13,793 research outputs found
Concept Extraction and Clustering for Topic Digital Library Construction
This paper is to introduce a new approach to build
topic digital library using concept extraction and
document clustering. Firstly, documents in a special
domain are automatically produced by document
classification approach. Then, the keywords of each
document are extracted using the machine learning
approach. The keywords are used to cluster the
documents subset. The clustered result is the taxonomy
of the subset. Lastly, the taxonomy is modified to the
hierarchical structure for user navigation by manual
adjustments. The topic digital library is constructed
after combining the full-text retrieval and hierarchical
navigation function
Uniqueness of a pre-generator for -semigroup on a general locally convex vector space
The main purpose is to generalize a theorem of Arendt about uniqueness of
-semigroups from Banach space setting to the general locally convex vector
spaces, more precisely, we show that cores are the only domains of uniqueness
for -semigroups on locally convex spaces. As an application, we find a
necessary and sufficient condition for that the mass transport equation has one
unique weak solution
- …