Description: We present a novel method for key term extraction from text
documents. In our method, document is modeled as a graph
of semantic relationships between terms of that document.
We exploit the following remarkable feature of the graph:
the terms related to the main topics of the document tend to
bunch up into densely interconnected subgraphs or communities,
while non-important terms fall into weakly interconnected
communities, or even become isolated vertices. We
apply graph community detection techniques to partition
the graph into thematically cohesive groups of terms. We
introduce a criterion function to select groups that contain
key terms discarding groups with unimportant terms. To
weight terms and determine semantic relatedness between
them we exploit information extracted from Wikipedia.
To Search:
File list (Check if you may need any files):
| Filename | Size | Date |
|---|
| VLDB08 | Authenticating the query results of text search engines .pdf |
Download