Hybrid Recommender for Research Papers and Articles
Alhassan Jamilu Ibrahim,
Peter Zira,
Nuraini Abdulganiyyi
Issue:
Volume 10, Issue 2, April 2021
Pages:
9-15
Received:
18 September 2019
Accepted:
22 March 2021
Published:
14 May 2021
Abstract: In digital libraries and other e-commerce sites, recommender system is the solution that supports the users in information search and decision making. Some of these recommender systems will make predictions by matching the content of an item against the user profile otherwise known as Content-Based recommendation approach. Other recommenders will provide recommendation based on ratings of items from current user and other users and then use it to recommend similar items the current user has not seen, this is known as Collaborative-Based recommender approach. There exist several other approaches that are used in recommending articles and other items to users of different search engines. Over the years several researchers have tried combining these approaches in an attempt to design more efficient recommendations in search engines. This research proposed and designed a prototype of a Hybrid recommender called Zira, which is a model that combines both the Collaborative filtering, Content-based filtering, attribute-based approach to look at contextual information as well as an item-based approach that will solve the issues associated with cold-start problems all working concurrently to complement one another. The proposed system supports multi-criteria ratings, provide more flexible and less intrusive types of recommendations to ensure the improvement in recommendations of e-learning materials to users of digital libraries.
Abstract: In digital libraries and other e-commerce sites, recommender system is the solution that supports the users in information search and decision making. Some of these recommender systems will make predictions by matching the content of an item against the user profile otherwise known as Content-Based recommendation approach. Other recommenders will p...
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Modeling of Virtual Assembly and Disassembly Process Based on Selective Disassembly
Hao Wang,
Yan Tao Yang,
Qing Shen,
Qian Zhang,
Bin Yin
Issue:
Volume 10, Issue 2, April 2021
Pages:
16-22
Received:
2 May 2021
Accepted:
17 May 2021
Published:
3 June 2021
Abstract: The virtual disassembly and assembly system based on computer virtual reality technology has been rapidly developed and applied. However, the current virtual disassembly system and assembly based on the hierarchy model and association model does not consider the problem of selective disassembly, which leads to inconsistency between virtual disassembly and actual disassembly. Aiming to solve the problem, introduces the concept of skipping disassembly path on the basis of the original disassembly system based on the hierarchical relationship and the association relationship model, and perfects and optimizes the disassembly and assembly structure model based on the hierarchical relationship model and the association relationship model. The sequence planning of the disassembly model after introducing the shipping disassembly path was carried out．And the combination and reduction of disassembling units in the course of disassembly decision was described. Finally, a selective disassembly algorithm based on the association relationship model is established. With the marine oil separator for example verification. The results show that the model can better solve the actual problem of selective disassembly which improved the authenticity and user experience of the virtual disassembly and assembly system, and has great influence on the application development of the virtual disassembly and assembly system.
Abstract: The virtual disassembly and assembly system based on computer virtual reality technology has been rapidly developed and applied. However, the current virtual disassembly system and assembly based on the hierarchy model and association model does not consider the problem of selective disassembly, which leads to inconsistency between virtual disassem...
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