- Semantic Web and Ontologies
- Biomedical Text Mining and Ontologies
- Data Quality and Management
- Advanced Database Systems and Queries
- Topic Modeling
- Web Data Mining and Analysis
- Service-Oriented Architecture and Web Services
- Natural Language Processing Techniques
- Advanced Text Analysis Techniques
- Data Mining Algorithms and Applications
- Sentiment Analysis and Opinion Mining
- Rough Sets and Fuzzy Logic
- Wikis in Education and Collaboration
- Spam and Phishing Detection
- Music and Audio Processing
- Educational Innovations and Technology
- Library Science and Information Systems
- Electronic Health Records Systems
- Bioinformatics and Genomic Networks
- Traffic Prediction and Management Techniques
- Big Data and Business Intelligence
- Data Visualization and Analytics
- Data Management and Algorithms
Universitat Jaume I
2007-2018
This paper describes the convergence of some most influential technologies in last few years, namely data warehousing (DW), on-line analytical processing (OLAP), and Semantic Web (SW). OLAP is used by enterprises to derive important business-critical knowledge from inside company. However, interesting queries can no longer be answered on internal alone, external must also discovered (most often web), acquired, integrated, (analytically) queried, resulting a new type OLAP, exploratory OLAP....
The Semantic Web has become a new environment that enables organizations to attach semantic annotations taken from ontologies the information they generate. As result, large amounts of complex, semi-structured and heterogeneous data repositories are being made available, making necessary warehouse tools for analyzing Web. In this paper, we present semi-automatic method identification extraction valid facts aimed at expressed as instance stores in RDF/OWL. starting point is multidimensional...
The semantic integration of biomedical resources is still a challenging issue which required for effective information processing and data analysis. availability comprehensive knowledge such as ontologies integrated thesauri greatly facilitates this effort by means annotation, allows disparate formats contents to be expressed under common space. In paper, we propose multidimensional representation space, where dimensions regard the different perspectives in research (e.g., population,...
The integration of heterogeneous biomedical information is one important step towards providing the level personalization required in next generation healthcare provision. In order to provide computer-based decision support systems needed access this integrated it will be necessary handle semantics (amongst other things) medical protocols. EC FP6 Health-e-Child project aims develop an platform for European paediatrics and tools personalized health information. This paper introduces both data...
The tremendous popularity of web-based social media is attracting the attention industry to take profit from massive availability sentiment data, which considered a high value for Business Intelligence (BI). So far, BI has been mainly concerned with corporate data little or null external world. However, analysts, taking into account Voice Customer (VoC) and Market (VoM) crucial put in context results their analyses. Recent advances Sentiment Analysis have made possible effectively extract...
This paper presents a method for semi-automatically building tailored application ontologies from set of data acquisition forms. Such are intended to facilitate the integration very heterogeneous generation processes and their linkage well-known external resources. The resulting tool is being applied medical domain, where wide variety knowledge linguistic resources available. proposed consists first inferring implicit structure forms then semantically annotating all textual elements....
The increasing amount of biomedical scientific literature published on the Web is demanding new tools and methods to automatically process extract relevant information. Traditional information extraction has focused recognizing well-defined entities such as genes or proteins, which constitutes basis for extracting relations between recognized entities. Most work harvesting domain-specific, pre-specified relations, usually requires manual labor heavy machinery. intrinsic features scale demand...
While the Linked Data (LD) initiative has given place to open, large amounts of semi-structured and rich data published on Web, effective analytical tools that go beyond browsing querying are still lacking. To address this issue, we propose automatic generation multidimensional (MD) stars. The success MD model for analysis been in great part due its simplicity. Therefore, paper aim at automatically discovering conceptual patterns summarize LD. These resemble star schema typical relational...
The Semantic Web has become a new environment that enables organizations to attach semantic annotations taken from domain and application ontologies the information they generate. As result, large amounts of complex, semi-structured heterogeneus data repositories are being made available. In this paper, we present an automatic method for on-demand construction fact tables aimed at analyzing expressed as instance stores in RDF/OWL. starting point is multidimensional star schema (i.e. topic...
The annotation of texts in natural language links some terms the text to an external information source that gives us more detailed about them. Most approaches made this field get any and annotate it by trying find out context each term, as there are have different meanings depending on topic treated. In article, we propose a variant process annotates knowing advance its context. used is Wikipedia extract use fragment embraces all related known beforehand.
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