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33rd Conference on Computational Linguistics and Speech Processing, ROCLING 2021

作者： Huang, Yen-Hao Pornvattanavichai, Ratana Alvarado, Fernando Henrique Calderon Chen, Yi-Shin Institute of Information Systems and Applications National Tsing Hua University Hsinchu Taiwan Department of Computer Science National Tsing Hua University Hsinchu Taiwan Social Networks and Human-Centered Computing Program Institute of Information Sciences Academia Sinica Taipei Taiwan

ISBN: (纸本)9789869576949

Information overload has been one of the challenges regarding information on the Internet. It is no longer a matter of information access, instead, the focus has shifted towards the quality of the retrieved data. Particularly in the news domain, multiple outlets report on the same news events but may differ in details. This work considers that different news outlets are more likely to differ in their writing styles and the choice of words, and proposes a method to extract sentences based on their key information by focusing on the shared synonyms in each sentence. Our method also attempts to reduce redundancy through hierarchical clustering and arrange selected sentences on the proposed orderBERT. The results show that the proposed unsupervised framework successfully improves the coverage and coherence, while also reducing the redundancy for a generated summary. Moreover, due to the process through which the dataset is obtained, a data refinement method is proposed to alleviate the problem of undesirable texts, which result from the process of automatic scraping. © 2021 ROCLING 2021 - Proceedings of the 33rd Conference on Computational Linguistics and Speech Processing. All rights reserved.

关键词： Redundancy

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LOCI: A Mobile QA System with Multimodal Motivation Scheme for Local Intent Questions in Dynamic social networks 91

LOCI: A Mobile QA System with Multimodal Motivation Scheme f...

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91st IEEE Vehicular Technology Conference, VTC Spring 2020

作者： Ali, Imad Chang, Ronald Y. Hsu, Cheng-Hsin Lee, Chi-Han Institute of Information Science Academia Sinica Taiwan International Graduate Program Social Networks and Human-Centered Computing Taipei Taiwan Research Center for Information Technology Innovation Academia Sinica Taipei Taiwan National Tsing Hua University Department of Computer Science Hsinchu Taiwan

ISBN: (纸本)9781728152073

Recent research has shown that people are frequently searching for information with local intent. The existing systems fail to answer this class of questions as they are not mainly designed to handle it. In this paper, we propose LOCI, a mobile question answer system with a multimodal motivation scheme for local intent questions where users provide timely and accurate answers in a dynamic social network. LOCI mines users' shared and contextual information to identify the most relevant users for each question. The proposed multimodal motivation scheme exploits users' social ties and monetary rewards to raise their basic motivation levels. LOCI assigns questions to the best answerers via our three proposed algorithms: (i) LOCI-RT, which immediately assigns newly arrived questions/users to available users/questions, (ii) LOCI-LO, which uses short-time batches for locally optimal questions-users assignment, and (iii) LOCI-AD, which assigns short- and long-deadline questions immediately and via batching, respectively. We conduct: (i) a survey to support our assumptions regarding the proposed multimodal motivation scheme, and (ii) trace-driven experiments to evaluate the performance of the three proposed LOCI's algorithms. © 2020 IEEE.

关键词： Motivation

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Massive Machine Type Communication in Cellular System: A Distributed Queue Approach

Massive Machine Type Communication in Cellular System: A Dis...

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IEEE International Conference on Communications (ICC)

作者： Awuor, Fredrick Mzee Wang, Chih-Yu Acad Sinica Taiwan Int Grad Program Inst Informat Sci Social Networks & Human Centered Comp Program Taipei Taiwan Natl Chengchi Univ Dept Comp Sci Taipei Taiwan Acad Sinica Res Ctr Informat Technol Innovat Taipei Taiwan

ISBN: (纸本)9781479966646

Massive machine type communication (MTC) brings new challenges to next generation wide-area networks. Random Access Channel procedure (RACH) used in LTE-Advanced system for request delivery, for instance, is inefficient in handling massive number of concurrent access requests. The S-Aloha approach in RACH will lead to unsustainable delays and resource wastage due to collisions from concurrent access in massive MTC networks. To address this issue, we propose a distributed queue based MTC communication protocol that exploits multiple packet reception (MPR) capability of MTC devices to self-organize themselves into a logical queue in a distributed way such that the devices connect to BS depending on their positions in the queue. We derive the algorithm and present analysis of its performance in regard to delay and throughput. The algorithm behaves like S-Aloha when MTC traffic load is low and seamlessly and smoothly switches to a reservation based protocol during heavy traffic. From the simulation results, the proposed scheme exhibits better performance compared to conventional RACH procedure as it increases number of successful transmissions by 2.7 times and reduces both the average access delay and transmission failure probability by 20%.

关键词： Wide area networks

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On Efficient Processing of Queries for Live Multi-Streaming Soiree Organization

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IEEE Transactions on Services computing 2023年第4期16卷 2812-2826页

作者： Kankeu Fotsing, C.P. Shen, Chih-Ya Huang, Liang-Hao Chen, Yi-Shin Lee, Wang-Chien Yang, De-Nian International Graduate Program Academia Sinica Social Networks and Human-Centered Computing Program Taipei115 Taiwan National Tsing Hua University Institute of Information Systems and Applications Hsinchu300 Taiwan National Tsing Hua University Department of Computer Science Hsinchu300 Taiwan Academia Sinica Institute of Information Science Taipei115 Taiwan Pennsylvania State University Department of Computer Science and Engineering State CollegePA16801 United States

Real-time social interactions and multi-streaming are two critical features of live streaming services. In this paper, we formulate a new fundamental service query, social-aware Diverse and Preferred Organization Query (SDSQ), that jointly selects a set of diverse and preferred live streaming channels and a group of socially tight viewers for organization of a live multi-streaming soiree. We prove that SDSQ is NP-hard and inapproximable within any factor, and design SDSSel, a 2-approximation algorithm with a guaranteed error bound. Moreover, we study SDSQ-T, a special case of SDSQ, where the social graph is a threshold graph, and propose TDSSel, a 2-approximation algorithm without any error to SDSQ-T. We propose two pruning strategies, PCP and CDP to boost SDSSel and TDSSel. We further propose a more challenging but practical service query, Generalized social-aware Maximum Preferred and Diverse Query (GSPQ), a generalization of SDSQ. We design GPDSel, a 4-approximation algorithm for GSPQ with a guaranteed error bound. We propose a strategy to improve the approximation ratios of the proposed algorithms. A user study on Twitch validates SDSQ, and the large-scale experiments on real datasets demonstrate the superiority of the proposed algorithms over several baselines for live-streaming services. © 2008-2012 IEEE.

关键词： Approximation algorithms

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Massive Machine Type Communication in Cellular System: A Distributed Queue Approach

Massive Machine Type Communication in Cellular System: A Dis...

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Ad-Hoc and Sensor networks Symposium

作者： Fredrick Mzee Awuor Chih-Yu Wang Taiwan International Graduate Program Social Networks and Human-Centered Computing Program Institute of Information Science Research Center for Information Technology Innovation Academia Sinica

ISBN: (纸本)9781479966653

关键词： Concurrent Access Queue Minesite Technical Committees cellular system S-ALOHA

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SwapItUp: A Face Swap Application for Privacy Protection

SwapItUp: A Face Swap Application for Privacy Protection

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International Conference on Advanced Information Networking and Applications (AINA)

作者： Sachit Mahajan Ling-Jyh Chen Tzu-Chieh Tsai Department of Computer Science National Chengchi University Social Networks and Human Centered Computing Program Taiwan International Graduate Program Academia Sinica Institute of Information Science

ISBN: (纸本)9781509060306

There is a growing concern over the issues related to online privacy due to large availability of high quality images. To tackle the privacy concerns a face swapping application is proposed. There is a library of face images, which is created by downloading images from different sources on Internet. For any given image, lirst of all facial landmarks are detected. The second image is rotated and scaled so that it can properly lit over the input image. To make sure that the new image looks natural, color balance adjustment is done. After that blending of features from the second image onto the input image is done. It is also shown how this system can be used to creating appealing and funny photographs for entertainment purposes. We conclude with a study that shows the high quality of images produced by this system as compared to existing face swap applications and also limitations of this system.

关键词： Face Image color analysis Three-dimensional displays Solid modeling Skin Privacy Image resolution

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A Vector Mosquitoes Classification System Based on Edge computing and Deep Learning

A Vector Mosquitoes Classification System Based on Edge Comp...

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Conference on Technologies and Applications of Artificial Intelligence (TAAI)

作者： Huang, Li-Pang Hong, Ming-Hong Luo, Cyuan-Heng Mahajan, Sachit Chen, Ling-Jyh Acad Sinica Inst Informat Sci Taipei Taiwan Natl Taiwan Normal Univ Taiwan Int Grad Program Social Networks & Human Centered Comp Program Taipei Taiwan Natl Taiwan Normal Univ Dept Comp Sci & Informat Engn Taipei Taiwan

ISBN: (纸本)9781728112299

In recent years, we have witnessed a sudden increase in mosquito-borne diseases and related casualties. This makes it important to have an efficient mosquito classification system. In this paper, we implement a mosquito classification system which is capable of identifying Aedes and Culex (types of the mosquito) automatically. To facilitate the implementation of such Internet of Things (IoT) based system, we first create a trap device with a stable area for filming mosquitoes. Then, we analyze video frames in order to reduce the video size for transmission. We also build a model to identify different types of mosquitoes using deep learning. Later, we fine-tune the edge computing on the trap device to optimize the system efficiency. Finally, we integrate the device and the model into a mosquito classification system and test the system in wild fields in Taiwan. The tests show significant results when the experiments are conducted in the rural area. We are able to achieve an accuracy of 98% for validation data and 90.5% for testing data.

关键词： Mosquito Classification Internet of Things Deep Learning Convolutional Neural Network Image Processing

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TERMS: textual emotion recognition in multidimensional space

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Applied Intelligence 2023年第3期53卷 2673-2693页

作者： Ghafoor, Yusra Jinping, Shi Calderon, Fernando H. Huang, Yen-Hao Chen, Kuan-Ta Chen, Yi-Shin Social Networks and Human-Centered Computing Taiwan International Graduate Program Institute of Information Science Academia Sinica. Institute of Information Systems and Applications National Tsing Hua University Hsinchu City Taiwan Institute of Information Systems and Applications National Tsing Hua University Hsinchu City Taiwan Institute of Information Science Academia Sinica Taipei Taiwan Department of Computer Science National Tsing Hua University Hsinchu City Taiwan

Microblogs generate a vast amount of data in which users express their emotions regarding almost all aspects of everyday life. Capturing affective content from these context-dependent and subjective texts is a challenging task. We propose an intelligent probabilistic model for textual emotion recognition in multidimensional space (TERMS) that captures the subjective emotional boundaries and contextual information embedded in a text for robust emotion recognition. It is implausible with discrete label assignment;therefore, the model employs a soft assignment by mapping varying emotional perceptions in a multidimensional space and generates them as distributions via the Gaussian mixture model (GMM). To strengthen emotion distributions, TERMS integrates a probabilistic emotion classifier that captures the contextual and linguistic information from texts. The integration of these aspects, the context-aware emotion classifier and the learned GMM parameters provide a complete coverage for accurate emotion recognition. The large-scale experimentation shows that compared to baseline and state-of-the-art models, TERMS achieved better performance in terms of distinguishability, prediction, and classification performance. In addition, TERMS provide insights on emotion classes, the annotation patterns, and the models application in different scenarios. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Emotion Recognition

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Boosting Patch Correctness Checking via Combining Code-Edit Embeddings as Additional What-To-Change Information 22

Boosting Patch Correctness Checking via Combining Code-Edit ...

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22nd IEEE/WIC International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)

作者： Plengvittaya, Chontipan Tang, Zee Hen Yeh, Mi-Yen Shen, Chih-Ya Taiwan Int Grad Program Social Networks & Human Centered Comp Taipei Taiwan Natl Taiwan Univ & Acad Sinica Data Sci Degree Program Taipei Taiwan Acad Sinica Inst Informat Sci Taipei Taiwan Natl Tsing Hua Univ Inst Informat Syst & Applicat Taipei Taiwan

ISBN: (纸本)9798350309188

Patch Correctness Checking is the task of detecting automated-program-repair-generated patches that can pass the test suite but are still buggy. In this study, we investigated a new feature to improve the classification performance for automated patch correctness checking. Our approach involved leveraging code-change information at a finer granular level by embedding the code edits and combining them with existing code-change vectors. Through extensive experiments, the results revealed gains up to 3.4% and 3.2% on the F1-score and AUC.

关键词： Patch Correctness Checking Code Edits Code Changes Feature Combination

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Text and Speech Adjustable Bimodal Emotion Recognition in Conversational Interface

Text and Speech Adjustable Bimodal Emotion Recognition in Co...

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IEEE International Symposium on Consumer Electronics (ISCE)

作者： Komang Rinartha Lun-Wei Ku Social Networks and Human Centered Computing Program Taiwan International Graduate Program Institute of Information Science Nangang Taipei Taiwan Institute of Information Science Academia Sinica Taipei Taiwan

ISBN: (数字)9798350365191

ISBN: (纸本)9798350365207

Speech emotion recognition (SER) is a Machine Learning (ML) topic that is now receiving a lot of research attention. This can be attributed to its growing capacity, improvements in algorithms, and utilization in practical situations. Furthermore, speech contains not just auditory information but also lexical information. Both speech-based emotion recognition and text-based emotion recognition, called bimodal emotion recognition, can be highly beneficial for human interaction. Take an example, maintaining the communication between elder parents who are left behind after their children leave for education, employment, and family dynamics who can be greatly affected, both physically and emotionally, by feelings of loneliness and social isolation. Bimodal emotion recognition employs both text-based and audio-based methods to identify emotions. Each algorithm was trained separately and then combined using a late fusion technique. RoBERTa text-based emotion recognition can be combined with CNN audio-based emotion recognition by using late fusion to create a bimodal emotion recognition that can obtain more than 50% of accuracy by combining text and audio in a similar proportion or relying on text more than audio. By adjusting the proportion of text or audio emotion recognition, we can get better result of recognition and it can be customized by the user's preference. We elaborate on creating bimodal emotion recognition, conversational interface, a framework for emotion monitoring system, and give the example of a combined algorithm to perform emotion recognition.

关键词： Emotion recognition Accuracy Machine learning algorithms Text recognition Computational modeling Heuristic algorithms Speech recognition Machine learning Real-time systems Monitoring

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