@inbook {IOPORT.05617205,
    author       = {Tsatsaronis, George and Varlamis, Iraklis and Vazirgiannis, Michalis and N{\o}rv{\aa}g, Kjetil},
    title        = {Omiotis: A thesaurus-based measure of text relatedness.},
    year         = {2009},
    booktitle    = {Machine learning and knowledge discovery in databases. European conference, ECML PKDD 2009, Bled, Slovenia, September 7--11, 2009. Proceedings, Part II},
    isbn         = {978-3-642-04173-0},
    pages        = {742-745},
    publisher    = {Berlin: Springer},
    doi          = {10.1007/978-3-642-04174-7_54},
    abstract     = {Summary: In this paper we present a new approach for measuring the relatedness between text segments, based on implicit semantic links between their words, as offered by a word thesaurus, namely WordNet. The approach does not require any type of training, since it exploits only WordNet to devise the implicit semantic links between text words. The paper presents a prototype on-line demo of the measure, that can provide word-to-word relatedness values, even for words of different part of speech. In addition the demo allows for the computation of relatedness between text segments.},
    identifier   = {05617205},
}