tailieunhanh - Báo cáo khoa học: "Growing Finely-Discriminating Taxonomies from Seeds of Varying Quality and Size"

Concept taxonomies offer a powerful means for organizing knowledge, but this organization must allow for many overlapping and fine-grained perspectives if a general-purpose taxonomy is to reflect concepts as they are actually employed and reasoned about in everyday usage. We present here a means of bootstrapping finely-discriminating taxonomies from a variety of different starting points, or seeds, that are acquired from three different sources: WordNet, ConceptNet and the web at large. | Growing Finely-Discriminating Taxonomies from Seeds of Varying Quality and Size Tony Veale School of Computer Science University College Dublin Ireland Guofu Li School of Computer Science University College Dublin Ireland Yanfen Hao School of Computer Science University College Dublin Ireland Abstract Concept taxonomies offer a powerful means for organizing knowledge but this organization must allow for many overlapping and fine-grained perspectives if a general-purpose taxonomy is to reflect concepts as they are actually employed and reasoned about in everyday usage. We present here a means of bootstrapping finely-discriminating taxonomies from a variety of different starting points or seeds that are acquired from three different sources WordNet ConceptNet and the web at large. 1 Introduction Taxonomies provide a natural and intuitive means of organizing information from the biological taxonomies of the Linnaean system to the layout of supermarkets and bookstores to the organizational structure of companies. Taxonomies also provide the structural backbone for ontologies in computer science from common-sense ontologies like Cyc Lenat and Guha 1990 and SUMO Niles and Pease 2001 to lexical ontologies like WordNet Miller et al. 1990 . Each of these uses is based on the same root-branch-leaf metaphor the broadest terms with the widest scope occupy the highest positions of a taxonomy near the root while specific terms with the most local concerns are located lower in the hierarchy nearest the leaves. The more interior nodes that a taxonomy possesses the finer the conceptual distinctions and the more gradated the similarity judgments it can make . Budanit-sky and Hirst 2006 . General-purpose computational taxonomies are called upon to perform both coarse-grained and fine-grained judgments. In NLP for instance the semantics of eat requires just enough knowledge to discriminate foods like tofu and cheese from non-foods

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