansour
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  2. Mohammad A. Obeidat
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  3. Bilal Hawashin
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Contributions

“All authors contributed to the study conception and design. Material preparation. The first draft of the manuscript was written by AMM and MAO, then it is reviewed by BH. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.”

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Correspondence to Ayman M. Mansour.

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The authors have no relevant financial or non-financial interests to disclose. The authors declare no conflict of interest.

Ethical approval

Hereby Mohammad A Obeidat consciously assure that for the manuscript entitled "Reducing the fluctuations effect of the DC supply on the three phase inverter Using Intelligent inverter control",the following is fulfilled: (1) This material is the authors' own original work, which has not been previously published elsewhere.(2) The paper is not currently being considered for publication elsewhere. (3) The paper reflects the authors' own research and analysis in a truthful and complete manner. (4) The paper properly credits the meaningful contributions of co-authors and co-researchers. (5) Results are presented clearly, honestly, and without fabrication, falsification or inappropriate data manipulation (including image based manipulation). (6) All sources used are properly disclosed (correct citation). Literally copying of text must be indicated as such by using quotation marks and giving proper reference. (7) All authors have been personally and actively involved in substantial work leading to the paper, and will take public responsibility for its content. (8) No data, text, or theories by others are presented as if they were the author’s own (‘plagiarism’). Proper acknowledgements to other works is given. (9) The study is not splitted up into several parts to increase the quantity of submissions and submitted to various journals or to one journal over time.

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Mansour, A.M., Obeidat, M.A. & Hawashin, B. A novel multi agent recommender system for user interests extraction. Cluster Comput 26, 1353–1362 (2023). https://doi.org/10.1007/s10586-022-03655-7

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  • DOI: https://doi.org/10.1007/s10586-022-03655-7

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