def __init__(self, catVect, catDir, cclass):
self.catFileDict = getCats(catDir)
self.catVectors = catVect;
self.catObjDict = {}
self.catClass = cclass;
def getStatsPerQuery(argv):
tagURL = 'http://localhost:8080/rest/annotate'
catURL = 'http://localhost:8080/rest/graph/get-entity-categories'
catVector = loadCategoryVector(argv[3])
f1Dict = getCats(argv[2])
sFound = 0.0
sTotal = 0.0
eTotal = set()
eRemov = set()
catFoundNoTerm = set()
catNotFound = set()
catTermFound = set()
catEntity = set()
outfile = open('match_session_dom.txt', 'w')
#categoryVectors = {}
for session in getSessionWithNL(argv[1]):
catCount = {}
entCount = {}
querySpotList = {}
for query in session:
#find the entities in query
try:
spotDict = None #tagQueryWithDexter(query, tagURL,catURL)
querySpotList[query] = spotDict
for text in spotDict.keys():
for entry in spotDict[text]['cat'].split():
catCount[entry] = catCount.setdefault(entry, 1) + 1
entCount[text] = entCount.setdefault(text, 1) + 1
except Exception as err:
print err
#print 'SESSION', session, 'CATCOUNT', catCount, 'ENTCOUNT',entCount
found = False
if len(catCount) > 0:
#find the dominant entity
maxEnt = max(entCount.values())
#sessionQueryMapping = {}
for query, spotList in querySpotList.iteritems():
matchl = spotList.keys()
for entry in matchl:
eTotal.add(entry)
if entCount[entry] < maxEnt:
spotList.pop(entry, None)
print 'Removing spot', query, entry
eRemov.add(entry)
else:
#get the categories
#catTermMatch = {}
rquery = query.replace(entry, '')
queryTerms = set(rquery.split())
for cat in spotList[entry]['cat'].lower().split():
catEntity.add(entry + '_' + cat)
if cat in f1Dict:
phrase1 = loadPhrasesWithScore(argv[2] + '/' + f1Dict[cat])
pVector = catVector[cat]
queryDict = getDictFromSet(queryTerms)
pTotal = sum(phrase1.values())
pset = set(phrase1.keys())
sint = pset & queryTerms
score = 0.0
cscore = get_cosine(queryDict, pVector)
for iphrase in sint:
score += phrase1[iphrase] / pTotal
if len(queryTerms) > 0:
score *= (1.0 * len(sint)) / len(queryTerms)
if sint:
outfile.write(query + '\t' + entry + '\t' + cat + '\t' +
str(cscore) + '\t' + ', '.join(sint) + '\n')
found = True
catTermFound.add(entry + '_' + cat)
else:
outfile.write(query + '\t' + entry + '\t' + cat + '\t0\t0\n')
catFoundNoTerm.add(cat + '_' + entry)
else:
outfile.write(
query + '\t' + entry + '\t' + cat + '\t0\tNOT FOUND\n')
catNotFound.add(cat + '_' + entry)
#load the terms for category
#check if these terms match
if found:
sFound += 1
sTotal += 1
outfile.write('\n')
print 'Total Sessions ', sTotal
print 'Sessions with dominant entity in AOL', sFound
print '# Unique Entities', len(eTotal)
print '# Removed Entities (non dominant)', len(eRemov)
print '# no of entity types', len(catEntity)
print '# no of entity types with terms match ', len(catTermFound)
print '# no of entity types with no term match', len(catFoundNoTerm)
print '# no of entity types with no match in AOL', len(catNotFound)
