摘要
This paper presents anew way to extract concept that can beused to improve text classification per-formance (precision and recall). Thecomputational measure will be dividedinto two layers. The bottom layercalled document layer is concernedwith extracting the concepts of parti-cular document and the upper layercalled category layer is with findingthe description and subject concepts ofparticular category. The relevant im-plementation algorithm that dramatic-ally decreases the search space is dis-cussed in detail. The experiment basedon real-world data collected from Info-Bank shows that the approach is supe-rior to the traditional ones.
This paper presents a new way to extract concept that can be used to improvetext classification performance (precision and recall). The computational measure will be dividedinto two layers. The bottom layer called document layer is concerned with extracting the concepts ofparticular document and the upper layer called category layer is. with finding the description andsubject concepts of particular category. The relevant implementation algorithm that dramaticallydecreases the search space is discussed in detail. The experiment based on real-world data collectedfrom Info-Bank shows that the approach is superior to the traditional ones.
基金
Project supported by the National Natural Science Foundation of China (No. 60082003) and the National High Technology Research and Development Program of China (N0.863-306-ZD03-04-1).
