OBJECTIVE: To analyze the comparison, through their results, of two distinct approaches applied to aligning two representations of anatomy. MATERIALS: Both approaches use a combination of lexical and structural techniques. In addition, the first approach takes advantage of domain knowledge, while the second approach treats alignment as a special case of schema matching. The same versions of FMA and GALEN were aligned by each approach. Two thousand one hundred and ninety-nine concept matches were obtained by both approaches. METHODS AND RESULTS: For matches identified by one approach only (337 and 336, respectively), we analyzed the reasons that caused the other approach to fail. CONCLUSIONS: The first approach could be improved by addressing partial lexical matches and identifying matches based solely on structural similarity. The second approach may be improved by taking into account synonyms in FMA and identifying semantic mismatches. However, only 33% of the possible one-to-one matches among anatomical concepts were identified by the two approaches together. New directions need to be explored in order to handle more complex matches.
OBJECTIVE: To analyze the comparison, through their results, of two distinct approaches applied to aligning two representations of anatomy. MATERIALS: Both approaches use a combination of lexical and structural techniques. In addition, the first approach takes advantage of domain knowledge, while the second approach treats alignment as a special case of schema matching. The same versions of FMA and GALEN were aligned by each approach. Two thousand one hundred and ninety-nine concept matches were obtained by both approaches. METHODS AND RESULTS: For matches identified by one approach only (337 and 336, respectively), we analyzed the reasons that caused the other approach to fail. CONCLUSIONS: The first approach could be improved by addressing partial lexical matches and identifying matches based solely on structural similarity. The second approach may be improved by taking into account synonyms in FMA and identifying semantic mismatches. However, only 33% of the possible one-to-one matches among anatomical concepts were identified by the two approaches together. New directions need to be explored in order to handle more complex matches.