def main():
query = "obama"
snippets = search_articles(api_urls, api_keys, query)['snippets']
if len(snippets) == 0:
return
hc = HierarchicalClustering(snippets)
hc.find_clusters()
hc.print_clusters()
def main():
query = "obama"
snippets = search_articles(api_urls, api_keys, query)['snippets']
if len(snippets) == 0:
return
km = kMeansClustering(snippets)
km.find_clusters()
km.print_clusters()
km.print_common_phrases()
def __init__(self, api_urls, api_keys, query = ''):
self.API_URLs = api_urls
self.API_KEYs = api_keys
self.snippets = []
self.sources = []
self.links = []
self.titles = []
if len(query) > 0:
result = search_articles(self.API_URLs, self.API_KEYs, query)
self.snippets = result['snippets']
self.sources = result['sources']
self.links = result['links']
self.titles = result['titles']
self.clustering = None # stores clustering object
def __init__(self, api_urls, api_keys, query=''):
self.API_URLs = api_urls
self.API_KEYs = api_keys
self.snippets = []
self.sources = []
self.links = []
self.titles = []
if len(query) > 0:
result = search_articles(self.API_URLs, self.API_KEYs, query)
self.snippets = result['snippets']
self.sources = result['sources']
self.links = result['links']
self.titles = result['titles']
self.clustering = None # stores clustering object
def main():
query = "putin"
snippets = search_articles(api_urls, api_keys, query)['snippets']
if len(snippets) == 0:
print("Sorry, no results for your query!")
return
STC = SuffixTreeClustering(snippets)
#STC.add_strings(snippets)
#STC.find_base_clusters() # finding base clusters
STC.find_clusters()
STC.print_clusters()
STC.print_common_phrases(2)
def search(self, query):
if len(query) > 0:
self.snippets = search_articles(self.API_URLs, self.API_KEYs, query)
return self.snippets
def search(self, query):
if len(query) > 0:
self.snippets = search_articles(self.API_URLs, self.API_KEYs,
query)
return self.snippets
print(phrases)
def print_clusters(self):
result = self.get_clusters()
for cluster, snippets in result.items():
print("cluster #%i contains documents: " % cluster, end=' ')
print(snippets)
def compute_index(lattice, function, name):
"""
Computing probability index
"""
indexes = function(lattice)
for concept in indexes.items():
if concept[0].meta:
concept[0].meta[name] = concept[1]
else:
concept[0].meta = {name: concept[1]}
if __name__ == "__main__":
query = "obama"
snippets = search_articles(api_urls, api_keys, query)['snippets']
FC = FCAClustering(snippets)
FC.find_clusters()
FC.print_clusters()
FC.print_common_phrases()
def print_clusters(self):
result = self.get_clusters()
for cluster, snippets in result.items():
print("cluster #%i contains documents: " % cluster, end=" ")
print(snippets)
def compute_index(lattice, function, name):
"""
Computing probability index
"""
indexes = function(lattice)
for concept in indexes.items():
if concept[0].meta:
concept[0].meta[name] = concept[1]
else:
concept[0].meta = {name: concept[1]}
if __name__ == "__main__":
query = "obama"
snippets = search_articles(api_urls, api_keys, query)["snippets"]
FC = FCAClustering(snippets)
FC.find_clusters()
FC.print_clusters()
FC.print_common_phrases()
