from gensim import corpora,models,similarities
dictionary=corpora.Dictionary.load('/tmp/deerwester.dict')
corpus=corpora.MmCorpus('/tmp/deerwester.mm')
print(corpus)

lsi=models.LsiModel(corpus,id2word=dictionary,num_topics=2)
doc="human computer interaction"
vec_bow=dictionary.doc2bow(doc.lower().split())
vec_lsi=lsi[vec_bow]  #convert the query to LSI space
print(vec_lsi)

#transform corpus to space and index it
index=similarities.MatrixSimilarity(lsi[corpus])

index.save('/tmp/deerwester.index')
sims=index[vec_lsi]
sims=sorted(enumerate(sims),key=lambda item:-item[1])

from pprint import pprint
pprint(sims)