Survey on Privacy Preservation in Personalized Web Environment

Personalized web search (PWS) is a general category of search techniques aiming at providing different search results for different users or organize search results differently for each user, based upon their interest, preferences and information needs. As the expense, user information has to be collected and analyzed to figure out the user intention behind the issued query. However, users are uncomfortable with exposing private information during search which has become a major barrier for the wide proliferation of PWS. Search engines should provide security mechanism such that user will be ensured of its privacy and its information should be kept safe. Many personalization techniques are giving access to achieve personalization of user’s web search. Search engines can provide more accurate and specific data if users trust search engine and provide more information. But users should be ensured that their private information should be kept safe. In this paper we will discuss on different techniques on personalized web search and securing personalized information. DOI: 10.17762/ijritcc2321-8169.16041

Survey on privacy preservation in personalized web environment

Personalized web search (PWS) is a general category of search techniques aiming at providing different search results for different users or organize search results differently for each user, based upon their interest, preferences and information needs. As the expense, user information has to be collected and analyzed to figure out the user intention behind the issued query. However, users are uncomfortable with exposing private information during search which has become a major barrier for the wide proliferation of PWS. Search engines should provide security mechanism such that user will be ensured of its privacy and its information should be kept safe. Many personalization techniques are giving access to achieve personalization of user’s web search. Search engines can provide more accurate and specific data if users trust search engine and provide more information. But users should be ensured that their private information should be kept safe. In this paper we will discuss on different techniques on personalized web search and securing personalized information. DOI: 10.17762/ijritcc2321-8169.16040

Personalized Search Engine: A Review

Now a days there is A major problem in mobile search is that the interactions between the users and search engines are limited by the small form factors of the mobile devices. As a result, mobile users tend to submit shorter, hence, more ambiguous queries compared to their web search counterparts. In order to return highly relevant results to the users, mobile search engines must be able to profile the users� interests and personalize the search results according to the user�s profiles. A personalized mobile search engine (PMSE) that captures the users� preferences in the form of concepts by mining their click through data. Due to the importance of location information in mobile search, In this paper PMSE classifies these concepts into content concepts and location concepts To characterize the diversity of the concepts associated with a query and their relevance�s to the user�s need, four entropies are introduced to balance the weights between the content and location facets

Integrating Technology With Student-Centered Learning

Reviews research on technology's role in personalizing learning, its integration into curriculum-based and school- or district-wide initiatives, and the potential of emerging digital technologies to expand student-centered learning. Outlines implications

Time-Sensitive User Profile for Optimizing Search Personlization

International audienceThanks to social Web services, Web search engines have the opportunity to afford personalized search results that better fit the user’s information needs and interests. To achieve this goal, many personalized search approaches explore user’s social Web interactions to extract his preferences and interests, and use them to model his profile. In our approach, the user profile is implicitly represented as a vector of weighted terms which correspond to the user’s interests extracted from his online social activities. As the user interests may change over time, we propose to weight profiles terms not only according to the content of these activities but also by considering the freshness. More precisely, the weights are adjusted with a temporal feature. In order to evaluate our approach, we model the user profile according to data collected from Twitter. Then, we rerank initial search results accurately to the user profile. Moreover, we proved the significance of adding a temporal feature by comparing our method with baselines models that does not consider the user profile dynamics

A Context-Aware Search System for Smart Phones Based on Context-Aware Infrastructure

The major objectives behind designing the context-aware architecture are to: i) collect the mobile user’s context information, ii) derive a meaningful & a usable current context from user’s accumulated context information, iii) replicate and/or distribute this current context information among the context-aware systems and thereby, support building a context-aware platform that delivers search results which are closer to the user’s current context & are more specifically tailored for user’s current search semantics. The user’s context information is maintained & updated at the server, so as to reuse it across different context aware backend providers. The process of context reasoning, itself takes place at the application level. By implementing context-aware architectures, applications can derive user context profiles. Such user context profiles can be integrated with the 3rd party search providers like, Yahoo search engine or the ones plugged into the platform to meet the users’ demands for the services and products they are searching for around

Local Ranking Problem on the BrowseGraph

The "Local Ranking Problem" (LRP) is related to the computation of a centrality-like rank on a local graph, where the scores of the nodes could significantly differ from the ones computed on the global graph. Previous work has studied LRP on the hyperlink graph but never on the BrowseGraph, namely a graph where nodes are webpages and edges are browsing transitions. Recently, this graph has received more and more attention in many different tasks such as ranking, prediction and recommendation. However, a web-server has only the browsing traffic performed on its pages (local BrowseGraph) and, as a consequence, the local computation can lead to estimation errors, which hinders the increasing number of applications in the state of the art. Also, although the divergence between the local and global ranks has been measured, the possibility of estimating such divergence using only local knowledge has been mainly overlooked. These aspects are of great interest for online service providers who want to: (i) gauge their ability to correctly assess the importance of their resources only based on their local knowledge, and (ii) take into account real user browsing fluxes that better capture the actual user interest than the static hyperlink network. We study the LRP problem on a BrowseGraph from a large news provider, considering as subgraphs the aggregations of browsing traces of users coming from different domains. We show that the distance between rankings can be accurately predicted based only on structural information of the local graph, being able to achieve an average rank correlation as high as 0.8

A state of art survey on zz-structures

Zz-structures are particular data structures capable of representing both hypertextual information and contextual interconnections among different information. The focus of this paper is to stimulate new research on this topic, by providing, in a state of the art survey, a short description and comparison of all the material that, to the best of our knowledge, is related to zz-structures: informal and formal descriptions, implementations, languages, demonstrations, projects and applitudes of zz-structures; in fact, despite their large use in different fields, the literature lacks of an exhaustive and up-to-date description of them

Human genetics and genomics research in Ecuador: historical survey, current state, and future directions

Background: In South America, the history of human genetics is extensive and its beginnings go back to the onset of the twentieth century. In Ecuador, the historical record of human genetics and genomics research is limited. In this context, our work analyzes the current status and historical panorama of these fields, based on bibliographic searches in Scopus, Google Scholar, PubMed, and Web of Science. Results: Our results determined that the oldest paper in human genetics coauthored by an Ecuadorian institution originates from the Central University of Ecuador in 1978. From a historical standpoint, the number of articles has increased since the 1990s. This growth has intensified and it is reflected in 137 manuscripts recorded from 2010 to 2019. Areas such as human population genetics, phylogeography, and forensic sciences are the core of genetics and genomics-associated research in Ecuador. Important advances have been made in the understanding of the bases of cancer, some genetic diseases, and congenital disorders. Fields such as pharmacogenetics and pharmacogenomics have begun to be explored during the last years. Conclusions: This work paints a comprehensive picture and provides additional insights into the future panorama of human genetic and genomic research in Ecuador as an example of an emerging, resource-limited country with interesting phylogeographic characteristics and public health implications