Semi-automatic ontology engineering and ontology supported document indexing in a multilingual environment
Author | : Boris Lauser |
Publisher | : diplom.de |
Total Pages | : 134 |
Release | : 2014-04-02 |
ISBN-10 | : 9783832469054 |
ISBN-13 | : 3832469052 |
Rating | : 4/5 (54 Downloads) |
Book excerpt: 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 [...]