settings.yml revision 5ad93833caec560945adbce7b6f1342ef731ae83
286N/A# /config/settings/<environment>.yml
286N/Ahostname: example.com
286N/A# asset_host: assets.example.com
286N/A# http://guides.rubyonrails.org/action_mailer_basics.html#action-mailer-configuration
286N/A verify_url: http://localhost/
286N/A documentation: http://www.example.com
286N/A description: "describes the most important concepts in a specific domain (also: mid-level ontology)"
286N/A documentation: http://www.example.com
286N/A documentation: http://www.example.com
286N/A documentation: http://www.example.com
286N/A documentation: http://www.example.com
286N/A description: the task characterizes how ontologies are used to refine common keywordbased search algorithms using domain knowledge in form of subsumption relations. Ontology-driven search is usually performed automatically by means of reasoning services handling particular aspects of an ontology representation language.
286N/A description: the ontology is used as a controlled vocabulary to annotate Semantic Web resources. This task includes the usage of a semantically rich ontology for representing arbitrarily complex annotation statements on these resources. The task can be performed manually or (semi-)automatically.
286N/A description: complementary to the query formulation dimension, this task applies ontologies to semantically optimize query expressions by means of the domain knowledge (constraints, subsumption relations etc.) The task can be interpreted as a particular art of filtering information. The task is performed automatically; however, it assumes the availability of patterns describing the transformations at query level.
286N/A description: the task describes at a very general level how ontologies are applied to refine the solution space of a certain problem, such as information retrieval or personalization. The task is targeted at being performed semi-automatically or automatically.
286N/A description: the task characterizes how ontologies provide an integrating environment, an inter-lingua, for information repositories or software tools. In this scenario the ontology is applied (semi-)automatically to merge between heterogeneous data pools in the same or in adjacent domains.
286N/A description: the ontology is used in information retrieval settings as a controlled vocabulary for representing user queries. Usually the task is performed automatically in that the concepts of the ontology is are listed in a query formulation front-end in order to allow users to specifies their queries.
286N/A description: the ontology is built to reduce the ambiguities between communicating human or machine agents. It can act as a normative model which formally and clearly defines the meaning of the terms employed in agent interactions. In the context of programmed agents, the task is envisioned to be performed automatically.
286N/A description: the ontology is designed to provide a controlled and unambiguous means to represent valid configuration profiles in application systems. As the aim of the ontology is to support the operationalization of particular system-related processes; this task is performed automatically in that the ontology is processed in an automatic manner by means of reasoners or APIs.
286N/A description: the ontology is used mainly for providing personalized access to information resources. Individual user preferences w.r.t. particular application settings are formally specified by means of an ontology, which, in conjunction with appropriate reasoning services, can be directly integrated to a personalization component for filtering purposes. The usage of ontologies in personalization tasks might be carried out in various forms, from a direct involvement of the user who manually specifies ontological concepts which optimally describe his preferences, to the ontological modelling of user profiles.
286N/A description: in this scenario, the goal of the ontology is to provide a clearly defined classification and browsing structure for the information items in a repository. Again, the task can be performed manually by domain experts or as part of an application in an automatic or semi-automatic way.
286N/A description: the goal of matching is to establish links between semantically similar data items in information repositories. In contrast to the previous task, matching does not include the production of a shared final schema/ontology as a result of aggregating the matched source elements to common elements. W.r.t. the automatization level the range varies from manual to fully-automatical execution.