Knowledge Seeker-Ontology Modelling for Information Search and Management (Record no. 8264)

MARC details
000 -LEADER
fixed length control field 02292nam a2200301Ia 4500
003 - CONTROL NUMBER IDENTIFIER
control field OSt
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20251112151827.0
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
fixed length control field 220909b |||||||| |||| 00| 0 eng d
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9783642179150
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number SL01558459
037 ## - SOURCE OF ACQUISITION
Terms of availability Textbook
040 ## - CATALOGING SOURCE
Original cataloging agency CSL
Language of cataloging eng
Transcribing agency CSL
041 ## - LANGUAGE CODE
Language code of text/sound track or separate title eng
084 ## - COLON CLASSIFICATION NUMBER
Classification number D65,8(B):71 Q1 TD
Assigning agency CSL
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Lim, Edward H Y
Relator term author
9 (RLIN) 850986
245 #0 - TITLE STATEMENT
Title Knowledge Seeker-Ontology Modelling for Information Search and Management
260 ## - PUBLICATION, DISTRIBUTION, ETC.
Place of publication, distribution, etc. Heidelberg :
Name of publisher, distributor, etc. Springer-Verlag ,
Date of publication, distribution, etc. 2011 .
300 ## - PHYSICAL DESCRIPTION
Extent xxvi,237p.
500 ## - GENERAL NOTE
General note Included References 195-210p.; Appendix 211-232p.
520 ## - SUMMARY, ETC.
Summary, etc. The Knowledge Seeker 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 Knowledge Seeker 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 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Information retrieval.
9 (RLIN) 850987
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Ontology.
9 (RLIN) 850988
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Computer Science.
9 (RLIN) 850989
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Liu, James N K
Relator term co-author
9 (RLIN) 850990
700 ## - ADDED ENTRY--PERSONAL NAME
Personal name Lee Raymond S T
Relator term co-author
9 (RLIN) 850991
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Classification part D65,8(B):71 Q1 TD
Koha item type Textbook
Source of classification or shelving scheme Colon Classification (CC)
Suppress in OPAC No
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Home library Current library Date acquired Source of acquisition Total Checkouts Full call number Barcode Date last seen Price effective from Koha item type
    Colon Classification (CC)     Central Science Library Central Science Library 2022-09-12 1751, 15/06/2012, Ashutosh Technical Books   D65,8(B):71 Q1 TD SL1558459 2022-09-12 2022-09-12 Textbook
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