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Semantic Web

About: Semantic Web is a research topic. Over the lifetime, 26987 publications have been published within this topic receiving 534275 citations. The topic is also known as: Sem Web & SemWeb.


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Journal ArticleDOI
TL;DR: This work develops a prototype web-based application called YeastHub that demonstrates how a life sciences data warehouse can be built using a native RDF data store (Sesame) and introduces an RDF structure into which they can be converted.
Abstract: Motivation: As the semantic web technology is maturing and the need for life sciences data integration over the web is growing, it is important to explore how data integration needs can be addressed by the semantic web. The main problem that we face in data integration is a lack of widely-accepted standards for expressing the syntax and semantics of the data. We address this problem by exploring the use of semantic web technologies---including resource description framework (RDF), RDF site summary (RSS), relational-database-to-RDF mapping (D2RQ) and native RDF data repository---to represent, store and query both metadata and data across life sciences datasets. Results: As many biological datasets are presently available in tabular format, we introduce an RDF structure into which they can be converted. Also, we develop a prototype web-based application called YeastHub that demonstrates how a life sciences data warehouse can be built using a native RDF data store (Sesame). This data warehouse allows integration of different types of yeast genome data provided by different resources in different formats including the tabular and RDF formats. Once the data are loaded into the data warehouse, RDF-based queries can be formulated to retrieve and query the data in an integrated fashion. Availability: The YeastHub website is accessible via the following URL: http://yeasthub.gersteinlab.org Contact: kei.cheung@yale.edu

128 citations

Journal ArticleDOI
TL;DR: Sentilo implements an approach based on the neo-Davidsonian assumption that events and situations are the primary entities for contextualizing opinions, which makes it able to distinguish holders, main topics, and sub-topics of an opinion.
Abstract: Sentilo is a model and a tool to detect holders and topics of opinion sentences. Sentilo implements an approach based on the neo-Davidsonian assumption that events and situations are the primary entities for contextualizing opinions, which makes it able to distinguish holders, main topics, and sub-topics of an opinion. It uses a heuristic graph mining approach that relies on FRED, a machine reader for the Semantic Web that leverages Natural Language Processing (NLP) and Knowledge Representation (KR) components jointly with cognitively-inspired frames. The evaluation results are excellent for holder detection (F1: 95%), very good for subtopic detection (F1: 78%), and good for topic detection (F1: 68%).

128 citations

Journal ArticleDOI
01 Feb 2006
TL;DR: A new approach for automatic content recommendation is presented, based on the so-called semantic Web technologies, that significantly reduces deficiencies of current approaches of content recommenders.
Abstract: The search engines in Internet and the recommender systems in the digital TV domain, pursue to light the burden of users with access to massive amounts of information, by offering only data (and TV programs) of interest for them. In this paper, we emphasize the advantages of using the so-called semantic Web technologies in the development of an intelligent TV assistant, named AVATAR. Its main advantage is a great improvement with respect to previous TV recommenders, obtained by combining two personalization strategies with a novel common nexus related to semantic inference capabilities. By the inference, AVATAR discovers appealing and complex semantic associations between the user preferences and the finally recommended TV shows. It is worth noting that this inference process overcomes a drawback identified in the existing tools, which suggest programs too similar to those the user watched in the past. In this regard, our inference strategy provides the viewers with suggestions clearly enhanced, diversified and permanently updated to their personal preferences.

127 citations

Journal ArticleDOI
TL;DR: A Semantic Web application for semantic annotation and search in large virtual collections of cultural-heritage objects, indexed with multiple vocabularies, based on established Web standards, in particular HTML/XML, CSS, RDF/OWL, SPARQL and JavaScript.

127 citations

Journal ArticleDOI
TL;DR: An ontology-driven system has proposed to implement the Felder-Silverman learning style model in addition to the learning contents, to validate its integration with the semantic web environment.
Abstract: DL Query is used to extract information from content stored in the ontology.The Felder Silverman model is used to determine learning styles of learner's.JADE agents monitor learner's behavior to provide adaptive learning.Deployments on cloud enable scope for expanding the content stored on an ontology.The proposed system supports the vision of?Semantic web education learning (SWEL). E-learning and online education have made great strides in the recent past. It has moved from a knowledge transfer model to a highly intellect, swift and interactive proposition capable of advanced decision-making abilities. Two challenges have been observed during the exploration of recent developments in e-learning. Firstly, to incorporate e-learning systems effectively in the evolving semantic web environment and secondly, to realize adaptive personalization according to the learner's changing behavior. An ontology-driven system has proposed to implement the Felder-Silverman learning style model in addition to the learning contents, to validate its integration with the semantic web environment. Software agents are employed to monitor the learner's actual learning style and modify them accordingly. The learner's learning style and their modifications are made within the proposed e-learning system. Cloud storage is used as the primary back-end in order to maintain the ontology, databases and other required server resources. To verify the system, comparisons are made between the information presented and adaptive learning styles of the learner along with actions of agents according to learners' behavior. Finally, various conclusions are drawn by exploring the learner's behavior in an adaptive environment for the proposed e-learning system.

127 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
2023116
2022348
2021412
2020612
2019782
2018881