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The purpose of this paper is to present a system for recognition of location names in ancient books written in languages, such as Chinese, in which proper names are not…
The purpose of this paper is to present a system for recognition of location names in ancient books written in languages, such as Chinese, in which proper names are not signaled by an initial capital letter.
Rule-based and statistical methods were combined to develop a set of rules for identification of product-related location names in the local chronicles of Guangdong. A name recognition system, with functions of document management, information extraction and storage, rule management, location name recognition, and inquiry and statistics, was developed using Microsoft's .NET framework, SQL Server 2005, ADO.NET and XML. The system was evaluated with precision ratio, recall ratio and the comprehensive index, F.
The system was quite successful at recognizing product-related location names (F was 71.8 percent), demonstrating the potential for application of automatic named entity recognition techniques in digital collation of ancient books such as local chronicles.
Results suffered from limitations in initial digitization of the text. Statistical methods, such as the hidden Markov model, should be combined with an extended set of recognition rules to improve recognition scores and system efficiency.
Electronic access to local chronicles by location name saves time for chorographers and provides researchers with new opportunities.
Named entity recognition brings previously isolated ancient documents together in a knowledge base of scholarly and cultural value.
Automatic name recognition can be implemented in information extraction from ancient books in languages other than English. The system described here can also be adapted to modern texts and other named entities.
The purpose of this paper is to apply Geographic Information System (GIS) in the development and utilization of Chinese ancient local chronicles to achieve the mining and…
The purpose of this paper is to apply Geographic Information System (GIS) in the development and utilization of Chinese ancient local chronicles to achieve the mining and visualization of historical data about products distribution and dispersal in Products in Local Chronicles of Guangdong.
Using 1,756 records of product-related location names in Products in Local Chronicles of Guangdong of the Qing dynasty, which are recognized by a name recognition system, as attribute data; taking the spatial data of Chinese administrative geography of the Qing dynasty in 1820 and the Historical Atlas of China as spatial data; connect the attribute data with relevant spatial data based on the table connection function of Arcmap in Arcgis 8.3 to implement the data management, cartography and analysis.
The application of GIS in the development and utilization of ancient local chronicles was quite successful. With some thematic maps, knowledge about products distribution and dispersal in ancient books was vividly displayed so as to facilitate relevant researches.
Only product-related location names inside China were analyzed, not other named entities in local chronicles; and only static visual display was achieved, not dynamic visual display. Historical maps of the world can be used to carry out the visualization of the products distribution and dispersal in the world, and even the visualization of other knowledge, such as poetries and songs scattered over many places in China. The process of products dispersal and the distribution of poetries and songs can be dynamically and visually displayed by pictures, audios, videos, multimedia, etc.
By using GIS in the development and utilization of Chinese ancient local chronicles, this paper explores a new way for the collation of ancient books and open up a new area for the research of digital humanities.
This is the first try about the application of GIS in the development and utilization of ancient local chronicles, and also the same of digital humanities research in the field of agricultural history.