Chaoyu Deng, Guangfu Zeng, Zhiping Cai, Xiaoqiang Xiao^*

Journal on Artificial Intelligence, Vol.2, No.4, pp. 157-166, 2020, DOI:10.32604/jai.2020.011541

Abstract The purpose of automated question answering is to let the machine understand natural language questions and give accurate answers in the form of natural language. This technology requires the machine to store a large amount of background knowledge. In recent years, the rapid development of knowledge graph has made the knowledge based question answering (KBQA) more and more popular. Traditional styles of KBQA methods mainly include semantic parsing, information extraction and vector modeling. With the development of deep learning, KBQA with deep learning has gradually become the mainstream method. This paper introduces the application of deep learning in KBQA mainly… More >

Sabin C. Buraga¹, Octavian Dospinescu^2,*

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2857-2873, 2021, DOI:10.32604/cmc.2021.014429

Abstract A knowledge-driven approach is proposed for assessing the music influence on university students. The proposed method of modeling and conducting the interactive pilot study can be useful to convey other surveys, interviews, and experiments created in various phases of the user interface (UI) design processes, as part of a general human-computer interaction (HCI) methodology. Benefiting from existing semantic Web and linked data standards, best practices, and tools, a microservice-oriented system is developed as a testbed platform able to generate playlists in a smart way according to users’ music preferences. This novel approach could bring also benefits for user interface adaptation… More >

Yichao Zang^1,*, Tairan Hu², Tianyang Zhou², Wanjiang Deng³

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2573-2585, 2021, DOI:10.32604/cmc.2021.012220

Abstract Mining penetration testing semantic knowledge hidden in vast amounts of raw penetration testing data is of vital importance for automated penetration testing. Associative rule mining, a data mining technique, has been studied and explored for a long time. However, few studies have focused on knowledge discovery in the penetration testing area. The experimental result reveals that the long-tail distribution of penetration testing data nullifies the effectiveness of associative rule mining algorithms that are based on frequent pattern. To address this problem, a Bayesian inference based penetration semantic knowledge mining algorithm is proposed. First, a directed bipartite graph model, a kind… More >

Chengrong Yang¹, Rongjing Bu², Yan Kang², Yachuan Zhang², Hao Li^2,*, Tao Li², Junfeng Li²

Journal on Big Data, Vol.2, No.4, pp. 135-144, 2020, DOI:10.32604/jbd.2020.010000

Abstract With the rise of open-source software, the social development paradigm occupies an indispensable position in the current software development process. This paper puts forward a variant of the PageRank algorithm to build the importance assessment model, which provides quantifiable importance assessment metrics for new Java projects based on Java open-source projects or components. The critical point of the model is to use crawlers to obtain relevant information about Java open-source projects in the GitHub open-source community to build a domain knowledge graph. According to the three dimensions of the Java opensource project’s project influence, project activity and project popularity, the… More >

Chuanrong Wu^1,*, Huayi Yin¹, Xiaoming Yang², Zhi Lu³, Mark E. McMurtrey⁴

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1173-1184, 2020, DOI:10.32604/iasc.2020.014961

Abstract Nowadays big data knowledge is being bought and sold online for market research, new product development, or other business decisions, especially when customer demands and consumer preferences knowledge for new product development are needed. Previous studies have introduced two commonly used pricing schemes for big data knowledge transactions (e.g., cloud services): Subscription pricing and pay-per-use pricing from a big data knowledge provider’s standpoint. However, few studies to date have investigated a two-part tariff pricing scheme for big data knowledge transactions, albeit this pricing scheme may increasingly attract the big data knowledge providers in this hyper-competitive market. Also, little research has… More >

Tharam S. Dillon^1,2,∗, Yi-Ping Phoebe Chen^1,†, Elizabeth Chang^2,‡, Mukesh Mohania^3,§, Vish Ramakonar⁴

Computer Systems Science and Engineering, Vol.35, No.5, pp. 321-334, 2020, DOI:10.32604/csse.2020.35.321

Abstract In Digital Enterprises Structured Data and Semi/Unstructured Content are normally stored in two different repositories, with the first often being stored in relational Databases and the second in a content manager which is frequently at an external outsourcer. This storage of complementary information in two different silos has led to the information being processed and data mined separately which is undesirable. Effective knowledge and information use requires seamless access and intelligent analysis of information in its totality to allow enterprises to gain enhanced insights. In this paper, we develop techniques to carry out correlation of the information across different sources… More >

Wuqian Lv¹, Zhifang Liao^1,*, Shengzong Liu², Yan Zhang³

CMC-Computers, Materials & Continua, Vol.66, No.1, pp. 1027-1042, 2021, DOI:10.32604/cmc.2020.012478

Abstract Entity recognition and extraction are the foundations of knowledge graph construction. Entity data in the field of software engineering come from different platforms and communities, and have different formats. This paper divides multi-source software knowledge entities into unstructured data, semi-structured data and code data. For these different types of data, Bi-directional Long ShortTerm Memory (Bi-LSTM) with Conditional Random Field (CRF), template matching, and abstract syntax tree are used and integrated into a multi-source software knowledge entity extraction integration model (MEIM) to extract software entities. The model can be updated continuously based on user’s feedbacks to improve the accuracy. To deal… More >

Qixue Guan^*, Yueqiu Jiang

Intelligent Automation & Soft Computing, Vol.26, No.4, pp. 773-781, 2020, DOI:10.32604/iasc.2020.010112

Abstract It is known that congestion in the reverse direction happens in advance of the congestion in the forward direction due to the significant bandwidth asymmetry in the two directions of the space networks, especially in the satellite networks, which enables the TCP Vegas to enter the phase of the congestion avoidance blindly and reduce the throughput of the forward direction. To solve this problem, a congestion control model, TCP Vegas-DDA, which maintains the frequency of the acknowledgments in the reverse direction is proposed. The model sets the interval time between acknowledgments dynamically based on the variation of the queuing delay… More >

Poomagal C T^1,∗, Sathish kumar G A², Deval Mehta³

Computer Systems Science and Engineering, Vol.35, No.1, pp. 51-63, 2020, DOI:10.32604/csse.2020.35.051

Abstract The burgeoning network communications for multiple applications such as commercial, IoT, consumer devices, space, military, and telecommunications are facing many security and privacy challenges. Over the past decade, the Internet of Things (IoT) has been a focus of study. Security and privacy are the most important problems for IoT applications and are still facing huge difficulties. To promote this high-security IoT domain and prevent security attacks from unauthorized users, keys are frequently exchanged through a public key exchange algorithm. This paper introduces a novel algorithm based on Elliptic Curve Cryptography(ECC) for multi-level Public Key Exchange and Encryption Mechanism. It also… More >

Giuseppe Della Penna^1,∗, Sergio Orefice^2,†

Computer Systems Science and Engineering, Vol.34, No.6, pp. 325-338, 2019, DOI:10.32604/csse.2019.34.325

Abstract In this paper we present a qualitative spatial relation formalism capable to represent spatio-temporal knowledge. To this aim, we have added the notion of time within the formalisation of spatial relations in order to describe moving graphical objects. As a case study, we exploited this augmented formalism to support a qualitative specification of gestures, which are an increasingly relevant issue in the human-computer interaction field. The resulting technique provides gesture specification with a systematic and formal foundation. More >