An intelligent approach for the design and development of a personalized system of knowledge representation

Abstract This article proposes a generic presentation system for hypermedia systems of adaptive teaching that is highly independent from the representation of domain knowledge and the application state maintenance. Generality is achieved by providing an application framework for the definition of ontologies that best fit a domain or a specific author. The presentation of the pages to be generated is described in terms of classes and relationships of the ontology. For this purpose, a web page ranking algorithm based on automatic learning is used, specifically, the algorithm for Advanced Cluster Vector Page Ranking (ACVPR). This algorithm provides the user a powerful meta-search tool that presents a ranking order of the web page to quickly meet custom needs, especially when the search is erroneous or incomplete.

[1]  Motomichi Toyama,et al.  Automatic Determination of Hyperlink Destination in Web Index , 2015, IDEAS.

[2]  Sharvari V. Malthankar,et al.  Client Side Privacy Protection Using Personalized Web Search , 2016 .

[3]  O. P. Rishi,et al.  An Innovative Approach of Web Page Ranking Using Hadoop- and Map Reduce-Based Cloud Framework , 2018 .

[4]  Amelec Viloria,et al.  Conglomerates of Latin American Countries and Public Policies for the Sustainable Development of the Electric Power Generation Sector , 2018, DMBD.

[5]  Mansaf Alam,et al.  Labeling of Web Search Result Clusters Using Heuristic Search and Frequent Itemset , 2015 .

[6]  Chao Li,et al.  A Semantic++ Social Search Engine Framework in the Cloud , 2012, 2012 Eighth International Conference on Semantics, Knowledge and Grids.

[7]  Panagiotis Adamopoulos.  On discovering non-obvious recommendations: using unexpectedness and neighborhood selection methods in collaborative filtering systems , 2014, WSDM.

[8]  Amelec Viloria,et al.  Analysis of Patterns in the University World Rankings Webometrics, Shanghai, QS and SIR-SCimago: Case Latin America , 2018, DMBD.

[9]  Paola Salomoni,et al.  Automatic web content personalization through reinforcement learning , 2016, J. Syst. Softw..

[10]  Dong Zhou,et al.  An iterative method for personalized results adaptation in cross-language search , 2018, Inf. Sci..

[11]  Enhong Chen,et al.  Context-aware ranking in web search , 2010, SIGIR '10.

[12]  O. P. Rishi,et al.  An intelligent approach to design of E-Commerce metasearch and ranking system using next-generation big data analytics , 2018 .

[13]  Amelec Viloria,et al.  Methodology for the Design of a Student Pattern Recognition Tool to Facilitate the Teaching - Learning Process Through Knowledge Data Discovery (Big Data) , 2018, DMBD.

[14]  O. P. Rishi,et al.  IMSS: A Novel Approach to Design of Adaptive Search System Using Second Generation Big Data Analytics , 2017 .

[15]  Amelec Viloria,et al.  Application of Classification Technique of Data Mining for Employee Management System , 2018, DMBD.

[16]  Yang Liu,et al.  Ranking products through online reviews: A method based on sentiment analysis technique and intuitionistic fuzzy set theory , 2017, Inf. Fusion.

[17]  C. L. Philip Chen,et al.  Data-intensive applications, challenges, techniques and technologies: A survey on Big Data , 2014, Inf. Sci..

[18]  Hakim Hacid,et al.  PerSaDoR: Personalized social document representation for improving web search , 2016, Inf. Sci..

[19]  Sheue-Ling Hwang,et al.  An improved Web search engine for visually impaired users , 2011, Universal Access in the Information Society.

[20]  Mohammad Najmud Doja,et al.  Enumerative feature subset based ranking system for learning to rank in presence of implicit user feedback , 2017, J. King Saud Univ. Comput. Inf. Sci..

[21]  Hongwei Liu,et al.  Privacy calculus and its utility for personalization services in e-commerce: An analysis of consumer decision-making , 2017, Inf. Manag..

[22]  O. P. Rishi,et al.  IMSS-E: An Intelligent Approach to Design of Adaptive Meta Search System for E Commerce Website Ranking , 2016 .