Newzmate, a Kiev, Ukraine-based startup that develops semantic data analysis, aggregation and recommendation services, has launched its latest product.
We have developed a web-based, semantic data mining and aggregation tool to 'filter' published literature for evidence of association of preterm birth with genes, genetic variants, SNPs or changes in gene expression.
Collection and cleaning of a total of 85,873 records was performed the Aggregator of Biological Knowledge (ABK) [64], which applied structural and semantic rules to automate the aggregation and annotation task.
The proposed framework results in various types constraints, i.e., attribute, class, participation, projection, co-occurrence, appearance and overlapping, on a semantic model that supports abstractions like classification, generalization/specialization, aggregation and association.
Lack of standards, unstructured data formats and aggregation of data (elements and cases) inhibit the semantic content processing, search and holistic data understanding.
In this paper, we provide the means for efficiently analyzing and exploring large amounts of semantic data by combining the inference power from the annotation semantics with the analysis capabilities provided by OLAP-style aggregations, navigation, and reporting.
The literature, however, takes it for granted that Fuzzy Cognitive Maps allow for a simple aggregation of domain knowledge from several experts without much considering holistic approaches with semantic comparison of concepts.
The difference between source (record) and target (terminology) vocabulary may for example be categorized as spelling variants, synonymy or aggregation, and in order to understand the coding process, the various degrees of semantic distance between records and terminologies must be taken into account.
