Abstract:

Term recognition is widely used in the ontology construction，dictionary construction and other fields. And term weighting is a key step in the term recognition. In this paper，several improvements have been made to TF-IDF algorithm，e.g.， the length of terms is considered in weighting，also with terms’ correlations to documentation set. The candidate term weight is calculated in a distributed manner based on MapReduce on Hadoop. Experimental results show that the method proposed not only simplifies the steps of term weighting，but also improves the efficiency of the algorithm.

Key words: term weight, TF-IDF, MapReduce, distributed