def advancedFeatureSearch(query, sought_feature):
formatted_query = parser.parse(query)
scoreDocs = searcher.search(formatted_query, 50).scoreDocs
#### create return structure ####
results = []
comments = []
for scoreDoc in scoreDocs:
doc = searcher.doc(scoreDoc.doc)
featureMap = simplejson.loads(doc.get("feature-contents"))
comments.append(featureMap["featureMap"][sought_feat]["sentence"])
resentry = {
"feature": sought_feature,
"title": doc.get("title"),
"review_date": doc.get("modified"),
"comments": comments
}
results.append(resentry)
return render_to_response("search_by_product_and_feature_results.html", {
"submitted_query": query,
"results": results
})
def extractFeatureQueryWords(query):
import string
from lucene import Document, TermQuery, Term
# create analyzer
aux_analyzer = StandardAnalyzer(Version.LUCENE_CURRENT)
try:
file = open('../features.txt', 'r')
featurelist = []
for line in file.readlines():
words_in_line = line.split()
featurelist += words_in_line
querywordlist = query.split()
featureQueryList = []
productQueryList = []
for word in querywordlist:
if word in featurelist:
featureQueryList.append(word)
else:
# create parser for word
aux_parser = QueryParser(Version.LUCENE_CURRENT, "title", aux_analyzer)
aux_query = aux_parser.parse(word)
scoreDocs = searcher.search(aux_query, 50).scoreDocs
if scoreDocs:
productQueryList.append(word)
featureQuery = ""
if featureQueryList:
featureQuery = "("
for i in range(len(featureQueryList)):
if i == len(featureQueryList) - 1:
featureQuery += featureQueryList[i] + ")"
else:
featureQuery += featureQueryList[i] + " AND "
print featureQuery
productQuery = ""
if productQueryList:
productQuery = "("
for i in range(len(productQueryList)):
if i == len(productQueryList) - 1:
productQuery += productQueryList[i] + ")"
else:
productQuery += productQueryList[i] + " AND "
return (featureQuery, productQuery, featureQueryList, productQueryList)
except Exception, ex:
print "Could not separate feature query words. Reason: ", ex
return ("", "(" + query + ")", [], querywordlist)
def extractFeatureQueryWords(query):
import string
from lucene import Document, TermQuery, Term
# create analyzer
aux_analyzer = StandardAnalyzer(Version.LUCENE_CURRENT)
try:
file = open('../features.txt', 'r')
featurelist = []
for line in file.readlines():
words_in_line = line.split()
featurelist += words_in_line
querywordlist = query.split()
featureQueryList = []
productQueryList = []
for word in querywordlist:
if word in featurelist:
featureQueryList.append(word)
else:
# create parser for word
aux_parser = QueryParser(Version.LUCENE_CURRENT, "title",
aux_analyzer)
aux_query = aux_parser.parse(word)
scoreDocs = searcher.search(aux_query, 50).scoreDocs
if scoreDocs:
productQueryList.append(word)
featureQuery = ""
if featureQueryList:
featureQuery = "("
for i in range(len(featureQueryList)):
if i == len(featureQueryList) - 1:
featureQuery += featureQueryList[i] + ")"
else:
featureQuery += featureQueryList[i] + " AND "
print featureQuery
productQuery = ""
if productQueryList:
productQuery = "("
for i in range(len(productQueryList)):
if i == len(productQueryList) - 1:
productQuery += productQueryList[i] + ")"
else:
productQuery += productQueryList[i] + " AND "
return (featureQuery, productQuery, featureQueryList, productQueryList)
except Exception, ex:
print "Could not separate feature query words. Reason: ", ex
return ("", "(" + query + ")", [], querywordlist)
def getResultScoreDocs(query):
# create analyzer
analyzer = StandardAnalyzer(Version.LUCENE_CURRENT)
# create parser for user submitted query
parser = QueryParser(Version.LUCENE_CURRENT, "title", analyzer)
parser.setDefaultOperator(QueryParser.Operator.AND)
formatted_query = parser.parse(query)
scoreDocs = searcher.search(formatted_query, 50).scoreDocs
return scoreDocs
def getResultScoreDocs(query):
# create analyzer
analyzer = StandardAnalyzer(Version.LUCENE_CURRENT)
# create parser for user submitted query
parser = QueryParser(Version.LUCENE_CURRENT, "title", analyzer)
parser.setDefaultOperator(QueryParser.Operator.AND)
formatted_query = parser.parse(query)
scoreDocs = searcher.search(formatted_query, 50).scoreDocs
return scoreDocs
def advancedFeatureSearch(query, sought_feature):
formatted_query = parser.parse(query)
scoreDocs = searcher.search(formatted_query, 50).scoreDocs
#### create return structure ####
results = []
comments = []
for scoreDoc in scoreDocs:
doc = searcher.doc(scoreDoc.doc)
featureMap = simplejson.loads(doc.get("feature-contents"))
comments.append(featureMap["featureMap"][sought_feat]["sentence"])
resentry = {"feature": sought_feature, "title": doc.get("title"), "review_date": doc.get("modified"),
"comments": comments }
results.append(resentry)
return render_to_response("search_by_product_and_feature_results.html", {"submitted_query": query, "results" : results})
