Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; Leacock and Chodorow , 1998 ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) .
wordnet an electronic lexical database chapter combining local context and wordnet similarity for word sense identification
Claudia Leacock Martin Chodorow
Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; Leacock and Chodorow , 1998 ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) . The knowledge sources used for computing relatedness can be as different as dictionaries , ontologies or large corpora .
Various approaches for computing semantic relatedness of words or concepts have been proposed , e.g. dictionary-based ( Lesk , 1986 ) , ontology-based ( Wu and Palmer , 1994 ; @@CITATION ) , information-based ( Resnik , 1995 ; Jiang and Conrath , 1997 ) or distributional ( Weeds and Weir , 2005 ) .