In this paper, we thus focus on graph-based ranking methods (Mihalcea and Tarau, 2004) which first build a word graph according to word co-occurrences within document, and then use random walk algorithms (e.g., PageRank) to measure word importance.
for negation focus identification, the graph-based methods may suffer from the following two problems: (a) the words in graphbased methods are strongly connected by cooccurrence rather than semantic content, which do not necessarily guarantee that they are relevant to the negation focus in context; and (b) identifying a negation focus may be affected by not only the relatedness of surrounding words but also its importance in current document which is not considered in standard random walk algorithms.