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The heterogeneity and the increasing amount of the news published on the web create challenges in accessing them. In the authors' previous studies, they introduced a semantic web-based sports news aggregation system called BKSport, which manages to generate metadata for every news item. Providing an intuitive and expressive way to retrieve information and exploiting the advantages of semantic search technique is within their consideration. In this paper, they propose a method to transform natural language questions into SPARQL queries, which could be applied to existing semantic data. This method is mainly based on the following tasks: the construction of a semantic model representing a question, detection of ontology vocabularies and knowledge base elements in question, and their mapping to generate a query. Experiments are performed on a set of questions belonging to various categories, and the results show that the proposed method provides high precision.

DBpedia is a community project upon extracting information from Wikipedia and standardize this data with Semantic Web and Linked Data principles. Therefore, it is a large-scale knowledge base and considered as one of the currently emerging heated issues in the subject of Semantic Web. Moreover, thanks to the development of DBpedia community, many more opportunities are created in the Linked Open Data (LOD) area. These lead to giving birth to the specific DBPedia chapters in different languages. However, there are many languages that do have not their own chapters including Vietnamese. The reason is that the extraction procedure of DBpedia requires manual mappings which match Wikipedia templates to corresponding types and properties of DBpedia ontology. Thus, in this paper, we describe how to identify automatically types for Vietnamese entities as the first step toward building the Vietnamese DBpedia chapter.

This paper focuses on describing the process of building a linked open data repository for presenting tourist resources, which presently contains more than 100,000 places in big cities of Vietnam. This information is extracted and integrated from various sources on the Internet, which are famous social networks or tourism websites, for example, Booking.com, Mytour, Vinalo, etc. These massive and heterogeneous materials would be described via a semantic knowledge base presented in RDF/XML format that is accessible by SPARQL query. Concentrating in studying the concept of linked open data with its publishing processes, this work adjusts and improves the repository to become a standardized linked open data and allows it connect with other famous ontology such as DBpedia.

Purpose – The purpose of this paper is to propose an automatic method to generate semantic annotations of football transfer in the news. The current automatic news integration systems on the Web are constantly faced with the challenge of diversity, heterogeneity of sources. The approaches for information representation and storage based on syntax have some certain limitations in news searching, sorting, organizing and linking it appropriately. The models of semantic representation are promising to be the key to solving these problems. Design/methodology/approach – The approach of the author leverages Semantic Web technologies to improve the performance of detection of hidden annotations in the news. The paper proposes an automatic method to generate semantic annotations based on named entity recognition and rule-based information extraction. The authors have built a domain ontology and knowledge base integrated with the knowledge and information management (KIM) platform to implement the former task (name...

Based on extracting information from Wikipedia, DBpedia is a large scale knowledge base and makes this one available using Semantic Web and Linked Data principles. Thanks to crowd-sourcing, it currently covers multiples domains in multilingualism. Knowledge is obtained from different Wikipedia editions by effort of contributors around the world. Their goal is to manually generate mappings Wikipedia templates into DBpedia ontology classes (types). However, this cause makes the type inconsistency for an entity among different languages. As a result, the quality of data in DBpedia can be affected. In this paper, we present the statement of type consistency for an entity in multilingualism. As a solution for this problem, we propose a method to predict the entity type based on a novel conformity measure. We also evaluate our method based on database extracted from aggregating multilingual resources and compare it with human perception in predicting type for an entity. The experimental result shows that our method can suggest informative types and outperforms the baselines.

The rapid development of mobile computing, social network and smart phones have led to a surge in photograph data. Efficient exploiting, searching and reusing this data have become a problem gaining increasing concerns. However, current systems are still encountering many challenges from the differences in perceiving the meaning of a photograph between human and machines. Among many different approaches, semantic web has recently been proven to be robust enough to overcome these challenges. In this paper, we propose the semantic web approach to develop a system which reduces above differences by accommodating an additional layer that annotates metadata with the original photo to describe important and useful information for the user in both content and context semi automatically. We use a mobile application that connects with a semantic web application. With above solution, the interaction of user of the photograph system becomes simple, friendly and quickly more than ever.

This paper presents the process of building a semantic search application in the field of the Vietnamese history. In particular, the design of ontology in the field of history will come up with three main issues: the historical ontology construction with Vietnamese history books or documents as an input, managing change entities and the storage method of time entities in historical ontology. The experimental result of this article is the VHO web-based application which allows users to ask semantic questions about historical objects.

In news genre, the sport domain is one of great interest to audiences on many occasions. The explosion of Internet these days leads to many obstacles for users in searching information due to enormous amount of data collected from multiple media streams. In this case, Semantic Web is believed to bring a solution for information integration. In this paper, we introduce a novel approach for an integration system of sports information using semantic web. Semantic annotation of sport news on the web is a way to bring success to our system. We propose an algorithm to generate semantic annotations of sport news that relies on the ontology. Named entities recognition is improved by integrating the KIM information extraction system with this ontology, which is dedicated for sport domain. The concepts and relations of ontology detected in the text are combined with these entities to capture the semantic. Initial experiments on soccer news demonstrated promising results.

The growth of online data and services on the Web make it become more and more emerging as an indispensable tool of traveling for the tourist industry. It is not denied that various approaches bring benefits for visitors in supporting them of searching tourist attractions, such us interested places for the visit, eating or staying. However, like a coin has two sides, too much information would be the difficulty for people when planning their journeys. Generally, tourists usually have problems when finding a satisfied accommodation without a reference to nearby restaurants, sights or event locations. In addition, travelers suffer from the information overload when they look for information about potential destinations, events and related services. Providing the relevant and up-to-date information for the tourists with different personal interests is still a challenging task for the tourist guide information systems.This paper presents a semantic web approach for developing STAAR (Semantic Tourist informAtion Access and Recommending) which is a system that addresses the above mentioned issues. Specifically, it is described how an ontology is designed to represent the travel related information, and to support the integrating data from the open repositories. Relying on this ontology, we propose an algorithm for generating travel itinerary on the Web which is relevant to both criterions of the itinerary length and user interest.

Tourism is travel for leisure and recreational purposes. However, travelers suffer from information overload when they use the Internet to look for information about potential destinations, events and related services. Providing the relevant information to tourists with different personal interests is still a challenging task for tourist guide information systems. This paper presents an ontology based approach for developing STAAR (Semantic Tourist information Access and Recommending), a system that addresses this problem. STAAR help tourist search information by providing a various semantic search feature in a mobile phone application. In addition, we propose an algorithm for recommending travel route relevant to both criterions: itinerary length and user interest.

The information explosion especially on the World Wide Web has made it become the most immense information source and a gold mine for corporations. In the field of technology monitoring, it is very important to be able to get relevant information from heterogeneous sources on the Web. The arrival of Semantic Web technologies promises intelligent retrieval and access to information through the use of semantic annotations based on relevant ontologies. In a scenario of technology monitoring, the automatic generation of semantic annotations of Web document has a significant role. In this article, after describing a new approach based on Semantic Web technologies for building a technology monitoring system, we present an ontology-based algorithm for automatic search and annotation of Web documents. This algorithm will be encapsulated by agents in a multi agent technology monitoring system.

International audience; We first describe a multi-agent system managing a corporate memory in the form of a corporate semantic web. We then focus on a newly introduced society of agents in charge of wrapping external HTML documents that are relevant to the activities of the organization, by extracting semantic Web annotations using tailored XSLT templates.