Construction of power marketing user knowledge graph based on $\text{BERT}+\text{BILSTM}+\text{CRF}$ model

Author(s):  
Tong Zhao ◽  
Ke-He Wu
Author(s):  
Maunendra Sankar Desarkar ◽  
Sandip Bhaumik ◽  
Sailesh K Sathish ◽  
Satnam Singh ◽  
Ranga V Narayanan

Author(s):  
Fuhua Shang ◽  
Qiuyu Ding ◽  
Ruishan Du ◽  
Maojun Cao ◽  
Huanyu Chen

The analysis of user behavior provides a large amount of useful information. After being extracted, this information is called user knowledge. User knowledge plays a guiding role in implementing user-centric updates for software platforms. A good representation and application of user knowledge can accelerate the development of a software platform and improve its quality. This paper aims to further the utilization of user knowledge by mining the user knowledge that is implicit in user behavior and then constructing a knowledge graph of this behavior. First, the association between a software bug and a software component is mined from the user knowledge. Then, the knowledge entity extraction and relationship extraction are performed from the development code and the user behavior. Finally, the knowledge is stored in the graph database, from which it can be visually retrieved. Relevant experiments on CIFLog, an integrated logging processing software platform, have proved the effectiveness of this research. Constructing a user behavior knowledge graph can improve the utilization of user knowledge as well as the quality of software platform development.


2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Suzanna Schmeelk ◽  
Lixin Tao

Many organizations, to save costs, are movinheg to t Bring Your Own Mobile Device (BYOD) model and adopting applications built by third-parties at an unprecedented rate.  Our research examines software assurance methodologies specifically focusing on security analysis coverage of the program analysis for mobile malware detection, mitigation, and prevention.  This research focuses on secure software development of Android applications by developing knowledge graphs for threats reported by the Open Web Application Security Project (OWASP).  OWASP maintains lists of the top ten security threats to web and mobile applications.  We develop knowledge graphs based on the two most recent top ten threat years and show how the knowledge graph relationships can be discovered in mobile application source code.  We analyze 200+ healthcare applications from GitHub to gain an understanding of their software assurance of their developed software for one of the OWASP top ten moble threats, the threat of “Insecure Data Storage.”  We find that many of the applications are storing personally identifying information (PII) in potentially vulnerable places leaving users exposed to higher risks for the loss of their sensitive data.


2019 ◽  
Author(s):  
Jemmy Wiratama
Keyword(s):  

I'm an Science & Technology enthusiast. I still learn how to build a knowledge graph and how to write a paper.


Author(s):  
A-Yeong Kim ◽  
◽  
Hee-Guen Yoon ◽  
Seong-Bae Park ◽  
Se-Young Park ◽  
...  

2020 ◽  
Vol 36 (2) ◽  
pp. 97-111
Author(s):  
Stanislava Gardasevic

Purpose This paper presents the results of a qualitative study that involved students of an interdisciplinary PhD program. The study objective was to gather requirements to create a knowledge graph information system. The purpose of this study was to determine information-seeking practices and information needs of this community, to inform the functionalities of a proposed system, intended to help students with relevant resource discovery and decision-making. Design/methodology/approach The study design included semi-structured interviews with eight members of the community, followed by a website usability study with the same student participants. Findings Two main information-seeking styles are recognized and reported through user personas of international and domestic (USA) students. The findings show that the useful information resides within the community and not so much on the program website. Students rely on peer communication, although they report lack of opportunities to connect. Students’ information needs and information seeking are dependent on their progress through the program, as well as their motivation and the projected timeline. Practical implications Considering the current information needs and practices, a knowledge graph hosting both information on social networks and the knowledge produced by the activities of the community members would be useful. By recording data on their activities (for example, collaboration with professors and coursework), students would reveal further useful system functionalities and facilitate transfer of tacit knowledge. Originality/value Aside from the practical value of this research that is directly influencing the design of a system, it contributes to the body of knowledge on interdisciplinary PhD programs.


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