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horn_concerto_parallel.py
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horn_concerto_parallel.py
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#!/usr/bin/env python
"""
Horn Concerto - Mining Horn clauses in RDF datasets using SPARQL queries.
Author: Tommaso Soru <[email protected]>
Version: 0.0.7
Usage:
Use test endpoint (DBpedia)
> python horn_concerto.py
Use with default hyperparameters
> python horn_concerto.py <ENDPOINT> <GRAPH_IRI>
Use the current directory as output folder
> python horn_concerto.py <ENDPOINT> <GRAPH_IRI> <MIN_CONFIDENCE> <TOP_PROPERTIES> <MAX_TRIANGLES>
Full custom setup
> python horn_concerto.py <ENDPOINT> <GRAPH_IRI> <MIN_CONFIDENCE> <TOP_PROPERTIES> <MAX_TRIANGLES> <OUTPUT_FOLDER>
"""
import urllib2, urllib, httplib, json
import sys
import pickle
import time
from joblib import Parallel, delayed
import multiprocessing
reload(sys)
sys.setdefaultencoding("utf-8")
VERSION = "0.0.7"
endpoint = None
graph = None
min_confidence = None
n_properties = None
n_triangles = None
output_folder = None
############################### FUNCTIONS ################################
def sort_by_value_desc(d):
return sorted(d.items(), key=lambda e: e[1], reverse=True)
def sparql_query(query):
param = dict()
param["default-graph-uri"] = graph
param["query"] = query
param["format"] = "JSON"
param["CXML_redir_for_subjs"] = "121"
param["CXML_redir_for_hrefs"] = ""
param["timeout"] = "600000" # ten minutes - works with Virtuoso endpoints
param["debug"] = "on"
try:
resp = urllib2.urlopen(endpoint + "?" + urllib.urlencode(param))
j = resp.read()
resp.close()
except (urllib2.HTTPError, httplib.BadStatusLine):
print "*** Query error. Empty result set. ***"
j = '{ "results": { "bindings": [] } }'
sys.stdout.flush()
return json.loads(j)
def simple_rules(q):
SIMPLE_RULES = "SELECT ?p (COUNT(*) AS ?c) WHERE { ?x ?p ?y . ?x <" + q + "> ?y . FILTER(?p != <" + q + "> ) } GROUP BY ?p ORDER BY DESC(?c)"
print "Querying:", SIMPLE_RULES
rules = dict()
start = time.time()
results = sparql_query(SIMPLE_RULES)
print "Time: {}".format(time.time() - start)
try:
for result in results["results"]["bindings"]:
rules[str(result["p"]["value"])] = int(result["c"]["value"])
except KeyError:
pass
print "Result:", rules
return rules
def type_two_rules(q):
TYPE_2_RULES = "SELECT ?p (COUNT(*) AS ?c) WHERE { ?y ?p ?x . ?x <" + q + "> ?y } GROUP BY ?p ORDER BY DESC(?c)"
print "Querying:", TYPE_2_RULES
rules = dict()
start = time.time()
results = sparql_query(TYPE_2_RULES)
print "Time: {}".format(time.time() - start)
try:
for result in results["results"]["bindings"]:
rules[str(result["p"]["value"])] = int(result["c"]["value"])
except KeyError:
pass
print "Result:", rules
return rules
def top_properties():
TOP_PROPERTIES = 'SELECT ?q (COUNT(*) AS ?c) WHERE { [] ?q [] } GROUP BY ?q ORDER BY DESC(?c) LIMIT ' + str(n_properties)
print "Querying:", TOP_PROPERTIES
tp = dict()
results = sparql_query(TOP_PROPERTIES)
try:
for result in results["results"]["bindings"]:
tp[str(result["q"]["value"])] = int(result["c"]["value"])
except KeyError:
pass
print "Result:", tp
return tp
def triangles(t, p):
tri = [["?x ?q ?z", "?z ?r ?y"], ["?x ?q ?z", "?y ?r ?z"], ["?z ?q ?x", "?z ?r ?y"], ["?z ?q ?x", "?y ?r ?z"]]
TRIANGLES = 'SELECT ?q ?r (COUNT(*) AS ?c) WHERE { ' + tri[t][0] + ' . ' + tri[t][1] + ' . ?x <' + p + '> ?y } GROUP BY ?q ?r ORDER BY DESC(?c) LIMIT ' + str(n_triangles)
print "Querying:", TRIANGLES
rules = dict()
start = time.time()
results = sparql_query(TRIANGLES)
print "Time: {}".format(time.time() - start)
try:
for result in results["results"]["bindings"]:
rules[(str(result["q"]["value"]), str(result["r"]["value"]))] = int(result["c"]["value"])
except KeyError:
pass
print "Result:", rules
return rules
def adjacencies(t, k):
nodes = ["xzzy", "xzyz", "zxzy", "zxyz"]
ADJACENCIES = 'SELECT (COUNT(*) AS ?c) WHERE { ?' + nodes[t][0] + ' <' + k[0] + '> ?' + nodes[t][1] + ' . ?' + nodes[t][2] + ' <' + k[1] + '> ?' + nodes[t][3] + ' }'
print "Querying:", ADJACENCIES
start = time.time()
results = sparql_query(ADJACENCIES)
print "Time: {}".format(time.time() - start)
try:
res = results["results"]["bindings"]
except KeyError:
return 0
if len(res) == 0:
return 0
else:
return res[0]["c"]["value"]
def write_rule(t, c, p, q):
files = ["pxy-qxy", "pxy-qyx"]
args = ["(x,y)", "(y,x)"]
worth = False
with open("{}/rules-{}.tsv".format(output_folder, files[t]), 'a') as f:
if c > min_confidence:
f.write("{}\t{}\t(x,y)\t{}\t{}\n".format(c, p, q, args[t]))
worth = True
return worth
def write_rule_3(t, c, p, q, r):
files = ["pxy-qxz-rzy", "pxy-qxz-ryz", "pxy-qzx-rzy", "pxy-qzx-ryz"]
args = [["(x,z)", "(z,y)"], ["(x,z)", "(y,z)"], ["(z,x)", "(z,y)"], ["(z,x)", "(y,z)"]]
worth = False
with open("{}/rules-{}.tsv".format(output_folder, files[t]), 'a') as f:
if c > min_confidence:
f.write("{}\t{}\t(x,y)\t{}\t{}\t{}\t{}\n".format(c, p, q, args[t][0], r, args[t][1]))
worth = True
return worth
def write_titles():
print "output_folder:", output_folder
files = ["pxy-qxy", "pxy-qyx", "pxy-qxz-rzy", "pxy-qxz-ryz", "pxy-qzx-rzy", "pxy-qzx-ryz"]
for t in range(len(files)):
if t < 2:
with open("{}/rules-{}.tsv".format(output_folder, files[t]), 'w') as f:
f.write(unicode("weight\tp\t(?,?)\tq\t(?,?)\n"))
else:
with open("{}/rules-{}.tsv".format(output_folder, files[t]), 'w') as f:
f.write(unicode("weight\tp\t(?,?)\tq\t(?,?)\tr\t(?,?)\n"))
types = [
"I: p(x,y) <= q(x,y)",
"II: p(x,y) <= q(y,x)",
"III: p(x,y) <= q(x,z), r(z,y)",
"IV: p(x,y) <= q(x,z), r(y,z)",
"V: p(x,y) <= q(z,x), r(z,y)",
"VI: p(x,y) <= q(z,x), r(y,z)"]
body = [
"(x,y)",
"(y,x)",
("(x,z)", "(z,y)"),
("(x,z)", "(y,z)"),
("(z,x)", "(z,y)"),
("(z,x)", "(y,z)")]
# outer loop
def rangeTypes(i, tp):
print "Rules of type", types[i]
# there might exist p_1,p_2 such that: p_i(x,y) <= q(?,?), r(?,?)
# shared dictionary
adj_dict = dict()
# inner loop
for tp_key, tp_val in sort_by_value_desc(tp):
print "Processing:", tp_key, tp_val
if i < 2: # p-q rules
if i == 0: # p(x,y) <= q(x,y)
r = simple_rules(tp_key)
else: # p(x,y) <= q(y,x)
r = type_two_rules(tp_key)
for r_key, r_val in sort_by_value_desc(r):
print r_key, r_val
print "*** RULE FOUND! ***",
c = float(r_val) / float(tp_val)
print "c = {}\t{} (x,y) <= {} {}".format(c, r_key, tp_key, body[i])
worth = write_rule(i, c, r_key, tp_key)
if not worth:
break
else: # p-q-r rules
j = i - 2 # p-q-r rule index
triang = triangles(j, tp_key)
for k, v in sort_by_value_desc(triang):
print k, v
if k in adj_dict:
print "Value found in dictionary:", k
adj = adj_dict[k]
else:
adj = adjacencies(j, k)
if adj == 0:
continue
c = float(v) / float(adj)
print "*** RULE FOUND! ***"
print "c = {}\t{} (x,y) <= {} {} ^ {} {}".format(c, tp_key, k[0], body[i][0], k[1], body[i][1])
worth = write_rule_3(j, c, tp_key, k[0], k[1])
if not worth:
break
adj_dict[k] = adj
############################### ALGORITHM ################################
def run(endpoint_P, graph_P, min_confidence_P, n_properties_P, n_triangles_P, output_folder_P):
global endpoint, graph, min_confidence, n_properties, n_triangles, output_folder
endpoint = endpoint_P
graph = graph_P
min_confidence = min_confidence_P
n_properties = n_properties_P
n_triangles = n_triangles_P
output_folder = output_folder_P
print "Horn Concerto v{}".format(VERSION)
print "Endpoint: {}\nGraph: {}\nMin_Confidence: {}\nN_Properties: {}\nN_Triangles: {}\nOutput_Folder: {}\n".format(endpoint, graph, min_confidence, n_properties, n_triangles, output_folder)
num_cores = multiprocessing.cpu_count()
print "Cores:", num_cores
write_titles()
tp = top_properties()
# Making outer loop Parallel
Parallel(n_jobs=num_cores)(delayed(rangeTypes)(i=iElem, tp=tp) for iElem in range(len(types)))
print "Done."
print "\nRules saved in files {}/rules-*.tsv".format(output_folder)
if __name__ == '__main__':
############################### ARGUMENTS ################################
if len(sys.argv) < 2:
endpoint = "http://dbpedia.org/sparql"
graph = "http://dbpedia.org"
else:
endpoint = sys.argv[1]
graph = sys.argv[2]
if len(sys.argv) < 4:
min_confidence = 0.001
n_properties = 100
n_triangles = 10
else:
min_confidence = float(sys.argv[3])
n_properties = int(sys.argv[4])
n_triangles = int(sys.argv[5])
if len(sys.argv) < 7:
output_folder = "."
else:
output_folder = sys.argv[6]
run(endpoint, graph, min_confidence, n_properties, n_triangles, output_folder)