Wan Tao^a,b, Tao Liu^a,b

Intelligent Automation & Soft Computing, Vol.24, No.1, pp. 65-72, 2018, DOI:10.1080/10798587.2016.1267243

Abstract With the explosive growth of various social media applications, individuals and organizations are increasingly using their contents (e.g. reviews, forum discussions, blogs, micro-blogs, comments, and postings in social network sites) for decision-making. These contents are typical big data. Opinion mining or sentiment analysis focuses on how to extract emotional semantics from these big data to help users to get a better decision. That is not an easy task, because it faces many problems, such as different context may make the meaning of the same word change variously, at the same time multilingual environment restricts the full use of the analysis… More >

Zhang Min, Teng Haibin, Jiang Ming, Wen Tao, Tang Jingfan

Intelligent Automation & Soft Computing, Vol.25, No.3, pp. 625-635, 2019, DOI:10.31209/2019.100000117

Abstract Mapping from sentence phrases to knowledge graph resources is an important step for applications such as search engines, automatic question answering systems based on acknowledge base and knowledge graphs. The existing solution maps a simple phrase to a knowledge graph resource strictly or approximately from the text. However, it is difficult to detect phrases and map the composite semantic resource. This paper proposes a longest matching resource mapping scheme to solve this problem, namely, to find the longest substring in a sentence that can match the knowledge base resource. Based on this scheme, we propose an optimization algorithm based on… More >

Yonghong Xie^{1, 3}, Liangyuan Hu^{1, 3}, Xingxing Chen^{2, 3}, Jim Feng⁴, Dezheng Zhang^{1, 3, *}

CMC-Computers, Materials & Continua, Vol.65, No.1, pp. 481-494, 2020, DOI:10.32604/cmc.2020.010297

Abstract As one of the most valuable assets in China, traditional medicine has a long history and contains pieces of knowledge. The diagnosis and treatment of Traditional Chinese Medicine (TCM) has benefited from the natural language processing technology. This paper proposes a knowledge-based syndrome reasoning method in computerassisted diagnosis. This method is based on the established knowledge graph of TCM and this paper introduces the reinforcement learning algorithm to mine the hidden relationship among the entities and obtain the reasoning path. According to this reasoning path, we could infer the path from the symptoms to the syndrome and get all possibilities… More >

Fulian Yin, Yanyan Wang, Jianbo Liu^*, Meiqi Ji

CMES-Computer Modeling in Engineering & Sciences, Vol.124, No.2, pp. 747-764, 2020, DOI:10.32604/cmes.2020.010579

Abstract Word similarity (WS) is a fundamental and critical task in natural language processing. Existing approaches to WS are mainly to calculate the similarity or relatedness of word pairs based on word embedding obtained by massive and high-quality corpus. However, it may suffer from poor performance for insuf- ficient corpus in some specific fields, and cannot capture rich semantic and sentimental information. To address these above problems, we propose an enhancing embedding-based word similarity evaluation with character-word concepts and synonyms knowledge, namely EWS-CS model, which can provide extra semantic information to enhance word similarity evaluation. The core of our approach contains… More >

Ning Chen¹, Hui Li², Xinxin Fan^{3, 4}, Weiliang Kong¹, Yonghong Xie^{3, 4, *}

Journal on Artificial Intelligence, Vol.2, No.3, pp. 149-155, 2020, DOI:10.32604/jai.2020.09888

Abstract In recent years, there are some problems in science and technology management, such as untimely task supervision and independent information system, which makes it difficult to achieve accurate, quantitative and standardized management. The storage of scientific research test data is scattered, and there are many deficiencies in the management, promotion and use of existing intellectual property. In this paper, on the basis of the knowledge economy, intelligence economy under the conditions of knowledge management concept and cutting-edge technology, technology management and service management related data, information, knowledge, method of blend together. Based on science and technology management, knowledge management as… More >

Hangjun Zhou¹, Tingting Shen^{1, *}, Xinglian Liu¹, Yurong Zhang¹, Peng Guo^{1, 2}, Jianjun Zhang³

Journal on Artificial Intelligence, Vol.2, No.2, pp. 89-101, 2020, DOI:10.32604/jai.2020.09968

Abstract With the advent of the era of big data, knowledge engineering has received extensive attention. How to extract useful knowledge from massive data is the key to big data analysis. Knowledge graph technology is an important part of artificial intelligence, which provides a method to extract structured knowledge from massive texts and images, and has broad application prospects. The knowledge base with semantic processing capability and open interconnection ability can be used to generate application value in intelligent information services such as intelligent search, intelligent question answering and personalized recommendation. Although knowledge graph has been applied to various systems, the… More >

Brett Snodgrass, Aruna Chilakala

Congenital Heart Disease, Vol.12, No.5, pp. 647-648, 2017, DOI:10.1111/chd.12522

Abstract This article has no abstract. More >

Elise D. Pieterman^1,2, Ricardo P. J. Budde², Danielle Robbers-Visser^1,2, Ron T. van Domburg³, Willem A. Helbing^1,2

Congenital Heart Disease, Vol.12, No.5, pp. 561-569, 2017, DOI:10.1111/chd.12484

Abstract Objective: Follow-up of right ventricular performance is important for patients with congenital heart disease. Cardiac magnetic resonance imaging is optimal for this purpose. However, observerdependency of manual analysis of right ventricular volumes limit its use. Knowledge-based reconstruction is a new semiautomatic analysis tool that uses a database including knowledge of right ventricular shape in various congenital heart diseases. We evaluated whether knowledge-based reconstruction is a good alternative for conventional analysis.
Design: To assess the inter- and intra-observer variability and agreement of knowledge-based versus conventional analysis of magnetic resonance right ventricular volumes, analysis was done by two observers in a mixed… More >

Joshua Saef¹, Sandeep Sodhi¹, Kristen M. Tecson², Vanessa al Rashida¹, Jong Mi Ko², Kamila S. White³, Philip A. Ludbrook¹, Ari M. Cedars⁴

Congenital Heart Disease, Vol.13, No.6, pp. 967-977, 2018, DOI:10.1111/chd.12668

Abstract Objective: Growth in the adults with congenital heart disease (ACHD) population represents a challenge to the health care infrastructure. As patients with chronic disease are increasingly held accountable for their own care, contributors to disease‐ specific health knowledge, which are known to correlate with patients’ participation in care, merit investigation to design patient‐focused interventions.
Design: We conducted a single‐site, cross‐sectional study of ACHD patients. Investigators retrospectively gathered clinical data as well as psychometric and health status assessments completed at the time of enrollment.
Outcome Measures: We investigated the impact of clinical and psychological varia‐ bles on Leuven Knowledge Questionnaire for… More >

Paul C. Helm¹, Sebastian Kempert², Marc-André Körten¹, Wiebke Lesch³, Katharina Specht³, Ulrike M. M. Bauer^1,3

Congenital Heart Disease, Vol.13, No.3, pp. 377-383, 2018, DOI:10.1111/chd.12581

Abstract Background: Children and adolescents with congenital heart disease (CHD) and their families require qualified combined medical and psychosocial information, care, and counseling. This study aimed to analyze CHD patients’ and parents’ perception of disease-specific knowledge, state of health, and impairments experienced in everyday life, as well as factors influencing these perceptions.
Materials and Methods: Analyses were based on a survey among patients/parents recruited via the German National Register for Congenital Heart Defects (NRCHD). The total sample (N = 818) was divided into four groups: “Children” (176 patients), “Adolescents” (142 patients), “Adults” (269 patients), and “Parents” (231 parents). The patients were… More >