A relevance vector machine is used to automatically select the most relevant terms of the model.
In particular, a relevance vector machine is used to automatically select the most relevant terms of the model while retaining an analytical expression for the predictive distribution.
The following sub-sections describe the general structure of the thesauri with reference to some of the most relevant terms and categories.
This means that developers don't have to pick out words one-by-one, and by linking the most relevant terms, Linkify encourages more users to click on them (and hopefully the contextual ads they find in search results).
In an effort to consolidate our understanding of GSD, we have developed an ontology in order to capture the most relevant terms, concepts and relationships related to the goals, barriers and features of GSD projects.
Taking all these aspects into account, we decided to represent the context of a Web page by the set of keywords that is most representative of the characteristics and properties of the Web page, i.e., the most relevant terms contained in its term-vector1 [26].
By applying precision and recall metrics, which are common in information retrieval domain [24], it becomes clear that to maximize the precision, one only needs to consider very few or possibly just the most relevant terms and to discard all others.
To identify the most relevant terms, a stemming algorithm (Lovins stemmer [ 25 ]) and a stopword list extracted from GATE tool [ 41 ] are used.
The functional groups with the highest p values in the enrichment analysis are shown in Table 2; the most relevant terms were glycoprotein, extracellular region, disulfide bond and cell cycle.
A comprehensive list of 1921 immunology terms was compiled by manual selection of the most relevant terms from the standard biomedical vocabularies of Medical Subject Headings (MeSH) in Medline and the Gene Ontology (GO) controlled vocabulary (see Methods: "Defining the dictionary of terms for immune and neoplasm relevance").
