def __init__(self, account_key, t_es, t_ec, host):
self.account_key = account_key
self.bing = Bing()
self.host = host
self.t_es = t_es
self.t_ec = t_ec
class WebClassifier(object):
''' Main class for web database classification
Also builds content summary for each category
'''
def __init__(self, account_key, t_es, t_ec, host):
self.account_key = account_key
self.bing = Bing()
self.host = host
self.t_es = t_es
self.t_ec = t_ec
def search_web(self, query):
''' Wrapper function that calls Bing search API with cache
@query: list of keywords for query
@return: (number of results, top-4 urls)
'''
return self.bing.search_web_cached(self.account_key, self.host, query)
def close(self):
''' Safely close Bing object, as is requested by Bing class
@return: None
'''
self.bing.close()
def classify(self, category, especificity_c, path, results):
''' Main function for web database classification
Also builds sample document urls for each category
@category: the CategoryNode object, C
@especificity_c: ESpecificity(host, C)
@path: list[str], path from root category to current category
@results: list[list[str]], all valid classification paths
@return: None
'''
path.append(category.name)
url_set = set()
# compute e_coverage vector
e_coverage_vector = {}
sum_e_coverage = 0
for sub_category_node in category.children:
sub_category = sub_category_node.name
probes = sub_category_node.queries
e_coverage = 0
for probe in probes:
freq, top_urls = self.search_web(probe)
e_coverage += freq
url_set.update(top_urls)
e_coverage_vector[sub_category] = e_coverage
sum_e_coverage += e_coverage
# compute e_especificity vector
e_especificity_vector = {}
for sub_category_node in category.children:
sub_category = sub_category_node.name
e_coverage = e_coverage_vector[sub_category]
e_especificity = especificity_c * e_coverage / sum_e_coverage
e_especificity_vector[sub_category] = e_especificity
print 'Coverage for category "%s" is %s' % (sub_category, e_coverage)
print 'Specificity for category "%s" is %s' % (sub_category, e_especificity)
# check threshold and recurse
push_down = False
for sub_category_node in category.children:
sub_category = sub_category_node.name
e_especificity = e_especificity_vector[sub_category]
e_coverage = e_coverage_vector[sub_category]
if e_especificity < self.t_es or e_coverage < self.t_ec:
continue
# Recursively classify into sub_category
push_down = True
self.classify(sub_category_node, e_especificity, path, results)
# Collect document sample urls of sub_category
url_set |= sub_category_node.url_set
# Attach document sample url to the category node object
# for generating summary content
category.url_set = url_set
if not push_down:
results.append(list(path))
path.pop()