Best way to parse tags to senticnet concept

Question

I am currently working with senticnet 1.6. I am usign it's data to assign a combined value based on "introspection", "temper", "attitude", "sensitivity", "polarity_value" that are present in senticnet for each concept defined into it's ontology.

I got a series of tags assigned to some songs, and I am trying to get the corresponding values from senticnet. Obviously not all the concept match, for example I found an "ominous" tag that got no match on senticnet, since I found a "ominously" or a "ominousness".

Can you suggest me a way to get the "nearest match"? Or, can you explain to me what are the common practice to treat these cases? I send you the template of data available in senticnet

#senticnet['concept_name'] = ['introspection_value', 'temper_value', 'attitude_value', 'sensitivity_value', 'primary_mood', 'secondary_mood', 'polarity_label', 'polarity_value', 'semantics1', 'semantics2', 'semantics3', 'semantics4', 'semantics5']
senticnet = {}
senticnet['1st_class'] = ['0.9', '0', '0', '0.9', '#joy', '#eagerness', 'positive', '0.9', 'five_star', 'first_class', 'four-star', 'first-class', 'four_star']
senticnet['a1'] = ['0', '0', '0', '0.827', '#eagerness', '#eagerness', 'positive', '0.827', 'finest', 'prime', 'top_tier', 'superior', 'first_rate']
senticnet['aapl'] = ['0.9', '0', '0', '0.9', '#joy', '#eagerness', 'positive', '0.9', 'joyful', 'happy', 'eager', 'proactive', 'smile']