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Discovery of association rules between factors affecting user satisfaction in software project by FP-GROWTH Algorithm 18

Discovery of association rules between factors affecting use...

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18th International Conference on Electrical engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2021

作者： Kaewbanjong, Katawut Intakosum, Sarun King Mongkut's Institute of Technology Ladkrabang Software System Engineering Laboratory Department of Computer Science Faculty of Science Bangkok Thailand

ISBN: (纸本)9780738111278

The main objective of this work was to find the association rules between factors affecting user satisfaction in software project by using an association rule discovery technique. Data from 191 software projects were collected and association rules between 15 Selected factors were discovered by FP-growth algorithm. Primarily, 281 association rules were discovered. Rules that were not directly related to user satisfaction were filtered out by simple criteria. In the end, 11 final association rules that passed those criteria were obtained with an average confidence value of 65.30%. These rules can incorporated in the planning and administration of a software project to gain utmost user satisfaction © 2021 IEEE.

关键词： Association rules

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Anti-Social Behavior Detection in Urdu Language Posts of Social Media 3

Anti-Social Behavior Detection in Urdu Language Posts of Soc...

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3rd International Conference on Computing, Mathematics and engineering Technologies, iCoMET 2020

作者： Sohail, Muhammad Imran, Azhar Ur Rehman, Hameed Salman, Muhammad Institute of Southern Punjab Multan Department of Computer Science and IT Multan Pakistan Beijing University of Technology School of Software Engineering Beijing China

ISBN: (纸本)9781728149707

Social media such as Facebook and Twitter has gained strong attention for sharing information, worldwide connectivity and brand marketing all over the globe. The prevalent use of social networking sites has produced exceptional amounts of data. The mining of these social media applications has its potential to excerpt illegal activities which may be helpful for individuals, business and customers. The mining of data obtained from Facebook and Twitter, can be used to predict emotions of stakeholder and its analysis can provide very valuable information regarding behavioral inclinations of the writer. The automatic sentiment analysis to detect the emotional content in textual data has been widely used in many research fields. Most of the existing sentiment analysis techniques are tailored for English Language. This paper presents Urdu based antisocial behavior detection (ASB). We aim in particular to establish antisocial behavior detection method and defining its emotional state. We are intended to introduce a sentiment analysis based behavioral model that describes emotions related to antisocial behavior. In addition to describing the negative emotional state, our model will also use the concept of behavioral tendencies and evidence to predict the possible behavior of social media activists based on input text. We will outline the design of behavior detection systems based on social media posts. The learning algorithm learn about emotions from social media posts in the Roman Urdu language to predict user's behavior regarding any specific post. The results of this study has verified that our method has outperformed state-of-the-art methods in terms of accuracy. A bilingual or multilingual ASB approach can be made in future. © 2020 IEEE.

关键词： Sentiment analysis

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A UML-based approach to system testing 4th

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4th International Conference on Unified Modeling Language, UML 2001

作者： Briand, Lionel Labiche, Yvan Software Quality Engineering Laboratory Systems and Computer Engineering Department Carleton University 125 Colonel By Drive OttawaK1S 5B6 Canada

ISBN: (纸本)9783540426677

System testing is concerned with testing an entire system based on its specifications. In the context of object-oriented, UML development, this means that system test requirements are derived from UML analysis artifacts such as use cases, their corresponding sequence and collaboration diagrams, class diagrams, and possibly the use of the Object Constraint Language across all these artifacts. Our goal is to support the derivation of test requirements, which will be transformed into test cases, test oracles, and test drivers once we have detailed design information. Another important issue we address is the one of testability. Testability requirements (or rules) need to be imposed on UML artifacts so as to be able to support system testing efficiently. Those testability requirements result from a trade-off between analysis and design overhead and improved testability. The potential for automation is also an overriding concern all across our work as the ultimate goal is to fully support testing activities with high-capability tools. © Springer-Verlag Berlin Heidelberg 2001.

关键词： Economic and social effects

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Context Query Generation using Scene Graph approach 24

Context Query Generation using Scene Graph approach

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24th IEEE International Conference on Mobile Data Management, MDM 2023

作者： De Silva, Ravindi Zaslavsky, Arkady Loke, Seng Jayaraman, Prem Prakash Deakin University School of Information Technology Melbourne Australia Swinburne University of Technology Department of Computer Sceince and Software Engineering Melbourne Australia

ISBN: (纸本)9798350341010

Context-awareness (CA) has become an evolving trend, especially in the domain of Internet of Things (IoT). With the progress of IoT, the necessity for accessing real-time contextual information has become a critical factor for the advancement of IoT applications. Context management platforms (CMPs) have been proposed in the literature to support the needs of such Context-aware IoT applications. However, there are still significant gaps in terms of supporting the increasing needs of Context-aware applications, including the performance analysis of CMPs. In this paper, we propose a scene-graph based approach to generate context queries which primarily intends to support the performance analysis of CMPs and its ability to support plethora of Context-aware IoT application needs. Given the situation driven nature of IoT applications, the ability to generate relevant queries needs to be very realistic. Hence, we propose a novel Situation State Machine based approach to capture and model real-world situations. To demonstrate the potential to generate relevant context queries based on dynamic situations, a bicycle dooring use case is considered. We then present a template-based query generation approach to create realistic queries that represent real-world IoT application environment. The dooring use case is considered to validate the ability to represent complex queries, and the ability to generate complex queries in linear time. © 2023 IEEE.

关键词： Internet of things

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Post-training with Data Augmentation for Improving T5-Based Question Generator 14th

Post-training with Data Augmentation for Improving T5-Based ...

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14th International Conference on computer Science and its Applications, CSA 2022 and the 16th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2022

作者： Park, Gyu-Min Hong, Seong-Eun Hong, Choong Seon Park, Seong-Bae Department of Computer Science and Engineering Kyung Hee University Yongin Korea Republic of Department of Software Convergence Kyung Hee University Yongin Korea Republic of

ISBN: (纸本)9789819912513

Post-training is known to be effective for boosting the performance of a pre-trained language model. However, in the task of question generation, question generators post-trained with a well-designed training objective show poor performance without sufficient training examples. To handle this problem, this paper proposes a novel post-training for question generation which adopts a data augmentation technique to increase the number of training examples as well as post-training objectives. As post-training objectives, this paper introduces a new training objective, wh-words deletion, in addition to the well-known question infilling. Moreover, this paper employs back-translation techniques to increase the number of instances for post-training. To prove the effectiveness of the proposed method, this paper applies the post-training strategies to T5, a large-scale pre-trained language model, on SQuAD-QG. The experimental results demonstrate that the proposed post-training is helpful for enhancing the performance of answer-aware question generation. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Computational linguistics

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Extracting initial UML domain models from Daml+OIL encoded ontologies 4th

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4th International Conference on Product Focused software Process Improvement, PROFES 2002

作者： Kuzniarz, Ludwik Staron, Miroslaw Department of Software Engineering and Computer Science Blekinge Institute of Technology Box 520 Soft Center RonnebySE-372-25 Sweden

ISBN: (纸本)3540002340

The paper presents and elaborates on an automatic method for creating initial domain model using part of the knowledge contained in ontologies. It describes the method of how the initial domain model expressed in Unified Modeling Language (UML) can be obtained in an automated way from ontologies encoded in DAML+OIL. The solution is presented in the context of Unified software Development Process, which uses UML as a modelling language. The elements necessary for construction of domain models are identified;a procedure for finding them in DAML+OIL encoded ontologies is described followed by suggestions for incorporation of the automatic domain model construction into software development process. © Springer-Verlag Berlin Heidelberg 2002

关键词： Unified Modeling Language

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Policy-based approach for dynamic architectural adaptation: A case study on location-based system

Policy-based approach for dynamic architectural adaptation: ...

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2011 5th Malaysian Conference in software engineering, MySEC 2011

作者： Mansor, Abdehamid Abdelhadi Kadir, Wan M. N. Wan Elias, Hidayah Department of Computer Science Faculty of Mathematical Sciences University of Khartoum Khartoum Sudan Department of Software Engineering Faculty of Computer Science and Information Systems Universiti Teknologi Malaysia Johor Malaysia

ISBN: (纸本)9781457715310

Current research efforts are being directed to commit with the long-term view of self-management properties for wireless telecommunications. Technology has transformed the cell phone from being a mere phone to becoming an indispensable medium for contact, information and entertainment. The new paradigm in mobile services lies in providing a location-based user experience and here lies the tremendous scope for expansion of location-based services (LBS). One of the key approaches that have been recognized as an enabler of such a view is policy-based management, which has been mostly acknowledged as a methodology that provides adaptability and support to automatically assign network resources, control Quality of Service and security, by considering administratively specified rules. The hype of policy-based management was to commit with these features in run-time as a result of changeable network conditions resulting from the interactions of users, applications and existing resources. This paper proposes an adaptive architectural framework which deals with the critical nature of addressing the policy conflict problem. In this framework, policies are used as a mechanism to direct and adapt the behavior of self-adaptive systems. This policy-based framework consists of a set of processes, the self-coordinator process represents as the main process;which coordinates all the framework activities. Furthermore, the paper provides a guideline to avoid static and dynamic policy conflicts of different applications. © 2011 IEEE.

关键词： Location based services

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ISTC: A New Method for Clustering Search Results

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Wuhan University Journal of Natural Sciences 2008年第4期13卷 501-504页

作者： ZHANG Wei XU Baowen ZHANG Weifeng XU Junling School of Computer Science and Engineering Southeast University Nanjing 211189 Jiangsu China State Key Laboratory of Software Engineering WuhanUniversity Wuhan 430072 Hubei China Department of Computer Nanjing University of Posts andTelecommunications Nanjing 210003 Jiangsu China

A new common phrase scoring method is proposed according to term frequency-inverse document frequency （TFIDF） and independence of the phrase. Combining the two properties can help identify more reasonable common phrases, which improve the accuracy of clustering. Also, the equation to measure the in-dependence of a phrase is proposed in this paper. The new algorithm which improves suffix tree clustering algorithm （STC） is named as improved suffix tree clustering （ISTC）. To validate the proposed algorithm, a prototype system is implemented and used to cluster several groups of web search results obtained from Google search engine. Experimental results show that the improved algorithm offers higher accuracy than traditional suffix tree clustering.

关键词： Web search results clustering suffix tree term frequency-inverse document frequency （TFIDF） independence of phrases

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Top-rank enhanced listwise optimization for statistical machine translation 21

Top-rank enhanced listwise optimization for statistical mach...

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21st Conference on Computational Natural Language Learning, CoNLL 2017

作者： Chen, Huadong Huang, Shujian Chiang, David Dai, Xinyu Chen, Jiajun State Key Laboratory for Novel Software Technology Nanjing University China Department of Computer Science and Engineering University of Notre Dame India

ISBN: (纸本)9781945626548

Pairwise ranking methods are the basis of many widely used discriminative training approaches for structure prediction problems in natural language processing (NLP). Decomposing the problem of ranking hypotheses into pairwise comparisons enables simple and efficient solutions. However, neglecting the global ordering of the hypothesis list may hinder learning. We propose a listwise learning framework for structure prediction problems such as machine translation. Our framework directly models the entire translation list’s ordering to learn parameters which may better fit the given listwise samples. Furthermore, we propose top-rank enhanced loss functions, which are more sensitive to ranking errors at higher positions. Experiments on a large-scale Chinese-English translation task show that both our listwise learning framework and top-rank enhanced listwise losses lead to significant improvements in translation quality. © 2017 Association for Computational Linguistics.

关键词： Machine translation

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Deep boundary-aware semantic image segmentation

Deep boundary-aware semantic image segmentation

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作者： Wu, Huisi Li, Yifan Chen, Le Liu, Xueting Li, Ping College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Computing The Hong Kong Polytechnic University Hong Kong

While extensive research efforts have been made in semantic image segmentation, the state-of-the-art methods still suffer from blurry boundaries and mismatched objects due to the insufficient multiscale adaptability. In this paper, we propose a two-branch convolutional neural network (CNN) approach to capture the multiscale context and the boundary information with the two branches, respectively. To capture the multiscale context, we propose to embed self-attention mechanism to the atrous spatial pyramid pooling network. To capture the boundary information, we propose to fuse the low-level features in boundary feature extraction for refining the extracted boundaries via a feature fusion layer (FFL). With FFL, our method can improve the segmentation result with clearer boundaries. A new loss function is proposed which contains a segmentation loss and a boundary loss. Experiments show that our method can predict the boundaries of objects more clearly and have better performance for small-scale objects. © 2021 John Wiley & Sons, Ltd.

关键词： Semantic Segmentation

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