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2014 Conference on Empirical Methods in Natural Language Processing, EMNLP 2014

作者： Tsai, Ming-Feng Wang, Chuan-Ju Program in Digital Content and Technology Department of Computer Science and National Chengchi University Taipei116 Taiwan Department of Computer Science University of Taipei Taipei100 Taiwan

ISBN: (纸本)9781937284961

This paper proposes to apply the continuous vector representations of words for discovering keywords from a financial sentiment lexicon. In order to capture more keywords, we also incorporate syntactic information into the Continuous Bag-of- Words (CBOW) model. Experimental results on a task of financial risk prediction using the discovered keywords demonstrate that the proposed approach is good at predicting financial risk. © 2014 Association for Computational Linguistics.

关键词： Finance

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A prototype of Baby Monitoring Use Raspberry Pi 7

A prototype of Baby Monitoring Use Raspberry Pi

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7th International Conference on ICT for Smart Society, ICISS 2020

作者： Rudyansyah, Aldy Hendric Spits Warnars, Harco Leslie Lumban Gaol, Ford Matsuo, Tokuro Bina Nusantara University BINUS Graduate Program - Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Advanced Institute of Industrial Technology Graduate School of Industrial Technology Tokyo Japan

ISBN: (纸本)9781665404228

The security system in monitoring the room or something suspicious activity that can cause crimes in the field of information and technology as in private homes is indispensable. Aims to keep valuables from theft and loved ones like babies from kidnapping or reducing the risk of an accident in an unguarded infant activity. The use of CCTV still has constraints because some functions are still done manually such as should always move the record of the CCTV data every day to different memory so that there is waste in using memory. Moreover, the position of the camera can not be adjusted freely in the placement so that it can easily be destroyed by irresponsible people, and also ordinary CCTV needs electricity that is considerable in its use. This research is done to improve and facilitate the process of monitoring of baby activity and the room where the baby is called sleep or rest, all monitoring activities can be done using only a Web browser that can be accessed by a smartphone or desktop. The monitoring system is created using a program called RPi Cam that is installed on the Raspberry Pi with a Raspberry Camera module as a monitoring camera and a DHT22 sensor module as a room temperature monitor. © 2020 IEEE.

关键词： Security systems

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Social influencer analysis with factorization machines 15

Social influencer analysis with factorization machines

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7th ACM Web science Conference, WebSci 2015

作者： Tsai, Ming-Feng Wang, Chuan-Ju Lin, Zhe-Li Department of Computer Science and Program in Digital Content and Technology National Chengchi University Taipei116 Taiwan Department of Computer Science University of Taipei Taipei100 Taiwan

ISBN: (纸本)9781450336727

How will the reputations of individuals in a social network be influenced by their communities in a quantitative way? This work attempts to observe the collaborative events occurring at individuals involved in a social network to obtain such crucial knowledge. We propose a Factorization Machine approach to find out the latent social influence among the individuals based on their collaborations. Experiments conducted on a real-world DBLP dataset verify that the proposed approach can discover the latent social influence among individuals and provide a better predictive model than several baselines. © 2015 ACM.

关键词： Collaborative filtering

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A bandwidth adaptation scheme to support QoS requirements of mobile users in wireless environments 9

A bandwidth adaptation scheme to support QoS requirements of...

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9th International Conference on computer Communications and Networks, ICCCN 2000

作者： Aljadhai, AbdulRahman Znati, Taieb F. Computer Technology Department Riyadh College of Technology Riyadh Saudi Arabia Department of Computer Science Telecommunications Program University of Pittsburgh PittsburghPA15260 United States

ISBN: (纸本)0780364945

- This paper presents an adaptive QoS management scheme to accommodate dynamic variations in network resources, due to the mobility of the users and location-dependent errors. The scheme ensures that satisfactory level of QoS guarantees are met regardless of the user mobility. QoS adaptation is achieved based on the use of application specific quality satisfaction curves, while enforcing a fair allocation of bandwidth among the competing flows. The performance of the proposed scheme is evaluated and results indicate that the scheme yields fair adaptation under heavy loads. © 2000 IEEE

关键词： Quality of service

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Bi_2Se_3/C Nanocomposite as a New Sodium-Ion Battery Anode Material

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Nano-Micro Letters 2018年第3期10卷 135-143页

作者： Lixin Xie Ze Yang Jingying Sun Haiqing Zhou Xiaowei Chi Hailong Chen ANDy X.Li Yan Yao Shuo Chen Department of Physics and TcSUH University of Houston Department of Electrical and Computer Engineering and Materials Science and Engineering Program University of Houston The Woodruff School of Mechanical Engineering Georgia Institute of Technology Clements High School

Bi_2Se_3 was studied as a novel sodium-ion battery anode material because of its high theoretical capacity and high intrinsic conductivity. Integrated with carbon,Bi_2Se_3/C composite shows excellent cyclic performance and rate capability. For instance, the Bi_2Se_3/C anode delivers an initial capacity of 527 mAh g^(-10) at 0.1 A g^(-1) and maintains 89% of this capacity over 100 cycles. The phase change and sodium storage mechanism are also carefully investigated.

关键词： Bi2Se3 Sodium-ion battery High-energy ball milling Sodium storage mechanism

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Sentiment Analysis of User Review on Indonesian Food and Beverage Group using Machine Learning Techniques

Sentiment Analysis of User Review on Indonesian Food and Bev...

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2022 IEEE Creative Communication and Innovative technology, ICCIT 2022

作者： Yanfi, Yanfi Heryadi, Yaya Lukas, Lukas Suparta, Wayan Arifin, Yulyani Bina Nusantara University Binus Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Binus Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Jakarta12930 Indonesia Faculty of Industrial Technology Institut Teknologi Nasional Yogyakarta Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9781665468763

A vast number of technologies based on Artificial Intelligence (AI) have proliferated into various application domains. As part of its objectives to develop agents which can behave and think like humans, some branches of AI have focused on developing various algorithms that can learn from input data without explicitly being programmed. In the food industry, notably in restaurants, smartphone technology is typically used to collect data from customers efficiently such as orders or feedback toward the services provided. The use of smartphones by some restaurants is motivated by their convenience and efficiency. Furthermore, various promotions, discounts, and membership benefits offered by cellular service providers have attracted the use of smartphones as devices for improving restaurant services to their customers. This study aimed to conduct a sentiment analysis related to multi-brand restaurants in Indonesia based on customer feedback. The data retrieved from the Google Play Store consists of 756 reviews from Boga, Champs, Hangry, Ismaya, Kulo, and Union groups. In this study, TF-IDF was used as a vectorizer to represent customer feedback as numeric vectors. The polarity sentiment of customer feedback was recognized using classifier models based on machine learning such as Logistic Regression, Naive Bayes (NB), Random Forest, and Support Vector Machine (SVM) as the classifier. The empirical results showed that SVM has the best accuracy of 93.10 % average accuracy followed by Logistic Regression with 92.41 %, Random Forest with 84.14 % average accuracy, and Naive Bayes with 76.55 % average accuracy. © 2022 IEEE.

关键词： Sentiment analysis

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Density Based Spatial Clustering of Applications with Noise and Sentence Bert Embedding for Indonesian Utterance Clustering

Density Based Spatial Clustering of Applications with Noise ...

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2023 International Conference on computer science, Information technology and Engineering, ICCoSITE 2023

作者： Hasani, Muhammad Fikri Heryadi, Yaya Arifin, Yulyani Lukas Suparta, Wayan Bina Nusantara University BINUS Graduate Program Computer Science School of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University BINUS Graduate Program Computer Science Computer Science Department Jakarta11480 Indonesia Jakarta12930 Indonesia Institut Teknologi Nasional Yogyakarta Faculty of Industrial Technology Department of Electrical Engineering Yogyakarta55281 Indonesia

ISBN: (纸本)9798350320954

Task oriented chatbots are a sub-topic related to chatbots, where chatbots will perform certain tasks with specific goals. One part of creating a task-oriented chatbot is doing intent classification. Intent classification is a task of text classification. As in general text classification, the required dataset requires a label to carry out the classification process. To speed up and help the utterance analysis process, there is already a method, namely clustering, and Density-based clustering is a part of clustering that can determine cluster patterns based on arbitrary data, with DBScan as one of its algorithms. This research used 10000 client utterance data of awhatsapp based e-commerce conversation. SentenceBert also used as a state of art sentence embedding. This research yield silhouette score of 0.327 as the best result from eps of 0.1 and MinPts of 95. However, based on the cluster result, sentences labelled as noise can be further clustered. Text Preprocessing, text augmentation and sentence embedding techniques can be explored to increase the cluster performance. © 2023 IEEE.

关键词： Embeddings

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Effect of active learning using program visualization in technology-constrained college classrooms

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Research and Practice in technology Enhanced Learning 2015年第1期10卷 1-25页

作者： Banerjee, Gargi Murthy, Sahana Iyer, Sridhar Interdisciplinary Program in Educational Technology Indian Institute of Technology Bombay Mumbai 400076 India Department of Computer Science and Engineering Indian Institute of Technology Bombay Mumbai 400076 India

Multiple studies report that computer science (CS) instructors face problems on how to integrate visualizations in their teaching. This problem gets compounded for instructors in technology-constrained classrooms that are common in developing countries. In these classrooms, students are not able to interact with visualization directly;instead, their interaction is mediated by the instructor who alone may have access to the visualization. In the current study, we contrasted learning outcome from integrating program visualization at two different engagement levels in instructor-mediated classroom setting. The two levels were “Responding” (prediction activity with visualization) and “Viewing” (watching visualization with instructor commentary) as per Naps’ taxonomy. The study was conducted for a programming topic of medium complexity. We found the strategy of prediction with visualization (“Responding”) led to statistically significant higher active behavioral engagement and higher perception of learning among students than the strategy of watching the visualization with instructor commentary (“Viewing”). We also found statistically significant higher cognitive achievement in terms of the rate of problem solving for the “Responding” group, if the students had prior training in active learning. This study can serve as a reference guide to design effective integration of visualizations in instructor-mediated classrooms. © 2015, The Author(s).

关键词： Active learning Engagement levels Prediction program visualization Viewing

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Design and Implementation of Business Intelligence Dashboard for Project Control at the Port Harbor-Company 12th

Design and Implementation of Business Intelligence Dashboard...

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12th Asian Conference on Intelligent Information and Database Systems, ACIIDS 2020

作者： Lumban Gaol, Ford Syahir, Arsyan Matsuo, Tokuro Computer Science Department BINUS Graduate Program – Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program – Master of Information System Bina Nusantara University Jakarta Indonesia Advanced Institute of Industry Technology Tokyo Japan

ISBN: (纸本)9789811533792

This study aims to assist resource management and the project controller at Port Harbor Company. Port Harbor Company is an IT Consulting. Problems that often occur in IT Consulting are related to the project cost, resource management and control of each project. Problems that occur at the Port Harbor Company are poor resource management, spending costs that exceed a predetermined budget and how to see the status of ongoing projects. Using Business Intelligence and the dashboard as a front end will help the project controller and resource management manage resources, manage project costs and monitor ongoing projects. In this study, the development and implementation of Business Intelligence and dashboards using the ASAP method are expected to be more structured and can solve the Port Harbor Company problem. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Project management

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Optimation Cavacity Vehicle Routing Problem with K-Nearest Neighbor in Classification of Goods Ditribution Route 7

Optimation Cavacity Vehicle Routing Problem with K-Nearest N...

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7th IEEE International Conference of computer science and Information technology, ICOSNIKOM 2023

作者： Novelan, Muhammad Syahputra Efendi, Syahril Sihombing, Poltak Mawengkang, Herman Universitas Sumatera Utara Doctoral Program of Computer Science Faculty of Computer Science and Information Technology Medan Indonesia Universitas Sumatera Utara Faculty of Computer Science and Information Technology Department of Computer Science Medan Indonesia Universitas Sumatera Utara Faculty of Mathematics and Natural Sciences Department of Mathematics Medan Indonesia

ISBN: (纸本)9798350360752

Industrial and distribution service problems that belong to combinatorial optimization include vehicle routing with Vehicle Routing Problem. This research builds a framework and implements it in a multi-class optimization model to reduce overfitting and misclassification results caused by unbalanced multiclassification in the influence of the number of 'nodes' on vehicle routes with machine learning. The problem of imbalance in vehicle route classification has been a challenge in the classification process and attracted the attention of a number of researchers. The purpose of the model in general is to gain an understanding of the mechanism in the problem so as to classify the imbalanced vehicle route data based on JNE delivery routes. The solution method that will be used by applying k-nearest neighbor to determine the amount of carrying capacity of the goods will then determine the delivery location point with the vehicle routing problem. So that this model can be a model in determining vehicle routes based on the capacity limit of the number of shipments of goods. © 2023 IEEE.

关键词： Machine learning

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