389 research outputs found
EfficientRec an unlimited user-item scale recommendation system based on clustering and users interaction embedding profile
Recommendation systems are highly interested in technology companies
nowadays. The businesses are constantly growing users and products, causing the
number of users and items to continuously increase over time, to very large
numbers. Traditional recommendation algorithms with complexity dependent on the
number of users and items make them difficult to adapt to the industrial
environment. In this paper, we introduce a new method applying graph neural
networks with a contrastive learning framework in extracting user preferences.
We incorporate a soft clustering architecture that significantly reduces the
computational cost of the inference process. Experiments show that the model is
able to learn user preferences with low computational cost in both training and
prediction phases. At the same time, the model gives a very good accuracy. We
call this architecture EfficientRec with the implication of model compactness
and the ability to scale to unlimited users and products.Comment: Published in 14th Asian Conference on Intelligent Information and
Database Systems (ACIIDS), 202
Alpha-N: Shortest Path Finder Automated Delivery Robot with Obstacle Detection and Avoiding System
Alpha N A self-powered, wheel driven Automated Delivery Robot is presented in
this paper. The ADR is capable of navigating autonomously by detecting and
avoiding objects or obstacles in its path. It uses a vector map of the path and
calculates the shortest path by Grid Count Method of Dijkstra Algorithm.
Landmark determination with Radio Frequency Identification tags are placed in
the path for identification and verification of source and destination, and
also for the recalibration of the current position. On the other hand, an
Object Detection Module is built by Faster RCNN with VGGNet16 architecture for
supporting path planning by detecting and recognizing obstacles. The Path
Planning System is combined with the output of the GCM, the RFID Reading System
and also by the binary results of ODM. This PPS requires a minimum speed of 200
RPM and 75 seconds duration for the robot to successfully relocate its position
by reading an RFID tag. In the result analysis phase, the ODM exhibits an
accuracy of 83.75 percent, RRS shows 92.3 percent accuracy and the PPS
maintains an accuracy of 85.3 percent. Stacking all these 3 modules, the ADR is
built, tested and validated which shows significant improvement in terms of
performance and usability comparing with other service robots.Comment: 12 pages, 7 figures, To be appear in the proceedings of 12th Asian
Conference on Intelligent Information and Database Systems 23-26 March 2020
Phuket, Thailan
SciRecSys: A Recommendation System for Scientific Publication by Discovering Keyword Relationships
In this work, we propose a new approach for discovering various relationships
among keywords over the scientific publications based on a Markov Chain model.
It is an important problem since keywords are the basic elements for
representing abstract objects such as documents, user profiles, topics and many
things else. Our model is very effective since it combines four important
factors in scientific publications: content, publicity, impact and randomness.
Particularly, a recommendation system (called SciRecSys) has been presented to
support users to efficiently find out relevant articles
Combination of linear classifiers using score function -- analysis of possible combination strategies
In this work, we addressed the issue of combining linear classifiers using
their score functions. The value of the scoring function depends on the
distance from the decision boundary. Two score functions have been tested and
four different combination strategies were investigated. During the
experimental study, the proposed approach was applied to the heterogeneous
ensemble and it was compared to two reference methods -- majority voting and
model averaging respectively. The comparison was made in terms of seven
different quality criteria. The result shows that combination strategies based
on simple average, and trimmed average are the best combination strategies of
the geometrical combination
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