A Semiotic-Based Approach for Search in Social Network Services

2012 ◽  
pp. 137-151
Author(s):  
Júlio C. dos Reis ◽  
Rodrigo Bonacin ◽  
M. Cecília C. Baranauskas
Keyword(s):  
Social Network ◽  
Semantic Web ◽  
Network Services ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Search Results ◽  
Search Mechanism ◽  
Common Interests ◽  
Social Network Services ◽  
Organizational Semiotics

Search mechanisms in Social Network Services (SNSs) should take into account the meanings created, shared, and used by people through the use of the system. This paper investigates a new approach to develop search mechanisms more adequate for SNSs. SNSs represent an opportunity for people access to information in the Web. These systems allow individuals to constitute communities of common interests with wide cultural diversity, sharing information and vocabularies. The search mechanism proposed in this paper is grounded in Semantic Web technologies combined and articulated with Organizational Semiotics methods and artifacts. The authors illustrate a process to create the ontology and techniques to improve semantic search results in SNSs using Semantic Web Rule Language. The paper discusses the practical and technological results that could be achieved using the proposed approach.

A Semiotic-Based Approach for Search in Social Network Services

2011 ◽  
Vol 3 (3) ◽  
pp. 27-40
Author(s):  
Júlio C. dos Reis ◽  
Rodrigo Bonacin ◽  
M. Cecília C. Baranauskas
Keyword(s):  
Social Network ◽  
Semantic Web ◽  
Network Services ◽  
Semantic Web Technologies ◽  
New Approach ◽  
Web Technologies ◽  
Search Mechanism ◽  
Common Interests ◽  
Social Network Services ◽  
Organizational Semiotics

Search mechanisms in Social Network Services (SNSs) should take into account the meanings created, shared, and used by people through the use of the system. This paper investigates a new approach to develop search mechanisms more adequate for SNSs. SNSs represent an opportunity for people access to information in the Web. These systems allow individuals to constitute communities of common interests with wide cultural diversity, sharing information and vocabularies. The search mechanism proposed in this paper is grounded in Semantic Web technologies combined and articulated with Organizational Semiotics methods and artifacts. The authors illustrate a process to create the ontology and techniques to improve semantic search results in SNSs using Semantic Web Rule Language. The paper discusses the practical and technological results that could be achieved using the proposed approach.

Semantic Web Technologies in the Recruitmant Domain

2007 ◽  
pp. 299-318 ◽  
Author(s):  
Ralf Heese ◽  
Malgorzata Mochol ◽  
Radoslaw Oldakowski
Keyword(s):  
Semantic Web ◽  
Human Resource ◽  
Search Engines ◽  
Matching Function ◽  
Job Seekers ◽  
Recruitment Process ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Search Results ◽  
Job Offers

Due to the large number of job offers published online it is almost impossible for job seekers and job portals to gain an overview of the entire employment market. Since job offers lack semantically meaningful annotations, their location and integration into databases is extremely difficult. In this paper, we demonstrate how the application of Semantic Web technologies, can enable unambiguous identification of concepts and relationships between concepts, to the e-recruitment process provides advantages for all participants in the market. When comparing job and applicant profiles, this abovementioned identification through the use of a dedicated matching function is a key element for increasing the precision of search results provided by search engines. Furthermore, it allows for automating and supporting recruitment processes. In this chapter, we present an application scenario and our prototypical implementation discussing the construction of a human resource ontology for annotating job offers and job applications and our matching function.

scholarly journals Knowledge-Oriented Tool Complex Processing Databases of Scientific Publications

2020 ◽  
pp. 17-33
Author(s):  
Оlexander V. Palagin ◽  
◽  
Мykola G. Petrenko ◽  
Keyword(s):  
Information Retrieval ◽  
Semantic Web ◽  
Scientific Article ◽  
Multimedia Presentation ◽  
Scientific Publications ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Search Results ◽  
New Knowledge ◽  
Instrumental Complex

Introduction. Nowadays, numerous applications and tools are known that implement information retrieval technologies in various text sources in accordance with specified parameters. Moreover, the search results are provided to the user for each search parameter individually and not related to each other. And the application of Semantic Web technologies for the purpose of multi-parameter and related information retrieval in various sources in Ukraine is at the initial stage of development. A separate problem is the multimedia presentation of search results and their comparison with the conceptual structure of the domain of interest (Knowledge Domain) with the goal of extracting new knowledge. From this point of view, it is relevant for scientific research to process the scientific publications of one author, authors of a scientific unit and the academic institute as a whole, using the Semantic Web technologies, multimedia presentation of information, and effective support for the process of extracting new knowledge. Purpose. Designing the architecture and functioning algorithms of the instrumental complex for processing databases of scientific publications, as well as developing examples of using a formal description of a scientific article with a number of queries. Methods. The methods and models used in this work are based on Semantic Web information technologies focused on the development and use of subject ontologies. Ontologies are the basic components of these technologies both for conducting scientific research and creating large databases, including scientific publications of the authors. Results. The architecture of the instrumental complex for processing databases of scientific publications and the algorithms for its functioning at the preparatory and main stages have been developed. Examples of queries to the database of scientific publications that demonstrate the performance of IR are given. Conclusion. The article discusses the architecture of the instrumental complex for processing databases of scientific publications and the algorithms for its functioning at the preparatory and main stages. The steps of the preparatory phase, which are implemented by the knowledge engineer, are examined in detail. At the same time, the creation of two ontology models of the scientific article with the presentation of the corresponding ontographs was highlighted: the CRF-model describes the concepts contained in the article, and the OWL-model describes the structural components of the article. In conclusion, examples of queries to the databases of scientific publications are presented, demonstrating the performance of the instrumental complex. Further, it is necessary to expand the use in the development of IR technologies, such as cognitive semantics and graphics, multimedia presentation of information, focused on the effective support of the processes of extraction and/or generation of new knowledge.

Semantic Web Technologies for e-Learning: Models and Implementation

Informatica ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 221-240 ◽  
Author(s):  
Valentina Dagienė ◽  
Daina Gudonienė ◽  
Renata Burbaitė
Keyword(s):  
Semantic Web ◽  
Learning Models ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
E Learning

scholarly journals An Information Recommendation Technique Based on Influence and Activeness of Users in Social Networks

2021 ◽  
Vol 11 (6) ◽  
pp. 2530
Author(s):  
Minsoo Lee ◽  
Soyeon Oh
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Recommendation Systems ◽  
Network Services ◽  
The Past ◽  
User Behaviors ◽  
User Influence ◽  
User Activity ◽  
Information Recommendation ◽  
Social Network Services

Over the past few years, the number of users of social network services has been exponentially increasing and it is now a natural source of data that can be used by recommendation systems to provide important services to humans by analyzing applicable data and providing personalized information to users. In this paper, we propose an information recommendation technique that enables smart recommendations based on two specific types of analysis on user behaviors, such as the user influence and user activity. The components to measure the user influence and user activity are identified. The accuracy of the information recommendation is verified using Yelp data and shows significantly promising results that could create smarter information recommendation systems.

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