This literature review presents the History, Technology, and Applications of Natural Dialog Systems or simply chatbots. It aims to organize critical information that is a necessary background for further research activity in the field of chatbots. More specifically, while giving the historical evolution, from the generative idea to the present day, we point out possible weaknesses of each stage. After we present a complete categorization system, we analyze the two essential implementation technologies, namely, the pattern matching approach and machine learning. Moreover, we compose a general architectural design that gathers critical details, and we highlight crucial issues to take into account before system design. Furthermore, we present chatbots applications and industrial use cases while we point out the risks of using chatbots and suggest ways to mitigate them. Finally, we conclude by stating our view regarding the direction of technology so that chatbots will become really smart.

Chatbots: History, technology, and applications

Intelligent conversational agents have been implemented as virtual assistants in mobile applications to facilitate, engage, and interact with users for optimal learning experiences. With 24/7 availability, providing instant and consistent responses, chatbots, as a type of intelligent conversational agent, will help benefit the learning communication, makes the entire learning experience more engaging for the learners. They have also been successfully used by the elderly to encourage behavioral change for their intended purpose. This study investigated baseline data on the use of digital platforms of senior citizens in Bangkok Metropolitan and the six regions of Thailand and developed a chatbot from the derived data. The chatbot contained learning media and service function, served as a platform to enhance digital literacy for the senior citizens in Thailand. The study was conducted in 3 phases, the baseline survey on the use of digital platforms of the senior citizens in Thailand, the development of the chatbot and learning media, and the pre-experimental expert validation. The samples were 422 senior citizens. The data were collected by questionnaires, focused group discussion, and interviews with experts, and analyzed by percentage, mean, standard deviation, and content analysis. Results were incorporated in the design and development of the chatbot innovation following the software development life cycle (SDLC) framework. Expert feedback revealed that this chatbot innovation was easy to access, convenient to request for operations, artistically appealing, and comprehensive in content and functionality for enhancing digital literacy skills, which are to access, analyze, evaluate, participate, and act. In the next research sequence, this innovation will subsequently be experimented with more senior citizens to prepare and improve their digital competence to consequently equip them with the necessary capacities to keep up with Thailand's transition towards a full-blown aging society. 

/pdf/enhancing-digital-literacy-with-an-intelligent-3hb3h35n.pdf

Enhancing digital literacy with an intelligent conversational agent for senior citizens in Thailand

An academic integrity policy usually specifies the university’s ethical principles and values, the forms of appropriate academic behaviour, the penalties for academic malpractice and the procedures for handling policy violations. However, the policy does not itself create academic integrity, but needs to be consistently and effectively communicated, implemented, and applied. This paper presents a case study investigating the extent to which students at Riga Technical University (Latvia) are informed about the university’s academic integrity policy. This quantitative research was performed by surveying two groups of respondents: domestic students in the first year of their bachelor’s studies and the heads of the corresponding study programmes. The results revealed a low level of students’ awareness of the university policy on academic integrity and a lack of systematic institutional approach to promoting academic integrity. The study results also indicated that students with a higher awareness of the university policy on academic integrity were less tolerant towards violations and perceived academic integrity as an essential aspect for both the academic community and student life. These findings establish a foundation for a more extensive discussion of academic integrity issues in Latvia. They can also serve as impetus for similar studies in other Latvian universities, as well as research taking an international comparative perspective.

/pdf/students-awareness-of-the-academic-integrity-policy-at-a-5gipa5i7sf.pdf

Students’ awareness of the academic integrity policy at a Latvian university

Software as a Service

Financial risk is an essential indicator of investment, which can help investors to understand the market and companies better. Among the many influencing factors of financial risk, researchers find the earnings conference call is the most significant one. Predicting financial volatility after the earnings conference call has been critical to beneficiaries, including investors and company managers. However, previous work mainly focuses on the feature extraction from the word-level or documentlevel. The vital structure of conferences, the alternate dialogue, is ignored. In this paper, we introduced our Multi-Round Q&A Attention Network, which brings into account the dialogue form in the first place. Based on the data of earnings call transcripts, we apply our model to extract features of each round of dialogue through a bidirectional attention mechanism and predict the volatility after the earnings conference call events. The results prove that our model significantly outperforms the previous state-of-the-art methods and other baselines in three different periods.

/pdf/financial-risk-prediction-with-multi-round-q-a-attention-l25bfgip05.pdf

Financial Risk Prediction with Multi-Round Q&A Attention Network.

While researching integration aspects of cloud Business Process Management Systems (BPMS) with on-premises applications, authors have identified various scenarios that cannot be effectively addressed using existing integration solutions and patterns. Mobile Agents (MAs) were proposed as the technology addressing these integration challenges [30]. During the research, existing MA platforms were analyzed what led to conclusion that none of them is fully addressing specific requirements of end-users in BPM scenarios. The main concern was related to agent development experience - in existing platforms it is required that user creating an agent has at least some understanding of programming concepts. In addition, authors have identified that there is no standard approach for packaging agents that is used across platforms. To address these issues new approach for designing and executing mobile agents is proposed. This approach is based on workflows and enables end-users having no programming skills to design MAs what is critical in BPM scenarios. In addition, a new approach for packaging mobile agents is proposed. It is based on industry used standards and open specifications. Proposed approach is extendable and may be reused for designing and/or packaging MAs in other domains as well.

Workflow based approach for designing and executing mobile agents

While researching integration aspects of cloud Business Process Management Systems (BPMS) with on-premises applications, authors have identified various scenarios that cannot be effectively addressed using existing integration solutions and patterns. Mobile Agents (MAs) were proposed as the technology addressing these integration challenges [1]. During the research, existing MA platforms were analyzed what led to conclusion that none of them is fully addressing specific requirements of end-users in BPM scenarios. As a result, a new approach for designing and executing mobile agents was proposed. This approach is based on workflows and enables end-users having no programming skills to design MAs what is critical in BPM scenarios [2]. In addition existing researches cover different scenarios of how intelligent agents can be used in BPM space, however these do not address specific aspects of MA integration with cloud BPMS, what is critical for proposed solution. During analysis of this subject, authors have identified required integration components, and are proposing an algorithm that allows to determine how these components should be implemented based on technical specification of cloud BPMS. AgentWF prototype provides a sample implementation of all components, and demonstrates how MA system should be integrated with cloud BPMS using proposed approach. Proposed approach is extendable and may be reused for integrating MAs with cloud systems in other domains as well.

Integrating workflow-based mobile agents with cloud businessprocess management systems

Mobile Agents for Integrating Cloud-Based Business Processes with On-Premises Systems and Devices.

In previous papers the present authors have covered personalized study planning framework, and also have implemented study planning system (SPS) prototype, which allows to create a personalized study program, and then to plan the course learning, setting the courses in the required sequence, and make structure analysis thus detecting the most significant nodes in the graph structure. In this paper authors describe the application of eight common graph visualization algorithms — Tree, Circular, EfficientSugiyama Fruchterman-Reingold — FR, BoundedFR, ISOM, Kamada — Kawai — KK; LinLog — for representing study plans and course structures in the personalized study planning system.

Suitability analysis of graph visualization algorithms for personalized study planning

The planning of individual studies becomes more and more topical. Alongside the fast and diverse rhythm of life, people need individual approach to study planning. It ensures wider availability of learning for different social groups. The use of information and communication technologies (ICT) in the process of studies makes it more attractive and more interesting as well as more adequate to the demands of the 21st century. The authors have developed graph based framework for personalization of education process based on the set of four graphs representing the structure of the study programme, the structure of the study courses, the concept maps, and the learning objects [1, 2, 3, 4, 5]. Special tool is needed which allows the learners themselves to design the learning strategy corresponding to their interests. The authors had already implemented personalized study planning process in a prototype, which allows to create a personalized study programme, and then to plan the course learning, setting the courses in the required sequence [3, 4, 5]. In this paper the authors propose the use of the methods of structure analysis to calculate the ranks for the node of the graphs thus detecting the most significant nodes in the graph structure. The calculations for the ranks are made for the graph of the study programme, for the graph of study courses, and for the concept maps. The calculation of ranks for the graph nodes allows detecting the most significant courses in the study programme, the most important topics in the study course and the most essential concepts in the concept map

/pdf/new-approach-of-using-structural-modelling-for-personalized-57s5lip2jb.pdf

New Approach of Using Structural Modelling for Personalized Study Planning

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