# Base query class (parent of all query classes)
class Query(object):
def __init__(self):
pass
def get_matches(self, index):
# TODO, return all documents IDs (as a set) from the index
pass
# Query containing a single search term
class TermQuery(Query):
def __init__(self, term):
self.term = term
def get_matches(self, index):
# TODO, return all documents IDs (as a set) that contain the search term
pass
# Load index
index = Index()
index.load_from_file("data/index.txt")
# TODO, construct the following (or similar) queries and get results
# - "states"
# - "NOT washington"
# - "united AND states"
# - "(us OR (united AND states)) AND NOT washington"
# Base query class (parent of all query classes)
class Query(object):
def __init__(self):
pass
def get_matches(self, index):
# TODO, return all documents IDs (as a set) from the index
pass
# Query containing a single search term
class TermQuery(Query):
def __init__(self, term):
self.term = term
def get_matches(self, index):
# TODO, return all documents IDs (as a set) that contain the search term
pass
# Load index
index = Index()
index.load_from_file("data/index.txt")
# TODO, construct the following (or similar) queries and get results
# - "states"
# - "NOT washington"
# - "united AND states"
# - "(us OR (united AND states)) AND NOT washington"
freq = int(p.payload)
doclen = index.get_doc_meta(doc_id)['length']
wtd = tfidf(index, t, freq, doclen)
scores[doc_id] += wtq * wtd
doc_norm[doc_id] += wtd * wtd
# `scores` at this points holds the counter of the cosine formula
# we need to perform normslization dividing by sqrt(q_norm * doc_norm)
for doc_id, score in scores.iteritems():
scores[doc_id] = scores[doc_id] / math.sqrt(q_norm * doc_norm[doc_id])
return scores
if __name__ == "__main__":
# Load index
index = Index()
index.load_from_file("../data/index.txt", "../data/meta.txt")
# Input query
query = "financial japan world news"
# Retrieve documents using the vector space model
res = retrieve_vsm(index, query)
# Print relevance scores and document titles for the top 10 results
for doc_id in sorted(res, key=res.get, reverse=True)[:10]:
docmeta = index.get_doc_meta(doc_id)
print res[doc_id], docmeta['title']
