DCDistance google
Text Mining is a field that aims at extracting information from textual data. One of the challenges of such field of study comes from the pre-processing stage in which a vector (and structured) representation should be extracted from unstructured data. The common extraction creates large and sparse vectors representing the importance of each term to a document. As such, this usually leads to the curse-of-dimensionality that plagues most machine learning algorithms. To cope with this issue, in this paper we propose a new supervised feature extraction and reduction algorithm, named DCDistance, that creates features based on the distance between a document to a representative of each class label. As such, the proposed technique can reduce the features set in more than 99% of the original set. Additionally, this algorithm was also capable of improving the classification accuracy over a set of benchmark datasets when compared to traditional and state-of-the-art features selection algorithms. …

Knowledge as a Service (KaaS) google
In this paper, we introduce and explore a new computing paradigm we call knowledge as a service, in which a knowledge service provider, via its knowledge server, answers queries presented by some knowledge consumers. The knowledge server’s answers are based on knowledge models that may be expensive or impossible to obtain for the knowledge consumers.
Knowledge as a Service
Actionable Knowledge As A Service (AKAAS)

Neuroinformatics google
Neuroinformatics is a research field concerned with the organization of neuroscience data by the application of computational models and analytical tools. These areas of research are important for the integration and analysis of increasingly large-volume, high-dimensional, and fine-grain experimental data. Neuroinformaticians provide computational tools, mathematical models, and create interoperable databases for clinicians and research scientists. Neuroscience is a heterogeneous field, consisting of many and various sub-disciplines (e.g., Cognitive Psychology, Behavioral Neuroscience, and Behavioral Genetics). In order for our understanding of the brain to continue to deepen, it is necessary that these sub-disciplines are able to share data and findings in a meaningful way; Neuroinformaticians facilitate this. Neuroinformatics stands at the intersection of neuroscience and information science. Other fields, like genomics, have demonstrated the effectiveness of freely-distributed databases and the application of theoretical and computational models for solving complex problems. In Neuroinformatics, such facilities allow researchers to more easily quantitatively confirm their working theories by computational modeling. Additionally, neuroinformatics fosters collaborative research—an important fact that facilitates the field’s interest in studying the multi-level complexity of the brain. There are three main directions where neuroinformatics has to be applied:
1. the development of tools and databases for management and sharing of neuroscience data at all levels of analysis,
2. the development of tools for analyzing and modeling neuroscience data,
3. the development of computational models of the nervous system and neural processes. …