scholarly journals Requirements for Personal Information Agents in the Semantic Web

2003 ◽  
pp. 260-265 ◽  
Author(s):  
Wolfgang Woerndl
Keyword(s):  
Semantic Web ◽  
Personal Information ◽  
Information Agents

scholarly journals Privacy And Web 3.0: Implementing Trust and Learning from Social Networks

2018 ◽  
Vol 10 (4) ◽  
pp. 16
Author(s):  
George Bouchagiar
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Semantic Web ◽  
Web 2.0 ◽  
Personal Information ◽  
Personal Data ◽  
New Era ◽  
Web 3.0 ◽  
Data Portability ◽  
Privacy Risks

After having shifted from Web 1.0 to Web 2.0, scientists welcome the advent of Web 3.0, an environment where meaning is added to data. While in the Semantic Web people are no longer users, but part of the emerging applications, producers, subjects and beneficiaries of the Big Data, however, opaque processing of personal data poses tremendous risks and dangers for individuals. Given the new era of Big Data this paper studies firms’ purposes and practices to detect some emerging privacy risks. Moreover, theories that deal with social networks are examined to conclude that, even if people state that they value their privacy, however, they often disclose a huge volume of personal information. Taking into account that today’s European concept of privacy is conceptualized in negative terms this paper also proposes the implementation of trust and loyalty into the privacy concept through flexible fiduciary laws. Furthermore, data portability is discussed to detect its potential as a strategic feature, a key tool that will enhance trust. Finally, further scenarios and proposals are submitted, in our attempt to answer the question whether the European concept of privacy could be re-shaped for the benefit of individuals.

User profiling in personal information agents: a survey

2005 ◽  
Vol 20 (4) ◽  
pp. 329-361 ◽  
Author(s):  
DANIELA GODOY ◽  
ANALIA AMANDI
Keyword(s):  
State Of The Art ◽  
Personal Information ◽  
Relevant Information ◽  
User Profiling ◽  
The Internet ◽  
User Profiles ◽  
Amount Of Information ◽  
Information Agents ◽  
Personal Agents ◽  
Intelligent Information

Personal information agents have emerged in the last decade to help users to cope with the increasing amount of information available on the Internet. These agents are intelligent assistants that perform several information-related tasks such as finding, filtering and monitoring relevant information on behalf of users or communities of users. In order to provide personalized assistance, personal agents rely on representations of user information interests and preferences contained in user profiles. In this paper, we present a summary of the state-of-the-art in user profiling in the context of intelligent information agents. Existing approaches and lines of research in the main dimensions of user profiling, such as acquisition, learning, adaptation and evaluation, are discussed.

CONTEXT AWARE PERSONAL INFORMATION AGENTS

2002 ◽  
Vol 11 (03n04) ◽  
pp. 245-264 ◽  
Author(s):  
JOSEP LLUÍS ARCOS ◽  
ENRIC PLAZA
Keyword(s):  
Information Search ◽  
Context Awareness ◽  
Personal Information ◽  
Relevant Information ◽  
Context Aware ◽  
Information Spaces ◽  
Information Agent ◽  
Windows Of Opportunity ◽  
Information Agents ◽  
Specific Interests

We present a society of personal information agents that work for a community of users and that are aware of the physical and social context of their users. We show how context-awareness is a feature that allows the agents to improve their performance when they work with limited resources in information spaces with a large amount of information. The use of context information allows the agents to focus their information search and, as a result of this, increase the quantity and quality of information delivered to the user. Moreover, we propose an implemented agent architecture with context-aware capabilities. We discuss this architecture in detail, focusing on the capability of exploiting the windows of opportunity provided by the awareness of the users' activity. The agents use these windows of opportunity to furnish the user with information and advice in the situation where it can be most useful. In particular, we show how context-aware information agents can assist a community of attendees to big conferences and fairs. In this application, an information agent gathers relevant information based on a model of specific interests of a user. Given the multiplicity of interesting events, and their distribution in time and space, an information agent has to deliver the gathered information in a few hours and comply to the schedule constraints. Finally, we report some experimentation results to illustrate how context-awareness improve the service a society of information agents provides to a community of users in the conference application.

scholarly journals Privacy And Web 3.0: Implementing Trust and Learning from Social Networks

2018 ◽  
Vol 10 (4) ◽  
pp. 1632
Author(s):  
George Bouchagiar
Keyword(s):  
Social Networks ◽  
Big Data ◽  
Semantic Web ◽  
Web 2.0 ◽  
Personal Information ◽  
Personal Data ◽  
New Era ◽  
Web 3.0 ◽  
Data Portability ◽  
Privacy Risks

After having shifted from Web 1.0 to Web 2.0, scientists welcome the advent of Web 3.0, an environment where meaning is added to data. While in the Semantic Web people are no longer users, but part of the emerging applications, producers, subjects and beneficiaries of the Big Data, however, opaque processing of personal data poses tremendous risks and dangers for individuals. Given the new era of Big Data this paper studies firms’ purposes and practices to detect some emerging privacy risks. Moreover, theories that deal with social networks are examined to conclude that, even if people state that they value their privacy, however, they often disclose a huge volume of personal information. Taking into account that today’s European concept of privacy is conceptualized in negative terms this paper also proposes the implementation of trust and loyalty into the privacy concept through flexible fiduciary laws. Furthermore, data portability is discussed to detect its potential as a strategic feature, a key tool that will enhance trust. Finally, further scenarios and proposals are submitted, in our attempt to answer the question whether the European concept of privacy could be re-shaped for the benefit of individuals.

COLLABORATIVE WEB SEARCH BASED ON USER INTEREST SIMILARITY

2008 ◽  
Vol 17 (04) ◽  
pp. 495-521 ◽  
Author(s):  
DANIELA GODOY ◽  
ANALÍA AMANDI
Keyword(s):  
Recommender System ◽  
Web Search ◽  
Personal Information ◽  
Empirical Evaluation ◽  
User Interest ◽  
Agent Based ◽  
Information Agents ◽  
Personal Agents ◽  
Interest Similarity ◽  
The Web

The motivation behind personal information agents resides in the enormous amount of information available on the Web, which has created a pressing need for effective personalized techniques. In order to assists Web search these agents rely on user profiles modeling information preferences, interests and habits that help to contextualize user queries. In communities of people with similar interests, collaboration among agents fosters knowledge sharing and, consequently, potentially improves the results of individual agents by taking advantage of the knowledge acquired by other agents. In this paper, we propose an agent-based recommender system for supporting collaborative Web search in groups of users with partial similarity of interests. Empirical evaluation showed that the interaction among personal agents increases the performance of the overall recommender system, demonstrating the potential of the approach to reduce the burden of finding information on the Web.

The Threat Detection Framework for Securing Semantic Web Services

2019 ◽  
Vol 16 (12) ◽  
pp. 5099-5104
Author(s):  
Nagendra Kumar Singh ◽  
Sandeep Kumar Nayak
Keyword(s):  
Access Control ◽  
Semantic Web ◽  
Business Processes ◽  
Web Applications ◽  
Personal Information ◽  
Data Extraction ◽  
Database Systems ◽  
Threat Detection ◽  
External Threats ◽  
Security Structure

Security is a necessary aspect of modern life for organizations and individuals who use the semantic web to provide various services. Semantic web applications are being used as a portal to communicate with back-end database systems and to support business processes. The confidential and personal information of any organization is stored on these systems. Access Control ensures that the requesting user has to meet certain criteria to access these systems. In most cases, it has been observed that access control only provides protection against external threats. There is no provision for detecting internal attacks. Therefore, there is a need for a mechanism that can be able to detect the malicious behaviour of previously authorized users. This paper proposes two algorithms to detect anomalous behaviour performed by the legitimate insider. During training phase, the first algorithm will create the query signature of each incoming query submitted by the legitimate insider. It also estimates the amount of data that can be extracted by the submitted query and includes in the query signature. The second algorithm will detect incongruous data extraction from the database by comparing the current query signature with the previous signature. If both signatures are identical, the query is considered safe for execution. Otherwise, the query will be considered as threat. In this paper, efforts are being made to give details of the security structure on the semantic web service.

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