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A Study of Multi-Task Recommendation Models Incorporating Preference Propagation 3

A Study of Multi-Task Recommendation Models Incorporating Pr...

引用

3rd IEEE International Conference on Electronic technology, Communication and information, ICETCI 2023

作者： Yang, Benchen Ye, Hongyu Meng, Xiangfu Liaoning University of Engineering Technology Software Academy Huludao China Liaoning University of Engineering Technology Electronic and Information Engineering Academy Huludao China

ISBN: (纸本)9798350398410

To address the problem that knowledge graph can effectively reduce the triadic relationships of entities from multi-source heterogeneous data, but is not conducive to recommendation tasks and it is difficult to explore the potential association relationships of data using single-task learning, a multi-task recommendation model with fused preference propagation (MAPKR) is proposed. Firstly, the user's preference feature set is extracted from the knowledge graph using ripple propagation;secondly, the potential features are shared based on the similar nearest neighbor structure, and the higher-order feature representations of items and entities are extracted by cross-compression units;finally, the recommendation module and the knowledge graph embedding module are trained alternately with multi-task learning, and the extracted feature vectors are predicted and recommended after normalized inner product operation. Experiments are conducted on three publicly available datasets and compared with five baseline models. Compared with MKR and RippleNet, the AUC improved by 2.53% and 2.66% on average on the three datasets;ACC improved by 3.07% and 3.46% on average. The results show that the model presented in this paper has good recommended performance. © 2023 IEEE.

关键词： Recommender systems

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Recursive Weighted 2-Means Split Algorithm For Under-segmentation Reduction 28

Recursive Weighted 2-Means Split Algorithm For Under-segment...

引用

28th International Conference on information Society and University Studies, IVUS 2023

作者： Magylaitė, Kornelija Arlauskas, Lukas Ryselis, Karolis Software Engineering Department Kaunas University of Technology Lithuania Information Systems Department Kaunas University of Technology Lithuania

Human body segmentation is utilized in various applications as an intermediate step. This problem is best solved using supervised machine learning solutions, however, they require annotated data for training. Unfortunately, annotating data for segmentation is an extremely labor-intensive task. It could be improved by using semi-automatic segmentation algorithms, however, their accuracy tends to be low for complex scenes. The errors made by such algorithms can be manually corrected by a human. This process could be more efficient when automatic correction tools are added to the data processing pipeline. This research aims to improve the final semi-automatic segmentation accuracy by improving an existing random forest classifier for correcting point cloud segmentation based on metrics of recursive 2-Means split. We replace the K-Means clustering with a weighted K-Means clustering and optimize the weights. Experiments have revealed that the segmentation accuracy of 62.4% is improved to 66.1% with a weight ratio of 0.4. Since higher accuracy leads to less manual labor, this is a sought-after improvement that reduces the time to prepare datasets for human body segmentation. © 2023 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (***)

关键词： K-means clustering

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Dramatizing software Patterns: Focus Group Report 28

Dramatizing Software Patterns: Focus Group Report

引用

28th European Conference on Pattern Languages of Programs, EuroPLoP 2023

作者： Vranic, Valentino Vranic, Aleksandra Vranic, Branislava Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9798400700408

The focus group on drama patterns we organized at EuroPLoP 2023 attracted 16 participants (apart from the organizers), who together built a short drama play (created by Aleksandra Vranic) based on the motifs from the stories of Alice in Wonderland. We discussed how particular drama patterns metaphorically correspond to some software patterns and elaborated on two examples of such correspondence: the Thoughts Reflecting Environment drama pattern and its correspondence to the Observer design pattern and the Loosely Coupled Situations drama pattern and its correspondence to the Visitor design pattern. Both drama patterns were first played by the participants and then related to the corresponding design pattern. We also played Observer in a technical, nonmetaphoric way. We also made a performance at the banquet, which was accepted with delight. We achieved this with no rehearsals and with the actor for the main role appointed just before the performance, which confirmed once more how powerful patterns are. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： design patterns drama patterns organizational patterns pattern composition

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MAML-TSC: Model-Agnostic Meta-Learning for Time Series Classification 7

MAML-TSC: Model-Agnostic Meta-Learning for Time Series Class...

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7th International Conference on Pattern Recognition and Artificial Intelligence, PRAI 2024

作者： Wang, Jiahao Sun, Zutong Yan, Hang Chen, Hao School of Information and Software Engineering University of Electronic Science and Technology of China Chengdu610000 China School of Intelligent Manufacturing and Information Technology Yaan Polytechnic College Yaan625000 China

ISBN: (纸本)9798350350890

User portrait technology, involves analyzing historical usage records of household electronic devices, is evolving quickly. Traditional methods using LSTM or CNN for time series classification face challenges in achieving high accuracy with limited data. To address this, our study introduces MAML-TSC, which combines a dual-channel Transformer with model-agnostic meta-learning (MAML). This model features a dual-channel Transformer that leverages a multi-head self-attention mechanism to extract information from both time and channel axes effectively. By incorporating MAML, the model harnesses knowledge transfer to optimize initialization parameters for diverse training tasks, enhancing performance with fewer data samples. Experimental outcomes show MAML-TSC achieving 90% accuracy in the meta-learning phase and maintaining over 80% after 10 iterations, outperforming the DeepConvLSTM baseline by 12.5% and surpassing most current deep-learning approaches. © 2024 IEEE.

关键词： Contrastive Learning

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The Impact of Generative Artificial Intelligence on Learning: A Case Study at the University of Petra 2

The Impact of Generative Artificial Intelligence on Learning...

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2nd International Conference on Cyber Resilience, ICCR 2024

作者： El-Khalili, Nuha Al-Nashashibi, May Al-E'mari, Salam University Of Petra Faculty Of Information Technology Software Engineering Department Amman Jordan University Of Petra Faculty Of Information Technology Data Science & Artificial Intelligence Department Amman Jordan University Of Petra Faculty Of Information Technology Information Security Department Amman Jordan

ISBN: (纸本)9798350394962

Recently, a noticeable trend of using Generative Artificial Intelligence (GAI) within the educational field has raised interest to study the shape and impact of this utilization. This study investigates the opinions of information technology (IT) undergraduate students about the utilization of GAI during the learning process, focusing on their perception of the quality of produced information, challenges and concerns while using it, how they utilize it during learning, and long-term impact of using GAI. An electronic survey was distributed as a Google from to undergraduate students from five IT programs at the University of Petra. The results of 122 students revealed that 82% use GAI while learning. The main use of GAI (80% of respondents) was for solving programming problems, while 66% of respondents use GAI to write reports and express their ideas. The majority 86% of participants evaluate the presented information from GAI before using them, since they believe that sometimes the information is incorrect. 89% of respondents believe that they can learn from GAI tools, however, 95% of them feel it is necessary to train them on the proper utilization of GAI in education, and, 76% think that regulations must be released about the acceptable use of GAI. © 2024 IEEE.

关键词： Artificial intelligence

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Inclusive Gamification: An Exploratory Study in software Development Enterprises 35

Inclusive Gamification: An Exploratory Study in Software Dev...

引用

35th International Conference on software engineering and Knowledge engineering, SEKE 2023

作者： Elsalmy, Fayrouz Sherief, Nada Hany Abdelmoez, Walid Information Systems College of Computing and Information Technology Arab Academy for Science and Technology Alexandria Egypt Software engineering College of Computing and Information Technology Arab Academy for Science and Technology Alexandria Egypt

Gamification is the incorporation of game elements into non-game settings. software designers increase user motivation by introducing adequately engaging elements, such as leaderboards and badges, into an existing system. In recent years, few studies have examined the risks associated with gamification inside the business systems sector, especially within software development organizations. Yet, this issue must be addressed more systematically to build gamified solutions that take individual gamification risks into account. This research introduces "Inclusive Gamification" as contextually aware gamification that highlights individual risks. The purpose of this paper is twofold: 1) to identify the gamification risk factors that could cause the emergence of risks in software development organizations;and 2) to develop a list of risks with consideration of various contextual factors, namely tasks, personality type, adopted game element, and organizational cultural aspects. 15 employees from three software development companies participated in an exploratory study in which their perspectives on the negative effects of gamification were collected. As a result, we were able to identify several risk factors and associated risks. Our findings assist software engineers throughout the design process in identifying potential threats. Thus, create gamified solutions that better situate employees at their workplaces. © 2023 Knowledge Systems Institute Graduate School. All rights reserved.

关键词： Personnel

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Decoding Diabetes: Unconventional Indicators for Diabetic Diagnosis 10

Decoding Diabetes: Unconventional Indicators for Diabetic Di...

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10th International Conference on engineering and Emerging Technologies, ICEET 2024

作者： Sangavi, G. Kajanan, T. Methiny, S. Tissera, Wishalya Rajendran, Karthiga Sri Lanka Institute of Information Technology Faculty of Computing Malabe Colombo Sri Lanka Sri Lanka Institute of Information Technology Department of Software Engineering Malabe Colombo Sri Lanka

ISBN: (纸本)9798331532895

Diabetes diagnosis has always involved glucose tests;however, it is possible to recognize diabetic complications by simply looking at skin and nails. This work presents a new approach for identifying diabetes-related complications, including acanthosis nigricans, foot ulcers, and nail infections, utilizing and TensorFlow for deep learning. Both conditions are associated with visual signals and pass through a strictly trained dataset, marked up for maximum accuracy. From the methodologies, including image resizing, data augmentation, and hyperparameter tuning. The findings of accuracy confirm that the platform should register specific characteristics of the problem area and has the essential precision to maintain close attention to possible risks of diabetes and intervene early to reduce the likelihood of patients' deteriorating health. © 2024 IEEE.

关键词： Diagnosis

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Patterns for Improving User Contribution 28

Patterns for Improving User Contribution

引用

28th European Conference on Pattern Languages of Programs, EuroPLoP 2023

作者： Haiderzai, Mohammad Daud Vranic, Valentino Institute of Informatics Information Systems and Software Engineering Faculty of Informatics and Information Technologies Slovak University of Technology Bratislava Slovakia

ISBN: (纸本)9798400700408

User contributions is an important part in software development, the pursuit of identifying effective means of user contributions in software development is a crucial area of interest for software companies and their development teams. Determining the most opportune moments, locations, and methods for such contributions presents a significant challenge for organizations, which necessitates the exploration of generic and proven solutions. Applying patterns, established and observed solutions may provide the answers to such challenges and similar ones. This paper offers insights into the practical implementation of seven newly discovered organizational patterns in a real-life environment. The patterns are comprehensively described, accompanied by illustrative examples, and subsequently applied in actual practices. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： software design

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Analyzing Data Format Interoperability in API Ecosystems Using Big Data Architecture 11

Analyzing Data Format Interoperability in API Ecosystems Usi...

引用

11th International Conference on information technology, ICIT 2023

作者： Alzyadat, Wael Al-Showarah, Suleyman University of Jordan Faculty of Science and IT Alzaytoonah Department of Software Engineering Amman Jordan Mutah University Faculity of Information Technology Dept of Software Engineering Jordan

ISBN: (纸本)9798350320060

The API is a key player in cut edge technology for interact and exchange information across platforms whatever internally or external where the transfer information needs to be adjusted by several issues during request/response *** traditional concept of API was handle it by data mapping functions for this point uncapitalizable with big data architecture especially of variety of data which data able to presents in different kinds of structured data that aimed to fnd out approach to solve it, for this point the XML play an important role for variety data by dynamic behavior with effective © 2023 IEEE.

关键词： Big data

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Discussion Manipulation, Language and Domain Dependent Models: An Overview

Discussion Manipulation, Language and Domain Dependent Model...

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2023 IEEE Zooming Innovation in Consumer Technologies Conference, ZINC 2023

作者： Chalas, Filip Stupavsky, Igor Vranic, Valentino Slovak University of Technology in Bratislava Faculty of Informatics and Information Technologies Institute of Informatics Information Systems and Software Engineering Slovakia

ISBN: (纸本)9798350347722

The amount of antisocial online behavior (AOB) in the political field has been on the rise in recent years. In the research, we are dealing with the reason for confusing AOB with other forms of antisocial behavior. We specifically dealt with NLP in the political field in the Slovak language, with a specific number of prefixes and suffixes. In this paper, we focus on the area of detection of manipulation of political discussions. The data source consisted of previously collected data in the period from April 2018 with an update until November 19, 2022 realized within this research from the site ***, which we supplemented with new claims. We trained several classification models on preprocessed data and evaluated them. For multi-class classification, the best results were achieved using logistic regression and a support vector machine trained on the resampled dataset-both achieving an accuracy of 0.56 and a macro F1 score of 0.39. In the case of binary classification, the best results were achieved by logistic regression-accuracy 0.7 and macro F1 score 0.56. These models could help detect manipulation in online political discussions. © 2023 IEEE.

关键词： Logistic regression

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