Intelligent Answering Research Articles

UPCYCLING FOR REPURPOSING WASTE INTO CREATIVE PRODUCTS

Upcycling is the process of repurposing non-used materials or products to make them more valuable or usable, with increased quality and value. However, truly little research has been conducted on the design process and/or creative ideation of upcycling in order to produce higher-quality and more valuable products. This study presents the four stages of the design process, consisting of selecting the waste products, emerging conceptions, generating ideas, and rendering a series of creative ideas. SCAMPER (substitute, combine, adjust, modify, put to other uses, eliminate, reverse), one of the practical and effective techniques to create various creative ideas, was applied in the stages of emerging conceptions and generating ideas. With the upcycling concept of waste product design utilizing SCAMPER, the results demonstrated that waste soft drink cans could be converted into five creative products: a desk watch, a picture frame, a spring paper clip, a pencil holder, and a lamp. The five products featured the upcycling of waste soft drink cans, removing the need to recycle or send them to landfills at that point in their lifecycle. Consideration was given to the design process’ compatibility with creative concept generation and design. The study indicated that upcycling should be viewed as an essential component of waste management and repurposing in order to provide an intelligent answer to escalating product waste problems.

Key Technologies of Intelligent Question-Answering System for Power System Rules and Regulations Based on Improved BERTserini Algorithm

With the continuous breakthrough of natural language processing, the application of intelligent question-answering technology in electric power systems has attracted wide attention. However, at present, the traditional question-answering system has poor performance and is difficult to apply in engineering practice. This paper proposes an improved BERTserini algorithm for the intelligent answering of electric power regulations based on a BERT model. The proposed algorithm is implemented in two stages. The first stage is the text-segmentation stage, where a multi-document long text preprocessing technique is utilized that accommodates the rules and regulations text, and then Anserini is used to extract paragraphs with high relevance to the given question. The second stage is the answer-generation and source-retrieval stage, where a two-step fine-tuning based on the Chinese BERT model is applied to generate precise answers based on given questions, while the information regarding documents, chapters, and page numbers of these answers are also output simultaneously. The algorithm proposed in this paper eliminates the necessity for the manual organization of professional question–answer pairs, thereby effectively reducing the manual labor cost compared to traditional question-answering systems. Additionally, this algorithm exhibits a higher degree of exact match rate and a faster response time for providing answers.

A Schematic Review of Knowledge Reasoning Approaches Based on the Knowledge Graph

In the contemporary world, the Internet technology and its implementation mode are advancing at a swift pace, leading to an exponential growth in the scale of Internet data. This data contains a significant amount of valuable knowledge. The effective organization and articulation of knowledge, as well as the ability to conduct thorough calculations and analyses, have garnered significant attention and developments within a particular environmental context. The utilization of knowledge graphs for knowledge reasoning has emerged as a prominent area of focus within the realm of knowledge graph research. It holds substantial significance in the realm of vertical search, intelligent answering, and various other applications. This article will be centered on fundamental principles of reasoning. The approach of knowledge reasoning oriented towards knowledge graphs is focused on the derivation of novel knowledge or the detection of erroneous knowledge through the utilization of pre-existing knowledge. In contrast to conventional knowledge reasoning approaches, the knowledge reasoning technique employed in knowledge graphs is characterized by greater diversity, owing to the succinct, adaptable, and flexible representation of knowledge.

KinRob: An ontology based robot for solving kinematic problems

Intelligent answering technology, which enables computers to solve problems automatically, is often used to develop tutorial systems, and has a wide range of application prospects. However, due to the lack of linguistic analysis and understanding methods, there are few researches on intelligent algorithms for solving kinematics problems. Developing such an algorithm is challenging, because solving kinematics problems is a complex task that includes text understanding, problem analysis, and automatic solution. To understand all these complexities involved in kinematics problems requires background knowledge. And only when an automatic solver contains a powerful internal knowledge representation system can it perform these tasks. We, thus, develop KinRob, an tutorial system for solving kinematics problems by combining neural network and ontology. Firstly, we propose an ontology for KinRob, which defines the knowledge of kinematics, and can help the robot understand a kinematics problem. Secondly, to match the text in natural language with the ontology, we propose a novel tagging scheme based on the kinematic problem understanding model in named entity recognition (NER). Finally, extensive experiments are conducted, and the experimental results show that the performance of the proposed method on a dataset of kinematic problems from authoritative sources better than the baseline algorithms.

Design and Research of Artificial Intelligence in Multimedia Intelligent Question-Answering System and Self-Test System

With the development of computer science and technology, online education is gradually accepted by more and more users, and has become one of the main teaching methods in schools under the influence of the epidemic in recent years. In addition, online vocational education or higher education has also captured the psychology of national learning, and online tutoring has gradually entered into nonstudent groups such as office workers. Although online education has the advantages of low cost and no limitation of time and space, it also has some problems, such as low classroom satisfaction, delayed feedback from students, and poor teaching effect. Therefore, this paper aims at this problem by combining the development background of foreign intelligent answer system and self-test system, and introducing it into our computer application, using artificial intelligence for natural language processing, aiming at online teaching students cannot get timely answer, and self-test questions intelligent system design. The final experimental results show that the system effectively alleviates the problems of students’ delay in answering questions and poor self-test effect, and increases the satisfaction of online classroom by 13%.

Intelligent question and answer analysis model of power ICT based on BI-LSTM-CRF

With the deepening of the country’s digital transformation and the development of big data artificial intelligence software definition and other technologies, customers’ demand for IT services is constantly increasing. In the electric power industry, the front-end knowledge base for traditional customer service lacks self-learning ability, the accumulated customer service data in the middle cannot be analyzed and utilized effectively, the back-end quality inspection was not fully covered and lacked emotion recognition, etc. Apply artificial intelligence, information and communication technology and big data technology to power ICT customer service. It is proposed to construct a network model by combining conditional random airport with the long- and short-term memory neural network, and to realize the intelligent customer service model combined with human–computer interaction by constructing an intelligent knowledge base and the information system fault association analysis model, so as to improve the extraction performance of context information and establish a knowledge base question answering system in the field of power service. Through the comparative analysis of experimental data, the proposed model has achieved good results and can be effectively applied to the power industry to improve customer service satisfaction.

Ontological approach to Chinese text processing

To implement natural language user interface and an intelligent answer to questions, the knowledgebased semantic model for Chinese language processing is proposed. The article gives careful consideration to the existing methods and various knowledge bases for natural language processing. The analysis of these methods has led to the conclusion that in natural language processing, the knowledge base is the most fundamental and crucial part. The knowledge base makes it possible to ensure processing of a natural language based on initially described knowledge and to explain the processing operations. By virtue of the analysis of various methods for constructing knowledge bases about the English and Chinese languages, an ontological approach to the Chinese language processing was proposed. The Chinese language processing model has two main aspects: the design of knowledge base about the Chinese language and the development of ontology-based knowledge processing machine. The proposed approach is aimed at developing a semantic model of knowledge on the Chinese language. As a stage in the implementation of the approach, I designed the ontology of the Chinese language that can be applied for further processing of the language. This paper considers the preliminary version of the ontology and the principle of building a knowledge base about the Chinese language. There are no uniform standards and evaluation system for designing an ontology. Expansion, refinement and evaluation of the ontology require further research.

DPAEG: A Dependency Parse-Based Adversarial Examples Generation Method for Intelligent Q&A Robots

Recently, the natural language processing- (NLP-) based intelligent question and answer (Q&A) robots have been used ubiquitously. However, the robustness and security of current Q&A robots are still unsatisfactory, e.g., a slight typo in the user’s question may cause the Q&A robot unable to return the correct answer. In this paper, we propose a fast and automatic test dataset generation method for the robustness and security evaluation of current Q&A robots, which can work in black-box scenarios and thus can be applied to a variety of different Q&A robots. Specifically, we propose a dependency parse-based adversarial examples generation (DPAEG) method for Q&A robots. DPAEG first uses the proposed dependency parse-based keywords extraction algorithm to extract keywords from a question. Then, the proposed algorithm generates adversarial words according to the extracted keywords, which include typos and words that are spelled similarly to the keywords. Finally, these adversarial words are used to generate a large number of adversarial questions. The generated adversarial questions which are similar to the original questions do not affect human’s understanding, but the Q&A robots cannot answer these adversarial questions correctly. Moreover, the proposed method works in a black-box scenario, which means it does not need the knowledge of the target Q&A robots. Experiment results show that the generated adversarial examples have a high success rate on two state-of-the-art Q&A robots, DrQA and Google Assistant. In addition, the generated adversarial examples not only affect the correct answer (top-1) returned by DrQA but also affect the top-k candidate answers returned by DrQA. The adversarial examples make the top-k candidate answers contain fewer correct answers and make the correct answers rank lower in the top-k candidate answers. The human evaluation results show that participants with different genders, ages, and mother tongues can understand the meaning of most of the generated adversarial examples, which means that the generated adversarial examples do not affect human’s understanding.

Survey on Intelligent Answering System using Similarity Model based Learning

Survey on Intelligent Answering System using Similarity Model based Learning

Implementation of the Intelligent Question Answering System Based on Remote Service Framework

Remote answering system of modern distance education system is an indispensable component. However, the current system is based on answering user input on the exam questions simple keyword matching, accuracy and query the user interface cannot meet the needs of users. We have designed a semantic network theory to build up intelligent answering system. We analyzed the necessity of establishing intelligent answering system, and presents a model of intelligent question answering system based on its technology defined areas, and two university computer courses as a source of knowledge to achieve the function of the system. The results show that the proposed method can improve the accuracy of the query, user-friendly and convenient. System Based on J2EE three-tier system, in the middle layer of the advanced MVC design pattern thought to achieve page display and business logic separation, improve system maintainability.

Research and Implementation of Intelligent Question Answering System in MOOC

Massive Online Open Course which based on Open Educational Resource might be the most effective method to large-scale quality education, which can realize passive learning to active learning. Analyzing the status and shortages of Intelligent Answering System, propose and design an intelligent question answering system based on agent-model. System use software agents to implement and improve MOOC system’s Intelligent Answering System performance, which has capacity of natural language processing, and good versatility. It can provide an efficient online problem answer environment for thousands of learners, and can effectively promote students' autonomous learning and self-development.

Research and Implementation of Intelligent Question Answering System in MOOC

Massive Online Open Course which based on Open Educational Resource might be the most effective method to large-scale quality education, which can realize passive learning to active learning. Analyzing the status and shortages of Intelligent Answering System, propose and design an intelligent question answering system based on agent-model. System use software agents to implement and improve MOOC system’s Intelligent Answering System performance, which has capacity of natural language processing, and good versatility. It can provide an efficient online problem answer environment for thousands of learners, and can effectively promote students' autonomous learning and self-development.

From CD-ROM to the WWW: Coming Full Circle

This article describes the challenges faced and solutions adopted in adapting a multimedia-rich CD-ROM program, the Variétés de français program, to operation over the World Wide Web (WWW). While full web functionality offered the promise of flexible network distribution, it also had to confront the dual limitations of multimedia authoring systems and web based programming. In seeking to combine the best of full multimedia programming and centralized WWW mediated delivery, the Variétés de français-WWW program has come full circle to the CD-ROM for its base. The program runs locally to retrieve media resources, perform intelligent answer processing, and data collection and turns to the web only when necessary for data transfer, external WWW links, and electronic communication. Given the current state of the art, the article concludes that such a hybrid solution offers the most effective approach to courseware development.

A knowledge infrastructure for intelligent query answering in location-based services

Intelligent query answering in Location-based Services refers to their capability to provide mobile users with personalized and contextualized answers. Personalization is expected to lead to answers that better match user's interests, as inferable from the user's profile. Contextualization aims at not selecting answers that for some reason would not be appropriate at the time and place of the user query. These goals are beyond the current state of art in LBS, or are provided based on ad hoc solutions specific to the application at hand. This paper reports on the results of an investigation aiming at defining the knowledge infrastructure that should be developed within the LBS to make it capable of returning intelligent answers. We first discuss the data management features that make LBS different from other query answering systems. Next we propose a data infrastructure that builds on the idea of modular ontologies. We explain how the relevant knowledge may be incrementally set up and dynamically maintained based on an application-independent approach. Last we show how this knowledge is used to reformulate user's queries via personalized and contextualized rewriting.

Intelligent answering location questions from the web using molecular alignment

In this paper, a new molecular alignment based recognition method for question answering from from the Web is proposed. This identifies locations using an molecular alignment sequence algorithm according to their similarity with a user natural-language question. Different experiments and results concerning questions on locations are discussed. The high accuracy of the proposed alignment strategy shows the promise of approach to effectively deal with questions extracted from natural-language corpus which contain many complex patterns.

Why Study Mathematics

Why should anyone study mathematics? This type of question is not peculiar to mathematics nor to the field of education. Let us look at a corresponding situation in the field of business. Suppose an automobile salesman attempts to sell a car, what are some of the questions he has to answer? The buyer wants to know the make of the car and compares it with other makes from the standpoint of beauty, service, and economy. Before the sale can be made the salesman must present convincing argument on all of these points and surely no real salesman will attempt such a task without being thoroughly familiar with the car himself. While the analogy may not be complete from the case of the automobile salesman to that of the teacher of mathematics, yet it is certainly true that the teachers of mathematics are primarily the ones who should be able to “sell” mathematics to the “doubting public.” There are two questions that every mathematics teacher should be able to answer if he is to be able to give an intelligent answer to the one already proposed: they are “What is mathematics?” and “What relation does mathematics have to the cultural, industrial, and recreational activities of a progressive civilization?”

Geo-branding, are we talking nonsense? A theoretical reflection on brands applied to places

The geo-brand concept (branding applied to places) has been attacked by different sectors of society, and using branding techniques in regions and countries has been seen as sacrilegious. Nevertheless, in the present case the arguments that are used to attack the geo-brand concept are flawed and should be reviewed. The geo-brand is not a creation of ‘clever’ entrepreneurs but it is a result of changes in society. Branding places does not equate with the commercialisations of local culture, but with the protection and promotion of diversity. The geo-brand concept can be seen as an intelligent answer for local sustainable development.

Sunflowers

Sunflowers

Providing Approximate Answers Using a Knowledge Abstraction Database

As database users adopt a query language to obtain information from a database, a more intelligent query answering system is increasingly needed. Relational databases are exact in nature, but effectiveness of decision support would improve significantly if the query answering system returns approximate answers rather than a null information response when there is no matching data available. This paper proposes an abstraction hierarchy as a framework to practically derive such approximate answers from ordinary everyday databases. It provides a knowledge abstraction database to facilitate the approximate query answering. The knowledge abstraction database specifically adopts an abstraction approach to extract semantic data relationships from the underlying database, and uses a multi-level hierarchy for coupling multiple levels of abstraction knowledge and data values. In cooperation with the underlying database, the knowledge abstraction database allows the relaxation of query conditions so that the original query scope can be broadened and thus information approximate to exact answers can be obtained. Conceptually abstract queries can also be posed to provide a less rigid query interface. A prototype system has been implemented at KAIST and is being tested with a personnel database system to demonstrate the usefulness and practicality of the knowledge abstraction database in ordinary database systems.

A Man of the Book

A Homily Preached in Memory of Fr Leonard Boyle OP On the Feast of St Thomas Aquinas At Blackfriars, OxfordWhen news of Fr Leonard’s death reached Canada, Michael Attridge, a young doctorate student at the Pontifical Medieval Institute where Leonard had taught for many years, immediately sent a letter of condolence to the convent of the Master at Santa Sabina. In his letter, Michael spoke of his first and only visit to the Vatican Library where he found himself overwhelmed by Leonard’s kindness: “Fr Leonard offered to give me a tour of the library ... Our tour culminated with a visit to the beautifully frescoed Salone Sistino. Fr Boyle took me around to each of the paintings of the various ecumenical councils of the Church. At the end he asked me a question that I’ll never forget—he asked me what was the common feature in each of the paintings. As I struggled, by reviewing all the paintings, to give an intelligent answer to his question, he simply and quietly said with a smile—‘It’s the Book, Michael’. I looked up at the walls and there in the centre of each of the paintings surrounded by the council fathers, was the Bible. He continued: ‘The Book is always at the very heart of the Church’s activity and life—never forget that’.”I have always instinctively thought of Leonard as a man of the Book, and not only because of his enormous talent as a paleographer. Most of the times, in fact, when I heard him speaking in Rome, in public, he was preaching the Gospel.