Relevant Feedback Based Accurate and Intelligent Retrieval on Capturing User Intention for Personalized Websites

Relevant Feedback Based Accurate and Intelligent Retrieval on Capturing User Intention for Personalized Websites

Relevant Feedback Based Accurate and Intelligent Retrieval on Capturing User Intention for Personalized Websites
Relevant Feedback Based Accurate and Intelligent Retrieval on Capturing User Intention for Personalized Websites

ABSTRACT:

With the rapid growth of networking, cyber_physical_social systems (CPSSs) provide vast amounts of information. Aimed at the huge and complex data provided by networking, obtaining valuable information to meet precise search needs when capturing user intention has become a major challenge, especially in personalized websites. General search engines face difficulties in addressing the challenges brought by this exploding amount of information. In this paper, we use real-time location and relevant feedback technology to design and implement an efficient, configurable, and intelligent retrieval framework for personalized websites in CPSSs. To improve the retrieval results, this paper also proposes a strategy of implicit relevant feedback based on click-through data analysis, which can obtain the relationship between the user query conditions and retrieval results. Finally, this paper designs a personalized PageRank algorithm including modified parameters to improve the ranking quality of the retrieval results using the relevant feedback from other users in the interest group. Experiments illustrate that the proposed accurate and intelligent retrieval framework improves the user experience.

SYSTEM REQUIREMENTS:

HARDWARE REQUIREMENTS: 

  • System : Pentium Dual Core.
  • Hard Disk : 120 GB.
  • Monitor : 15’’ LED
  • Input Devices : Keyboard, Mouse
  • Ram : 1 GB

SOFTWARE REQUIREMENTS: 

  • Operating system : Windows 7.
  • Coding Language : JAVA/J2EE
  • Tool : Netbeans 7.2.1
  • Database : MYSQL

REFERENCE:

YAYUAN TANG, HAO WANG, KEHUA GUO, YIZHE XIAO, AND TAO CHI, “Relevant Feedback Based Accurate and Intelligent Retrieval on Capturing User Intention for Personalized Websites”, IEEE Access,2018.