An Improved Web Design to Support Online Investment Decisions

The rise of the Internet opens up new possibilities and creates new challenges for investors. The possibilities include ease of use, cheaper trading costs, and greatly improved access to information. The challenges include information overload and a temptation to overtrade. The present paper discusses how brokerage firms can improve their web site designs in order to meet these challenges and opportunities and to better facilitate the needs of individual investors. Specifically, the paper discusses how an objectoriented information representation system can be used to enable both investor-specific information, such as risktolerance level, investment time horizon, and tax status, and more general information from the financial markets themselves, such as company P/E levels, to be integrated into a consistent web presentation that will facilitate the investor’s making more intelligent investment decisions. Such an information representation system would be structured hierarchically, with the investor-specific information at the top of the hierarchy, driving the application of market-level, then industry-level, and, at the bottom of the hierarchy, company-specific information. Finally, the paper discusses the feasibility of implementing such a system and some of the promises and pitfalls that may arise from its implementation

Knowledge Discovery and Data Mining (KDDM) survey report.

The large number of government and industry activities supporting the Unit of Action (UA), with attendant documents, reports and briefings, can overwhelm decision-makers with an overabundance of information that hampers the ability to make quick decisions often resulting in a form of gridlock. In particular, the large and rapidly increasing amounts of data and data formats stored on UA Advanced Collaborative Environment (ACE) servers has led to the realization that it has become impractical and even impossible to perform manual analysis leading to timely decisions. UA Program Management (PM UA) has recognized the need to implement a Decision Support System (DSS) on UA ACE. The objective of this document is to research the commercial Knowledge Discovery and Data Mining (KDDM) market and publish the results in a survey. Furthermore, a ranking mechanism based on UA ACE-specific criteria has been developed and applied to a representative set of commercially available KDDM solutions. In addition, an overview of four R&D areas identified as critical to the implementation of DSS on ACE is provided. Finally, a comprehensive database containing detailed information on surveyed KDDM tools has been developed and is available upon customer request

Proceedings of the 1st joint workshop on Smart Connected and Wearable Things 2016

These are the Proceedings of the 1st joint workshop on Smart Connected and Wearable Things (SCWT'2016, Co-located with IUI 2016). The SCWT workshop integrates the SmartObjects and IoWT workshops. It focusses on the advanced interactions with smart objects in the context of the Internet-of-Things (IoT), and on the increasing popularity of wearables as advanced means to facilitate such interactions

헬스케어를 위한 대화형 인공지능의 모사된 페르소나 디자인 및 사용자 경험 연구

학위논문(박사) -- 서울대학교대학원 : 인문대학 협동과정 인지과학전공, 2021.8. 이준환.디지털 헬스케어(Digital Healthcare) 기술의 발전은 일상 헬스케어 영역에서의 혁신을 주도 하고 있다. 이는 의학 전문가들의 정확한 진단, 질병의 치료를 도울 뿐만 아니라 사용자가 스스로 일상에서 자기관리를 할 수 있도록 돕는다. 디지털 헬스케어 기술의 대표적인 목표 중 하나는 효과적으로 헬스케어 서비스를 개인화 시키는 것인데, 이러한 측면에서 대화형 인공지능(Conversational AI)은 사용하기 쉽고 효율적인 비용으로 개인화된 서비스를 제공할 수 있기에 주목받고 있다. 기존의 개인화된 케어 서비스들의 경우는 대부분 의료기관의 질병치료 서비스들에 포함되었는데, 대화형 인공지능은 이러한 개인화된 케어 서비스의 영역을 일상에서의 질병 예방을 위한 관리로 확장하는데 기여한다. 일대일 대화를 통해 맞춤형 교육, 테라피, 그외의 관련 정보 등을 제공할 수 있다는 측면에서 일상 헬스케어에 적합한 디지털 헬스케어 기술로의 활용도가 높다. 이러한 이점으로 인해 다양한 역할을 가진 대화형 인공지능들의 개발이 이루어지고 있다. 그러나, 이러한 대화형 인공지능들에게 사용자의 선호도에 적합한 페르소나를 부여하는 연구는 드물게 이루어 지고 있다. 대화형 인공지능의 주요 기능인 자연어 기반 상호작용은 CASA 패러다임(CASA Paradigm)에서 제기하는 사용자가 시스템을 의인화하는 경향을 높인다. 때문에 페르소나에 대한 사용자의 선호도가 지속적인 대화형 인공지능의 사용과 몰입에 영향을 미친다. 또한 대화형 인공지능의 장기적인 사용을 위해서 적절한 사용자와의 사회적, 감정적 상호작용을 디자인 해 주어야 하는데, 인지된 페르소나에 대한 사용자의 선호도가 이 과정에도 유의미한 영향을 미친다. 때문에 지속적인 참여가 결과에 큰 영향을 미치는 일상 헬스케어 영역에서 대화형 인공지능을 활용하는데 개인화된 페르소나 디자인이 긍정적인 사용자 경험 및 사용자 건강 증진의 가능성을 높일 것으로 본 연구는 가정한다. 개인화된 페르소나 디자인을 위해 사용자와 현실에서 친밀한 관계에 있는 실존인물(호스트)의 페르소나를 대화형 인공지능에 적용하고 평가하는 것이 본 연구의 핵심적인 아아디어이다. 이를 검증하기 위해서 해당 학위 논문은 총 세 가지의 세부 연구를 포함한다. 첫째는 실존인물의 페르소나 중에서도 일상 건강관리에 적합한 호스트의 페르소나를 탐색하는 연구이다. 둘째는 호스트의 페르소나를 대화형 인공지능에 적용하기 위해 고려해야 할 언어적 요소들을 정의하는 연구이다. 마지막으로는 위의 과정을 통해 개발된 실존하는 인물의 페르소나를 가진 대화형 인공지능이 일상 헬스케어 영역에서 실제 효과를 보이는지를 평가하는 연구이다. 또한 해당 학위논문은 일련의 연구들에서 발견한 결과들을 바탕으로 사용자와 친밀한 관계에 있는 페르소나를 일상 헬스케어를 위한 대화형 인공지능에 적용할 때 고려해야할 디자인 함의점들을 도출하고 가이드라인을 제시한다.Advance in digital healthcare technologies has been leading a revolution in healthcare. It has been showing the enormous potential to improve medical professionals’ ability for accurate diagnosis, disease treatment, and the users’ daily self-care. Since the recent transformation of digital healthcare aims to provide effective personalized health services, Conversational AI (CA) is being highlighted as an easy-to-use and cost-effective means to deliver personalized services. Particularly, CA is gaining attention as a mean for personalized care by ingraining positive self-care behavior in a daily manner while previous methods for personalized care are focusing on the medical context. CA expands the boundary of personalized care by enabling one-to-one tailored conversation to deliver health education and healthcare therapies. Due to CA's opportunities as a method for personalized care, it has been implemented with various types of roles including CA for diagnosis, CA for prevention, and CA for therapy. However, there lacks study on the personalization of healthcare CA to meet user's preferences on the CA's persona. Even though the CASA paradigm has been applied to previous studies designing and evaluating the human-likeness of CA, few healthcare CAs personalize its human-like persona except some CAs for mental health therapy. Moreover, there exists the need to improve user experience by increasing social and emotional interaction between the user and the CA. Therefore, designing an acceptable and personalized persona of CA should be also considered to make users to be engaged in the healthcare task with the CA. In this manner, the thesis suggests an idea of applying the persona of the person who is in a close relationship with the user to the conversational CA for daily healthcare as a strategy for persona personalization. The main hypothesis is the idea of applying a close person's persona would improve user engagement. To investigate the hypothesis, the thesis explores if dynamics derived from the social relationship in the real world can be implemented to the relationship between the user and the CA with the persona of a close person. To explore opportunities and challenges of the research idea, series of studies were conducted to (1) explore appropriate host whose persona would be implemented to healthcare CA, (2) define linguistic characteristics to consider when applying the persona of a close person to the CA, and (3)implement CA with the persona of a close person to major lifestyle domains. Based on findings, the thesis provides design guidelines for healthcare CA with the persona of the real person who is in a close relationship with the user.Abstract 1 1 Introduction 12 2 Literature Review 18 2.1 Roles of CA in Healthcare 18 2.2 Personalization in Healthcare CA 23 2.3 Persona Design CA 25 2.4 Methods for Designing Chatbot’s Dialogue Style 30 2.4.1 Wizard of Oz Method 32 2.4.2 Analyzing Dialogue Data with NLP 33 2.4.3 Participatory Design 35 2.4.4 Crowdsourcing 37 3 Goal of the Study 39 4 Study 1. Exploring Candidate Persona for CA 43 4.1 Related Work 44 4.1.1 Need for Support in Daily Healthcare 44 4.1.2 Applying Persona to Text-based CA 45 4.2 Research Questions 47 4.3 Method 48 4.3.1 Wizard of Oz Study 49 4.3.2 Survey Measurement 52 4.3.3 Post Interview 54 4.3.4 Analysis 54 4.4 Results 55 4.4.1 System Acceptance 56 4.4.2 Perceived Trustfulness and Perceived Intimacy 57 4.4.3 Predictive Power of Corresponding Variables 58 4.4.4 Linguistic Factors Affecting User Perception 58 4.5 Implications 60 5 Study 2. Linguistic Characteristics to Consider When Applying Close Person’s Persona to a Text-based Agent 63 5.1 Related Work 64 5.1.1 Linguistic Characteristics and Persona Perception 64 5.1.2 Language Component 66 5.2 Research Questions 68 5.3 Method 69 5.3.1 Modified Wizard of Oz Study 69 5.3.2 Survey 72 5.4 Results 73 5.4.1 Linguistic Characteristics 73 5.4.2 Priority of Linguistic Characteristics 80 5.4.3 Differences between language Component 82 5.5 Implications 82 6 Study3.Implementation on Lifestyle Domains 85 6.1 Related Work 86 6.1.1 Family as Effective Healthcare Provider 86 6.1.2 Chatbots Promoting Healthy Lifestyle 87 6.2 Research questions 94 6.3 Implementing Persona of Family Member 95 6.3.1 Domains of Implementation 96 6.3.2 Measurements Used in the Study 97 6.4 Experiment 1: Food Journaling Chatbot 100 6.4.1 Method 100 6.4.2 Results 111 6.5 Experiment 2: Physical Activity Intervention 128 6.5.1 Method 131 6.5.2 Results 140 6.6 Experiment 3: Chatbot for Coping Stress 149 6.6.1 Method 151 6.6.2 Results 158 6.7 Implications from Domain Experiments 169 6.7.1 Comparing User Experience 170 6.7.2 Comparing User Perception 174 6.7.3 Implications from Study 3 183 7 Discussion 192 7.1 Design Guidelines 193 7.2 Ethical Considerations 200 7.3 Limitations 206 8 Conclusion 210 References 212 Appendix 252 국문초록 262박

A software based mentor system

This thesis describes the architecture, implementation issues and evaluation of Mentor - an educational support system designed to mentor students in their university studies. Students can ask (by typing) natural language questions and Mentor will use several educational paradigms to present information from its Knowledge Base or from data-mined online Web sites to respond. Typically the questions focus on the student’s assignments or in their preparation for their examinations. Mentor is also pro-active in that it prompts the student with questions such as "Have you started your assignment yet?". If the student responds and enters into a dialogue with Mentor, then, based upon the student’s questions and answers, it guides them through a Directed Learning Path planned by the lecturer, specific to that assessment. The objectives of the research were to determine if such a system could be designed, developed and applied in a large-scale, real-world environment and to determine if the resulting system was beneficial to students using it. The study was significant in that it provided an analysis of the design and implementation of the system as well as a detailed evaluation of its use. This research integrated the Computer Science disciplines of network communication, natural language parsing, user interface design and software agents, together with pedagogies from the Computer Aided Instruction and Intelligent Tutoring System fields of Education. Collectively, these disciplines provide the foundation for the two main thesis research areas of Dialogue Management and Tutorial Dialogue Systems. The development and analysis of the Mentor System required the design and implementation of an easy to use text based interface as well as a hyper- and multi-media graphical user interface, a client-server system, and a dialogue management system based on an extensible kernel. The multi-user Java-based client-server system used Perl-5 Regular Expression pattern matching for Natural Language Parsing along with a state-based Dialogue Manager and a Knowledge Base marked up using the XML-based Virtual Human Markup Language. The kernel was also used in other Dialogue Management applications such as with computer generated Talking Heads. The system also enabled a user to easily program their own knowledge into the Knowledge Base as well as to program new information retrieval or management tasks so that the system could grow with the user. The overall framework to integrate and manage the above components into a usable system employed suitable educational pedagogies that helped in the student’s learning process. The thesis outlines the learning paradigms used in, and summarises the evaluation of, three course-based Case Studies of university students’ perception of the system to see how effective and useful it was, and whether students benefited from using it. This thesis will demonstrate that Mentor met its objectives and was very successful in helping students with their university studies. As one participant indicated: ‘I couldn’t have done without it.

Front Matter - Soft Computing for Data Mining Applications

Efficient tools and algorithms for knowledge discovery in large data sets have been devised during the recent years. These methods exploit the capability of computers to search huge amounts of data in a fast and effective manner. However, the data to be analyzed is imprecise and afflicted with uncertainty. In the case of heterogeneous data sources such as text, audio and video, the data might moreover be ambiguous and partly conflicting. Besides, patterns and relationships of interest are usually vague and approximate. Thus, in order to make the information mining process more robust or say, human-like methods for searching and learning it requires tolerance towards imprecision, uncertainty and exceptions. Thus, they have approximate reasoning capabilities and are capable of handling partial truth. Properties of the aforementioned kind are typical soft computing. Soft computing techniques like Genetic

Data and the city – accessibility and openness. a cybersalon paper on open data

This paper showcases examples of bottom–up open data and smart city applications and identifies lessons for future such efforts. Examples include Changify, a neighbourhood-based platform for residents, businesses, and companies; Open Sensors, which provides APIs to help businesses, startups, and individuals develop applications for the Internet of Things; and Cybersalon’s Hackney Treasures. a location-based mobile app that uses Wikipedia entries geolocated in Hackney borough to map notable local residents. Other experiments with sensors and open data by Cybersalon members include Ilze Black and Nanda Khaorapapong's The Breather, a "breathing" balloon that uses high-end, sophisticated sensors to make air quality visible; and James Moulding's AirPublic, which measures pollution levels. Based on Cybersalon's experience to date, getting data to the people is difficult, circuitous, and slow, requiring an intricate process of leadership, public relations, and perseverance. Although there are myriad tools and initiatives, there is no one solution for the actual transfer of that data