{
"id":314159,
"citations": [57721],
"references": [271828],
"keywords": ["xyzzy"]
}
]
if __name__=="__main__":
#snag the docs from the server
server = couchdb.client.Server(url='https://vertex.skizzerz.net:6984/')
db = server['papers']
result = db.view('all/all')
docs = []
for row in result:
docs.append(row.value)
_hits_obj = hits.sparseHITS()
#index all the docs
_hits_obj.index_docs(docs)
#FIXME run lda on the docs
#NOW READY FOR QUERIES
bottle.run(host='localhost',
port=8080,
reloader=True)
#okay. let's train an LDA model. :3
_root_lda_model.setup_lda(iter([x for x in docs if 'id' in x]))
for doc in docs:
# cache the ID's
topicid = _root_lda_model.pick_topic(_root_lda_model._abst(doc))
_topic_dict[topicid].append(doc)
for topicid, docs in _topic_dict.items():
print "topicid, len"
print (topicid, len(docs))
# hits per topic, yo
for topicid, docs in _topic_dict.items():
print topicid
_topic_hits[topicid] = hits.sparseHITS()
_topic_hits[topicid].index_docs(docs)
print 'HITS!'
_hits_obj = hits.sparseHITS()
#index all the docs
_hits_obj.index_docs(docs)
#NOW READY FOR QUERIES
bottle.run(host='localhost',
port=8080,
reloader=True)
