Finding Similarity and Comparability from Merged Hetero Data of the Semantic Web by Using Graph Pattern Matching
Hiroyuki Sato, Kyoji Iiduka, Takeya Mukaigaito, Takahiko Murayama · 2005
We propose a method to find similarity and compared points from merged hetero data of the Semantic Web using graph pattern matching. A query pattern based on simple keyword is automatically created by analyzing the frequent occurrence of patterns of data structures and by using individual user context. Therefore, this query allows users to extract not only a subgraph that includes the keyword but also a cluster of characteristic data related to the keyword or user profile and preference. We call the proposed method context structure matching (CSM). We have been trying to apply CSM to a large amount of o#ce data.