Semi Automatic Ontology Engineering And Ontology Supported Document Indexing In A Multilingual Environment
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Semi-automatic ontology engineering and ontology supported document indexing in a multilingual environment
Inhaltsangabe:Introduction: The management of large amounts of information and knowledge is of ever increasing importance in today s large organisations. With the ongoing ease of supplying information online, especially in corporate intranets and knowledge bases, finding the right information becomes an increasingly difficult task. Today s search tools perform rather poorly in the sense that information access is mostly based on keyword searching or even mere browsing of topic areas. This unfocused approach often leads to undesired results. The following example illustrates the problem more clearly: An agriculture scientist would like to find out which organisation established the Agreement on Agriculture. A simple search for establish Agreement on Agriculture might result in a huge list of documents containing these words, but actually none of them containing the desired result: WTO or World Trade Organisation. The problem becomes even worse if the result searched for only appears in a foreign language document. Semantically annotated documents, i.e. documents that are indexed with ontological terms and concepts instead of simple keywords, provide several advantages. First, the ontological abstraction provides robustness against changes in the document. In the above example, the document representation might change using the term Agricultural Agreement instead of Agreement on Agriculture . However, since the document has been annotated with the ontological semantics, this will not affect the search results. Second, since the ontology used for annotating the document in this example is domain-specific, the semantic meanings and interpretations of keywords are bound to that domain and therefore the retrieval is likely to be more efficient. A term can have several meanings in different domains. By first mapping the keyword to its semantic representation in a specific ontology and using the ontology s linked knowledge structure, a much more focused search approach can be taken. Third, document specific representations no longer affect the search. This is extremely important in the case of multilingual representations. Keywords of several languages are mapped to the same concept in an ontology and are therefore given the same meaning. Multilingual search portals can be established to produce the same results, no matter which language is used for retrieval. An important task in knowledge management facilitating above described search scenario id [...]
Research and Advanced Technology for Digital Libraries
Welcome to ECDL 2003 and to these conference proceedings, featuring all the papers presented at the 7th European Conference on Research and Advanced Technology for Digital Libraries. Following Pisa (1997), Heraklion (1998), Paris (1999), Lisbon (2000), Da- stadt (2001) and Rome (2002), ECDL 2003 in Trondheim reaches some of the northernmost shores of the continent. Being the seventh in an annual series of conferences represents, for better and for worse, a considerable tradition in the fast changing world of digit- library-related research and development. It is still a di?cult and slow job to change traditional forms and formats of communication at – and related to – scienti?c conferences, and also to change participants’ expectations. Yet each new conference builds upon the topics and communities involved in previous events and inherits the commitment to quality established by its predecessors. Each year, ECDL has to live up to its role of being “the major European forum focusing on digital libraries and associated technical, practical, and social issues,”bringingdiversedisciplinesandapplicationcommunitiestogether.There arestillchallengesinthisrespectaheadofus,butthequalityandrangeofpapers and other contributions, combined with opportunities for debate, should ensure that ECDL 2003 sets high standards for the future.
Pattern and Data Analysis in Healthcare Settings
Business and medical professionals rely on large data sets to identify trends or other knowledge that can be gleaned from the collection of it. New technologies concentrate on data’s management, but do not facilitate users’ extraction of meaningful outcomes. Pattern and Data Analysis in Healthcare Settings investigates the approaches to shift computing from analysis on-demand to knowledge on-demand. By providing innovative tactics to apply data and pattern analysis, these practices are optimized into pragmatic sources of knowledge for healthcare professionals. This publication is an exhaustive source for policy makers, developers, business professionals, healthcare providers, and graduate students concerned with data retrieval and analysis.