As we all know, syntactic analysis is one of the classic tasks in the field of natural language processing, and its goal is to analyze the input sentence and obtain the corresponding syntactic structure. The machine i...
详细信息
ISBN:
(纸本)9781450387330
As we all know, syntactic analysis is one of the classic tasks in the field of natural language processing, and its goal is to analyze the input sentence and obtain the corresponding syntactic structure. The machine idea of syntactic analysis came from the 1950s. Due to the importance of this task in natural language processing, syntactic analysis has become one of the very basic and very important tasks in the field of natural language processing, and this task has not only attracted a large number of the computer experts also attracted a large number of linguists, who made great contributions to the development of syntactic analysis. Since the development of syntactic analysis tasks, this research has made great progress, which has played a positive role in promoting the progress of natural language processing. However, there have always been two difficulties in the task of syntactic analysis: one is the accuracy of the analysis results;the other is the speed of analyzing the input sentences. From rule-based to statistics-based, from word vector models to pre-trained models, every technological innovation has contributed to the development of syntactic analysis tasks. Nonetheless, the heights achieved by the syntactic analysis task have not completely overcome the long-standing challenges of accuracy of results and speed of analysis. Therefore, syntactic analysis still has great value and research significance. This paper will start from three aspects: the development status of component parsing algorithms, the impact of word vector technology on component parsing, and syntactic parsing algorithms.
Goal of this paper is to determine actual trends in geocontext extraction methods and to understand which types of geocontext information are the most interesting for users. For this purposes comparison of recent rese...
详细信息
ISBN:
(纸本)9785757704890
Goal of this paper is to determine actual trends in geocontext extraction methods and to understand which types of geocontext information are the most interesting for users. For this purposes comparison of recent researches about geocontext analysis was done. Researches were compared by the type of achieved result, used formalism, source data and limitations. As the main result of comparison new approach for automatic semantic places recognition was proposed. This approach is based on geotags markup with semantic user-defined tags. The solution allows extracting information (coordinates and a set of corresponding semantic tags on the natural language) about locations which are interesting for the location-based services users. The main advantage of the approach is its simplicity - the method does not rely on any syntax analysis algorithms during the semantic labeling stage. For illustrating the approach an example of the general purpose accidents monitoring service for the Geo2Tag platform was described.
暂无评论