Paper: Knowledge Acquisition From Texts: Using An Automatic Clustering Method Based On Noun-Modifier Relationship

ACL ID P97-1066
Title Knowledge Acquisition From Texts: Using An Automatic Clustering Method Based On Noun-Modifier Relationship
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1997
Authors
  • Houssem Assadi (Centre National d'Etudes des Telecommunications, Lannion France)

We describe the early stage of our method- ology of knowledge acquisition from techni- cal texts. First, a partial morpho-syntactic analysis is performed to extract "candi- date terms". Then, the knowledge engi- neer, assisted by an automatic clustering tool, builds the "conceptual fields" of the domain. We focus on this conceptual anal- ysis stage, describe the data prepared from the results of the morpho-syntactic analy- sis and show the results of the clustering module and their interpretation. We found that syntactic links represent good descrip- tors for candidate terms clustering since the clusters are often easily interpreted as "conceptual fields".