Paper Info
Title
A Novel Knowledge-Based Architecture for Concept Mining on Italian and English Texts.
Abstract
Manually annotating unstructured texts for finding significant concepts is a knowledge intensive process and, given the amount of data available on the Web and on digital libraries nowadays, it is not cost effective. Therefore automatic annotators capable to perform like human experts are extremely desirable. State of the art systems already offer good performance but they are often limited to one language, one domain of application, and can not entail concepts that do not appear but are logically/semantically implied in the text. In order to overcome this shortcomings, we propose here a novel knowledge-based, language independent, unsupervised approach towards keyphrase generation. We developed DIKpE-G, an experimental prototype system which integrates different kinds of knowledge, from linguistic to statistical, meta/structural, social, and ontological knowledge. DIKpE-G is capable to extract, evaluate, and infer meaningful concepts from a natural language text. The prototype performs well over both Italian and English texts.
Year
DOI
Venue
2014
10.1007/978-3-319-25840-9_9
Communications in Computer and Information Science
Keywords
Field
DocType
Concept extraction,Keyphrase extraction,Information extraction,Italian language,Natural language processing,Text analysis,Text classification,Text summarization
Automatic summarization,Ontology,Architecture,Concept mining,Computer science,Natural language,Information extraction,Natural language processing,Artificial intelligence,Concept extraction,Digital library
Conference
Volume
ISSN
Citations 
553
1865-0929
0
PageRank 
References 
Authors
0.34
10
3
Name
Order
Citations
PageRank
Dante Degl'Innocenti1134.45
Dario De Nart2347.70
Carlo Tasso351184.98