Page 114 - JOURNAL OF LIBRARY SCIENCE IN CHINA 2015 Vol. 41
P. 114

Ying WANG, Zhixiong ZHANG, Hui SUN & Feng LEI / A method of semantic representation and   113
                                                          organization of the historic knowledge on contemporary China


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                           Figure 1. Framework of the method of semantic representation and organization.

               a historical knowledge network. By using text mining technologies, this process identifies
               knowledge objects from unstructured texts, annotates the important sentences that contain these
               objects, and then extracts the related facts which form important structural facts represented in
               “object1-relation-object2” or “object1-property-value” based on the judgment of historical
               experts. Many facts about one knowledge object may be extracted from the same or different text
               items and different objects may be associated directly or indirectly. Moreover, a text item will be
               related to others according to the same object or fact. In this way, the historical knowledge network
               can be constructed according to the association of knowledge objects, facts and text items. Based
               on the network, historical knowledge can be further explored, such as retrieval, association, rank,
               clustering, and reorganization and so on.
                  “Organizing up” is a construction process, which utilizes the historical knowledge network
               constructed by the “Mining down” process to implement deeper level organization and applications
               on historical knowledge and text items by associating or reorganizing them. Currently, the
               historical text items on contemporary China are simply organized by time dimension (such as
               “1949.09-1956.09” period, “1956.10-1966.04” period, etc.) and type dimension (such as event,
               conference, organization, etc.). The knowledge hidden in text still cannot be effectively discovered.
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