000 03076nam a22004815i 4500
001 978-3-642-17916-7
003 DE-He213
005 20140220083752.0
007 cr nn 008mamaa
008 110131s2011 gw | s |||| 0|eng d
020 _a9783642179167
_9978-3-642-17916-7
024 7 _a10.1007/978-3-642-17916-7
_2doi
050 4 _aQ342
072 7 _aUYQ
_2bicssc
072 7 _aCOM004000
_2bisacsh
082 0 4 _a006.3
_223
100 1 _aLim, Edward H. Y.
_eauthor.
245 1 0 _aKnowledge Seeker - Ontology Modelling for Information Search and Management
_h[electronic resource] :
_bA Compendium /
_cby Edward H. Y. Lim, James N. K. Liu, Raymond S. T. Lee.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg,
_c2011.
300 _aXXVI, 237 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v8
505 0 _aPart I Introduction -- Part II KnowledgeSeeker - An Ontology Modeling and Learning Framework -- Part III KnowledgeSeeker Applications.
520 _aThe KnowledgeSeeker is a useful system to develop various intelligent applications such as ontology-based search engine, ontology-based text classification system, ontological agent system, and semantic web system etc. The KnowledgeSeeker contains four different ontological components. First, it defines the knowledge representation model ¡V Ontology Graph. Second, an ontology learning process that based on chi-square statistics is proposed for automatic learning an Ontology Graph from texts for different domains. Third, it defines an ontology generation method that transforms the learning outcome to the Ontology Graph format for machine processing and also can be visualized for human validation. Fourth, it defines different ontological operations (such as similarity measurement and text classification) that can be carried out with the use of generated Ontology Graphs. The final goal of the KnowledgeSeeker system framework is that it can improve the traditional information system with higher efficiency. In particular, it can increase the accuracy of a text classification system, and also enhance the search intelligence in a search engine. This can be done by enhancing the system with machine processable ontology.
650 0 _aEngineering.
650 0 _aArtificial intelligence.
650 1 4 _aEngineering.
650 2 4 _aComputational Intelligence.
650 2 4 _aArtificial Intelligence (incl. Robotics).
650 2 4 _aOperations Research/Decision Theory.
700 1 _aLiu, James N. K.
_eauthor.
700 1 _aLee, Raymond S. T.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783642179150
830 0 _aIntelligent Systems Reference Library,
_x1868-4394 ;
_v8
856 4 0 _uhttp://dx.doi.org/10.1007/978-3-642-17916-7
912 _aZDB-2-ENG
999 _c107326
_d107326