Hongchul Lee

Sentiment analysis of twitter audiences: Measuring the positive or negative influence of popular twitterers

Twitter is a popular microblogging service that is used to read and write millions of short messages on any topic within a 140-character limit. Popular or influential users tweet their status and are retweeted, mentioned, or replied to by their audience. Sentiment analysis of the tweets by popular users and their audience reveals whether the audience is favorable to popular users. We analyzed over 3,000,000 tweets mentioning or replying to the 13 most influential users to determine audience sentiment. Twitter messages reflect the landscape of sentiment toward its most popular users. We used the sentiment analysis technique as a valid popularity indicator or measure. First, we distinguished between the positive and negative audiences of popular users. Second, we found that the sentiments expressed in the tweets by popular users influenced the sentiment of their audience. Third, from the above two findings we developed a positive-negative measure for this influence. Finally, using a Granger causality analysis, we found that the time-series-based positive-negative sentiment change of the audience was related to the real-world sentiment landscape of popular users. We believe that the positive-negative influence measure between popular users and their audience provides new insights into the influence of a user and is related to the real world.

Self-Recognition of Vehicle Position Using UHF Passive RFID Tags

This paper proposes a method that enables self-recognition of a mobile vehicles current position by utilizing ultrahigh frequency (UHF) passive radio-frequency identification (RFID) tags. The proposed method can be used in real industry environments such as complex storage warehouses where many different goods are dispersed throughout a wide area. In particular, the proposed method makes use of two UHF RFID readers with identical emission configuration attached to a vehicle to identify a reference RFID tag. By utilizing the received signal strength indicator obtained by the readers from the reference RFID tag, the precise position of the moving vehicle can be obtained. The experiments prove the effectiveness of the proposed method in accurately estimating the vehicle position.

Methodology of technological evolution for three-dimensional printing

Purpose – An increasing amount of attention is being paid to three-dimensional (3D) printing technology. The technology itself is based on diverse technologies such as laser beams and materials. Hence, 3D printing technology is a converging technology that produces 3D objects using a 3D printer. To become technologically competitive, many companies and nations are developing technologies for 3D printing. So to know its technological evolution is meaningful for developing 3D printing in the future. The paper aims to discuss these issues. Design/methodology/approach – To get technological competitiveness of 3D printing, the authors should know the most important and essential technology for 3D printing. An understanding of the technological evolution of 3D printing is needed to forecast its future technologies and build the R & D planning needed for 3D printing. In this paper, the authors propose a methodology to analyze the technological evolution of 3D printing. The authors analyze entire patent documents...

Establishment of a security system using Aspect Oriented Programming

Security systems are complex systems that perform multiple functions such as position locating of personnel, entry/exit management of personnel, entrance management, monitoring, logging, tracing, authentication, and authorization. This paper attempts to establish a security system using aspect oriented programming (AOP). Because it is possible to establish a system by completely separating the business logic and security logic of a system using AOP, there is the advantage of being able to clearly identify the roles of each module. Also, doing so enables the establishment of a more flexible system through leveraging the innate advantages of AOP, which are expansion of code reusability and implementation of efficient features.

A sentiment analysis of audiences on twitter: who is the positive or negative audience of popular twitterers?

Microblogging is a new informal communication medium of blogging that differs from a traditional blog in which content is much shorter. Microbloggers post about topics that describe their current status. Twitter is a popular microblogging service and social media where users read and write millions of short messages on any topics within the 140-character limit. Twitter is used to find the context of social trend. Popular or influential users tweet about their status and are retweeted, mentioned or replied to by their audience. A sentiment analysis of the tweets of popular users and their audiences discovers whether the audience is favorable or unfavorable to the views expressed by such popular users. We conducted a content analysis of over 1,000,000 tweets mentioning or replying to their thirteen most influential users to discover the sentiment of the audience. Arguably, Twitter messages reflect the silent landscape of sentiment towards its most popular users. This study uses the technique of Sentiment Analysis to deliver a valid popularity indicator or measure.

An intelligent manufacturing process diagnosis system using hybrid data mining

The high cost of maintaining a complex manufacturing process necessitates the enhancement of an efficient maintenance system. For the efficient maintenance of manufacturing process, precise diagnosis of the manufacturing process should be performed and the appropriate maintenance action should be executed when the current condition of the manufacturing system is diagnosed as being in abnormal condition. This paper suggests an intelligent manufacturing process diagnosis system using hybrid data mining. In this system, the cause-and-effect rules for the manufacturing process condition are inferred by hybrid decision tree/evolution strategies learning and the most effective maintenance action is recommended by a decision network and AHP (analytical hierarchy process). To verify the hybrid learning proposed in this paper, we compared the accuracy of the hybrid learning with that of the general decision tree learning algorithm (C4.5) and hybrid decision tree/genetic algorithm learning by using datasets from the well-known dataset repository at UCI (University of California at Irvine).

A new approach for automated parts recognition using time series analysisand neural networks

This paper presents a new approach for automated parts recognition. It is based on the use of the signature and autocorrelation functions for feature extraction and a neural network for the analysis of recognition. The signature represents the shapes of boundaries detected in digitized binary images of the parts. The autocorrelation coefficients computed from the signature are invariant to transformations such as scaling, translation and rotation of the parts. These unique extracted features are fed to the neural network. A multilayer perceptron with two hidden layers, along with a backpropagation learning algorithm, is used as a pattern classifier. In addition, the position information of the part for a robot with a vision system is described to permit grasping and pick-up. Experimental results indicate that the proposed approach is appropriate for the accurate and fast recognition and inspection of parts in automated manufacturing systems.

Design of Experiment and Analysis Method for the Integrated Logistics System Using Orthogonal Array

This paper presents the simulation design and analysis of Integrated Logistics System(ILS) which is operated by using the AGV(Automated Guided Vehicle). To maximize the operation performances of ILS with AGV, many parameters should be considered such as the number, velocity, and dispatching rule of AGV, part types, scheduling, and buffer sizes. We established the design of experiment in a way of Orthogonal Array in order to consider (1)maximizing the throughput; (2)maximizing the vehicle utilization; (3)minimizing the congestion; and (4)maximizing the Automated Storage and Retrieval System(AS/RS) utilization among various critical factors. Furthermore, we performed the optimization by using the simulation-based analysis and Evolution Strategy(ES). As a result, Orthogonal Array which is conducted far fewer than ES significantly saved not only the time but the same outcome when compared after validation test on the result from the two methods. Therefore, this approach ensures the confidence and provides better process for quick analysis by specifying exact experiment outcome even though it provides small number of experiment.

Opinion leader based filtering

Recommendation systems are helping users find the information, products, and other people they most want to find, therefore many on-line stores provide recommending services e.g. Amazon, CDNOW, etc. Most recommendation systems use collaborative filtering, content-based filtering, and hybrid techniques to predict user preferences. We discuss the strengths and weaknesses of the techniques and present a unique recommendation system that automatically selects opinion leaders by category or genre to improve the performance of recommendation. Finally, our approach will help to solve the cold-start problem in collaborative filtering.

The Development of Automatic Ontology Generation System Using Extended Search Keywords

Ontologies, which are the core of the Semantic Web, are usually limited by specific domains or created by defining meanings and relationships that depend on the heuristic. However, the creation of an ontology is not only very difficult but also very time-consuming. In contrast with ontologies that are used in specific fields, an ontology for the Web entails an unlimited scope of knowledge and expression of information. Hence, it is hard to express information in the same way that is used to create ontologies in specific fields. Therefore, the automatic generation of an ontology takes very important role in the Semantic Web. In this paper, to make ontologies automatically, we suggest the methods to create and renew ontologies by expanding keywords related to the index-terms which are extracted from the search keywords which users input in the search engines by analyzing the morphemes.