strategy.py
3.5 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
#!/usr/bin/python
# AppRecommender - A GNU/Linux application recommender
#
# Copyright (C) 2010 Tassia Camoes <tassia@gmail.com>
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
import xapian
from data import *
from recommender import *
class ReputationHeuristic:
""" Abstraction for diferent reputation heuristics. """
class BugsHeuristic(ReputationHeuristic):
""" Reputation heuristic based on quantity of open bugs. """
class RCBugsHeuristic(ReputationHeuristic):
""" Reputation heuristic based on quantity of RC bugs. """
class PopularityHeuristic(ReputationHeuristic):
""" Reputation heuristic based on popularity of packages. """
class PkgMatchDecider(xapian.MatchDecider):
""" Extends xapian.MatchDecider to disconsider installed packages. """
def __init__(self, installed_pkgs):
xapian.MatchDecider.__init__(self)
self.installed_pkgs = installed_pkgs
def __call__(self, doc):
return doc.get_data() not in self.installed_pkgs
class RecommendationStrategy:
""" Abstraction for diferent recommendation strategy. """
class ItemReputationStrategy(RecommendationStrategy):
""" Recommendation strategy based on items reputation. """
def run(self,items_list,heuristic):
""" """
return RecomendationResult()
class ContentBasedStrategy(RecommendationStrategy):
""" Content-based recommendation strategy. """
#def __init__(self,items_repository):
# self.items_repository = items_repository
def __init__(self,reindex):
self.reindex = reindex
def run(self,recommender,user):
""" """
best_tags = recommender.items_repository.get_relevant_tags(user.items(),
50)
debtags_index = DebtagsIndex(
os.path.expanduser("~/.app-recommender/debtags_index"))
debtags_index.load(recommender.items_repository,self.reindex)
qp = xapian.QueryParser()
query = qp.parse_query(best_tags)
enquire = xapian.Enquire(debtags_index.index)
enquire.set_query(query)
mset = enquire.get_mset(0, 20, None, PkgMatchDecider(user.items()))
item_score = {}
for m in mset:
item_score[m.document.get_data()] = m.rank
return RecommendationResult(item_score,20)
class ColaborativeStrategy(RecommendationStrategy):
""" Colaborative recommendation strategy. """
def run(self,user,users_repository,similarity_measure):
""" """
return RecomendationResult()
class KnowledgeBasedStrategy(RecommendationStrategy):
""" Knowledge-based recommendation strategy. """
def run(self,user,knowledge_repository):
""" """
return RecomendationResult()
class DemographicStrategy(RecommendationStrategy):
""" Recommendation strategy based on demographic data. """
def run(self,user,items_repository):
""" """
return RecomendationResult()