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.

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.

scholarly journals A Prototype of Speech Interface Baed on Google Cloud Platform to Access a Semantic Website

2018 ◽  
Author(s):  
Jimmy Aurelio Rosales-Huamani ◽  
José Luis Castillo-Sequera ◽  
Juan Carlos Montalvan-Figueroa ◽  
Joseps Andrade-Choque
Keyword(s):  
Semantic Web ◽  
Good Alternative ◽  
Cloud Platform ◽  
Semantic Web Technologies ◽  
New Approach ◽  
Web Technologies ◽  
Speech Interface ◽  
Web Tools ◽  
Java Program ◽  
Extract Information

The main restriction of the Semantic Web is the difficult of the SPARQL language, that is necessary to extract information from the Knowledge Representation also known as ontology. Making the Semantic Web accessible for people who do not know SPARQL, is essential the use of friendlier interfaces and a good alternative is Natural Language. This paper shows the implementation of a friendly prototype interface to query and retrieve, by voice, information from website building with the Semantic Web tools. In that way, the end users avoid the complicated SPARQL language. To achieve this, the interface recognizes a speech query and converts it into text, it processes the text through a java program and identifies keywords, generates a SPARQL query, extracts the information from the website and read it in voice, for the user. In our work Google Cloud Speech API makes Speech-to-Text conversions and Text-to Speech conversions are made with SVOX Pico. As results, we have measured three variables: The success rate in queries, the response time of query and a usability survey. The values of the variables allows the evaluation of our prototype. Finally the interface proposed provides us a new approach in the problem, using the Cloud like a Service, reducing barriers of access to the Semantic Web for people without technical knowledge of Semantic Web technologies.

AVATAR: ENHANCING THE PERSONALIZED TELEVISION BY SEMANTIC INFERENCE

2007 ◽  
Vol 21 (02) ◽  
pp. 397-421 ◽  
Author(s):  
YOLANDA BLANCO FERNÁNDEZ ◽  
JOSÉ J. PAZOS ARIAS ◽  
ALBERTO GIL SOLLA ◽  
MANUEL RAMOS CABRER ◽  
MARTÍN LÓPEZ NORES ◽  
...  
Keyword(s):  
Semantic Web ◽  
Digital Tv ◽  
End Users ◽  
Semantic Web Technologies ◽  
New Approach ◽  
Web Technologies ◽  
Semantic Inference ◽  
Wide Acceptance ◽  
Content Recommendation ◽  
Recommendation Accuracy

The generalized arrival of Digital TV will lead to a significant increase in the amount of channels and programs available to end users, making it difficult to find interesting programs among a myriad of irrelevant contents. Thus, in this field, automatic content recommenders should receive special attention in the following years to improve assistance to users. Current approaches of content recommenders have significant well-known deficiencies that hamper their wide acceptance. In this paper, a new approach for automatic content recommendation is presented that considerably reduces those deficiencies. This approach, based on the so-called Semantic Web technologies, has been implemented in the AVATAR tool, a hybrid content recommender that makes extensive use of well-known standards, such as TV-Anytime and OWL. Our proposal has been evaluated experimentally with real users, showing significant increases in the recommendation accuracy with respect to other existing approaches.

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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