def __iter__(self):
for (i, article_id1) in self.mapped_interests:
doc = []
ranks = utils.get_article_similarity_ranks(article_id1, 2000).items()
for (article_id2, rank) in ranks:
if article_id2 in self.dictionary.token2id:
id = self.dictionary.token2id[article_id2]
score = 1.0 / (math.log(rank + 5) / math.log(2))
doc.append((id, score))
yield doc
def make_doc(interest, dictionary):
article_id1 = utils.get_article_id_for_interest(interest)
if not article_id1:
return None
doc = []
ranks = utils.get_article_similarity_ranks(article_id1, 2000).items()
for (article_id2, rank) in ranks:
if article_id2 in dictionary.token2id:
id = dictionary.token2id[article_id2]
score = 1.0 / (math.log(rank + 5) / math.log(2))
doc.append((id, score))
return doc
def build_dict(self):
# force interest articles into resultset
#article_doc = self.mapped_interests.values()
#for i in range(5):
#self.dictionary.doc2bow(article_doc, True)
for (i, article_id) in self.mapped_interests:
doc = list(utils.get_article_similarity_ranks(article_id, 2000).keys())
self.dictionary.doc2bow(doc, True)
self.dictionary.filter_extremes()
self.dictionary.save_as_text('svd/dictionary.txt')
def build_article_adjacencies(interests):
article_sims = collections.defaultdict(list)
for i in interests:
article_id = utils.get_article_id_for_interest(i)
if not article_id:
continue
index1 = id_to_index(article_id)
ranks = utils.get_article_similarity_ranks(article_id, 2000).items()
ranks.sort(key=lambda pair: pair[1])
for (article_id2, rank) in ranks:
article_sims[index1].append(article_id2)
return article_sims
def build_article_adjacencies(interests):
article_sims = collections.defaultdict(list)
for i in interests:
article_id = utils.get_article_id_for_interest(i)
if not article_id:
continue
index1 = id_to_index(article_id)
ranks = utils.get_article_similarity_ranks(article_id, 2000).items()
ranks.sort(key=lambda pair: pair[1])
for (article_id2, rank) in ranks:
article_sims[index1].append(article_id2)
return article_sims
