The Semantic Portal for Supporting Research Community: a Review (original) (raw)
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Semantic Web Search: Perspectives and Key Technologies
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This paper gives an overview of recent Semantic Web technologies which can be used to enhance digital libraries in semantic nature. Deploying Semantic Web technologies would lead to efficient and more precise representation of digital library content and hence better retrieval. This paper presents a mode for enhancing the library with semantic technology and talk about the implementation of semantic technologies for architecting digital libraries, that will go a long way in providing digital library architecture and web based information services with product highly customized to users’ needs. Digital libraries have been an important source of information throughout the history of mankind. It has been present in our societies in different forms. Notably, traditional libraries have found their on the desktops of internet users. They have taken the shape of semantic digital libraries, which are accessible at any time, and accordingly provide a more meaningful search. This paper explains the Semantic Web and the technologies that support its functioning, including XML, RDF, and Ontology. Semantic Web technologies are considered from the perspective of digital Libraries and how Semantic Web technologies can enhance the functioning of digital libraries. The paper additionally explores on some existing semantic digital library systems like DSpace, SMILE, JeromeDL and BRICKS.
Upgrade of a current research information system with ontologically supported semantic search engine
Expert Systems with Applications, 2016
Harmonising the metadata format alone does not solve the issue of efficient access to relevant information in heterogeneous environments, when different systems use different content, contextual and semantic concepts for certain entities. One such type of heterogeneous systems are also Current Research Information Systems (CRIS), which store their data primarily in local relational databases, using different formats and various local concepts. In this article, we study the possibilities and propose a new ontologically supported semantic search engine (OSSSE) which, in addition to the harmonisation of the metadata format among local CRIS systems, also ensures that the meaning of data and/or concepts that belong to various metadata entities are also harmonised. A special model of ontological infrastructure was designed, and dedicated test ontology was created alongside with a new simplified algorithm for creating ontology, the basis of which is the distinction between new and already existing classes in terms of content. Finally, we evaluated the proposed OSSSE model using a simulation of the search process on the base of 41,113 real searches within SICRIS. The obtained results show that regardless of the search situation, the proposed OSSSE is always at least as efficient as a search without ontological support in terms of precision, while recall remains the same; the improvement has been shown to be statistically significant with a high confidence interval (p < 0.005). The proposed OSSSE model is able to solve the issue of harmonizing the data where different heterogeneous systems use different content, contextual and semantic concepts, which is the case in many advanced expert systems. In this manner, the more the search is carried out based on the properties described by the supporting ontology, the more the infrastructure can help a searcher. The proposed concepts, ontological infrastructure and the designed semantic search engine may well help to improve search precision in several information retrieval systems.
Semantic Web Search Engines : A Comparative Survey
International Journal of Scientific Research in Computer Science, Engineering and Information Technology, 2019
Search engines play important role in the success of the Web. Search engine helps the users to find the relevant information on the internet. Due to many problems in traditional search engines has led to the development of semantic web. Semantic web technologies are playing a crucial role in enhancing traditional search, as it work to create machines readable data and focus on metadata. However, it will not replace traditional search engines. In the environment of semantic web, search engine should be more useful and efficient for searching the relevant web information. It is a way to increase the accuracy of information retrieval system. This is possible because semantic web uses software agents; these agents collect the information, perform relevant transactions and interact with physical devices. This paper includes the survey on the prevalent Semantic Search Engines based on their advantages, working and disadvantages and presents a comparative study based on techniques, type of results, crawling, and indexing.
Ontology Based Information Retrieval Model for Semantic Research Digital Library (SEMRDL
Using semantic web technology through information retrieval process is becoming an efficient way to enhance the accuracy of the search process and retrieve more relevant results in the web based systems especially in digital library. This paper presents ontology based information retrieval model for digital library community based on the adaptation of the vector space model ranking algorithm combined with the semantic web technologies, this semantic retrieval and indexing model for digital library (SEMRDL) has been applied on a data set of a research center digital library. Then the search result and evaluation for our new model SEMRDL illustrated and compared with traditional search on the digital library and the enhancement in results are clarified in many levels.