Website Content Management System

Authors(2) :-B. Sankari, S. Ajikumar

Bug Tracking, Help Desk Ticketing, issue raising, search facility, help information, issue resolution. Issues related to software projects can be raised, tracked and resolved by Employees of different departments. Resolved issues can be allowed to access from Knowledge Base as Knowledge elements. The different groups and representatives can interact each other through emails.The issue tracking system does all the jobs that are done in conventional system but ,here , everything is done in more formal and efficient manner. All the users of organization can interact with each other through the Issue Tracking System. This system acts as an interface between the employees thereby enabling them to forward their issues to the centralized Issue tracking system. Hence, making the work easy for both the issue raiser and the resolved. It totally avoids the involvement of middlemen in getting resolution for a particular issue.The Issue Tracking system is an intranet application, which provides information about issues in software projects, in detail. This product develops a system that can be used by all the departments of a software organization. In the conventional method, all the issues are dealt manually .The progress of the issues are also checked in person, which is a tedious task. Here, in Issue Tracking, it fulfills different requirements of administrator and employees of a software development organization efficiently. The specific purpose of the system is to gather and resolve issues that arise in different projects handled by the organization.

Authors and Affiliations

B. Sankari
Department of M.Sc (Software Engineering), PSN College of Engineering & Technology, Tirunelveli, Tamilnadu, India}Department of M.Sc (Software Engineering), PSN College of Engineering & Technology, Tirunelveli, Tamilnadu, India
S. Ajikumar
Department of M.Sc (Software Engineering), PSN College of Engineering & Technology, Tirunelveli, Tamilnadu, India}Department of M.Sc (Software Engineering), PSN College of Engineering & Technology, Tirunelveli, Tamilnadu, India

Network, data, Local area Network, Transmission control protocol, Internet Protocol.

  1. DBLP computer science bibliography.
  2. IMDB movie database.
  3. Query templates.
  4. G. Adomavicius and A. Tuzhilin. Toward the next generation of recommender systems: A survey of the state-of-the-art and possible extensions. TKDE, 17(6):734–749, 2005.
  5. R. Agrawal, R. Rantzau, and E. Terzi. Context-sensitive ranking. In SIGMOD, pages 383–394, 2006.
  6. R. Agrawal and E. L. Wimmers. A framework for expressing and combining preferences. In SIGMOD, pages 297–306, 2000.
  7. A. Arvanitis and G. Koutrika. PrefDB: Bringing preferences closer to the DBMS. In SIGMOD, pages 665–668, 2012.
  8. A. Arvanitis and G. Koutrika. Towards preference-aware relational databases. In ICDE, pages 426–437, 2012.
  9. S. Borzs ¨ onyi, D. Kossmann, and K. Stocker. The skyline operator. ¨ In ICDE, pages 421–430, 2001.
  10. J. Chomicki. Preference formulas in relational queries. TODS, 28(4):427–466, 2003.
  11. V. Christophides, D. Plexousakis, M. Scholl, and S. Tourtounis. On labeling schemes for the semantic web. In WWW, pages 544–555, 2003.
  12. W. W. Cohen, R. E. Schapire, and Y. Singer. Learning to order things. J. Artif. Intell. Res. (JAIR), 10:243–270, 1999.
  13. R. Fagin, A. Lotem, and M. Naor. Optimal aggregation algorithms for middleware. In PODS, pages 102–113, 2001.
  14. P. Georgiadis, I. Kapantaidakis, V. Christophides, E. M. Nguer, and N. Spyratos. Efficient rewriting algorithms for preference queries. In ICDE, pages 1101–1110, 2008.
  15. S. Holland, M. Ester, and W. Kießling. Preference mining: A novel approach on mining user preferences for personalized applications. In PKDD, pages 204–216, 2003.
  16. I. F. Ilyas, W. G. Aref, and A. K. Elmagarmid. Supporting top-k join queries in relational databases. In VLDB, pages 754–765, 2003.
  17. T. Joachims. Optimizing search engines using clickthrough data. In KDD, pages 133–142, 2002.
  18. W. Kießling. Foundations of preferences in database systems. In VLDB, pages 311–322, 2002.
  19. W. Kießling and G. Kostler. Preference SQL - design, implementation, experiences. In VLDB, pages 990–1001, 2002.
  20. G. Koutrika and Y. E. Ioannidis. Personalization of queries in database systems. In ICDE, pages 597–608, 2004.
  21. M. Lacroix and P. Lavency. Preferences: Putting more knowledge into queries. In VLDB, pages 217–225, 1987.
  22. J. Levandoski, M. Mokbel, and M. Khalefa. FlexPref: A framework for extensible preference evaluation in database systems. In ICDE, pages 828–839, 2010.
  23. C. Li, K. C.-C. Chang, I. F. Ilyas, and S. Song. RankSQL: Query algebra and optimization for relational top-k queries. In SIGMOD, pages 131–142, 2005.
  24. C. Mishra and N. Koudas. Stretch ’n’ shrink: Resizing queries to user preferences. In SIGMOD, pages 1227–1230, 2008.
  25. P. G. Selinger, M. M. Astrahan, D. D. Chamberlin, R. A. Lorie, and T. G. Price. Access path selection in a relational database management system. In SIGMOD, pages 23–34, 1979.
  26. K. Stefanidis, E. Pitoura, and P. Vassiliadis. Adding context to preferences. In ICDE, pages 846–855, 2007.

Publication Details

Published in : Volume 2 | Issue 2 | March-April 2017
Date of Publication : 2017-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 313-317
Manuscript Number : CSEIT172281
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

B. Sankari, S. Ajikumar, "Website Content Management System", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 2, pp.313-317, March-April-2017.
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