Priporočilni sistem: navodila za implementacijo skupinskega filtriranja

Napovedovanje ocen s podobnostjo med produkti (6)

Napišite razred ItemBasedPredictor, ki v konstruktorju sprejme dva parametra: min_values in threshold (privzete vrednosti obeh naj bodo 0). Razred naj na podlagi podobnosti med produkti izračuna pričakovano oceno produktov za izbranega uporabnika. Podobnost izračunajte s popravljeno cosinusno razdaljo. V razredu implementirajte metode fit in predict ter similarity(self, p1, p2), ki vrne podobnost med produktoma p1 in p2. Če je izračunana podobnost med produktoma manjša od threshold ali če imamo manj kot min_values uporabnikov, ki je ocenilo oba filma, naj bo podobnost med produktoma 0. Predlagam, da v metodi fit izračunate vse podobnosti in jih v predict in fit le uporabljate.

Vzemimo le filme, ki imajo vsaj 1000 ocen, da bo računanje v metodi fit hitrejše. Moja implementacija potrebuje nekaj sekund.

md = MovieData('data/movies.dat')
uim = UserItemData('data/user_ratedmovies.dat', min_ratings=1000)
rp = ItemBasedPredictor()
rec = Recommender(rp)
rec.fit(uim)
print(uim.movies)
print("Podobnost med filmoma 'Men in black'(1580) in 'Ghostbusters'(2716): ", rp.similarity(1580, 2716))
print("Podobnost med filmoma 'Men in black'(1580) in 'Schindler's List'(527): ", rp.similarity(1580, 527))
print("Podobnost med filmoma 'Men in black'(1580) in 'Independence day'(780): ", rp.similarity(1580, 780))

Rezultat:

Podobnost med filmoma 'Men in black'(1580) in 'Ghostbusters'(2716):  0.233955231768
Podobnost med filmoma 'Men in black'(1580) in 'Schindler's List'(527):  0.0
Podobnost med filmoma 'Men in black'(1580) in 'Independence day'(780):  0.424661258447

Če uporabimo recommender za uporabnika 78, dobimo:

print("Predictions for 78: ")
rec_items = rec.recommend(78, n=15, rec_seen=False)
for idmovie, val in rec_items:
    print("Film: {}, ocena: {}".format(md.get_title(idmovie), val))

Film: Shichinin no samurai, ocena: 4.355734702553732
Film: The Usual Suspects, ocena: 4.354681671325777
Film: The Silence of the Lambs, ocena: 4.335305215729613
Film: Sin City, ocena: 4.278687059261374
Film: Monsters, Inc., ocena: 4.2175806874956665
Film: The Incredibles, ocena: 4.207098405922537
Film: The Lord of the Rings: The Fellowship of the Ring, ocena: 4.15279203714804
Film: Batman Begins, ocena: 4.146413660330134
Film: Die Hard, ocena: 4.125915501065452
Film: Rain Man, ocena: 4.071535187988423
Film: The Lord of the Rings: The Return of the King, ocena: 4.020237426179001
Film: A Beautiful Mind, ocena: 4.015142457113093
Film: Good Will Hunting, ocena: 4.009280780263334
Film: The Lord of the Rings: The Two Towers, ocena: 3.9414763181545847
Film: Indiana Jones and the Last Crusade, ocena: 3.7969765828982167

Najbolj podobni filmi (6)

Izpišite 20 parov najbolj podobnih filmov. Če spet uporabimo le filme, ki imajo vsaj 1000 ocen, dobimo:

Film1: The Lord of the Rings: The Return of the King, Film2: The Lord of the Rings: The Two Towers, podobnost: 0.8439842148481411
Film1: The Lord of the Rings: The Two Towers, Film2: The Lord of the Rings: The Return of the King, podobnost: 0.8439842148481411
Film1: The Lord of the Rings: The Two Towers, Film2: The Lord of the Rings: The Fellowship of the Ring, podobnost: 0.8231885401761887
Film1: The Lord of the Rings: The Fellowship of the Ring, Film2: The Lord of the Rings: The Two Towers, podobnost: 0.8231885401761887
Film1: The Lord of the Rings: The Return of the King, Film2: The Lord of the Rings: The Fellowship of the Ring, podobnost: 0.8079374897442487
Film1: The Lord of the Rings: The Fellowship of the Ring, Film2: The Lord of the Rings: The Return of the King, podobnost: 0.8079374897442487
Film1: Kill Bill: Vol. 2, Film2: Kill Bill: Vol. 2, podobnost: 0.7372340224381033
Film1: Kill Bill: Vol. 2, Film2: Kill Bill: Vol. 2, podobnost: 0.7372340224381033
Film1: Star Wars: Episode V - The Empire Strikes Back, Film2: Star Wars, podobnost: 0.7021321132220316
Film1: Star Wars, Film2: Star Wars: Episode V - The Empire Strikes Back, podobnost: 0.7021321132220316
Film1: The Mask, Film2: Ace Ventura: Pet Detective, podobnost: 0.6616471778494041
Film1: Ace Ventura: Pet Detective, Film2: The Mask, podobnost: 0.6616471778494041
Film1: Star Wars: Episode VI - Return of the Jedi, Film2: Star Wars: Episode V - The Empire Strikes Back, podobnost: 0.5992253753778951
Film1: Star Wars: Episode V - The Empire Strikes Back, Film2: Star Wars: Episode VI - Return of the Jedi, podobnost: 0.5992253753778951
Film1: Star Wars: Episode I - The Phantom Menace, Film2: Independence Day, podobnost: 0.5610426219249982
Film1: Independence Day, Film2: Star Wars: Episode I - The Phantom Menace, podobnost: 0.5610426219249982
Film1: Austin Powers: The Spy Who Shagged Me, Film2: Ace Ventura: Pet Detective, podobnost: 0.5546511205201548
Film1: Ace Ventura: Pet Detective, Film2: Austin Powers: The Spy Who Shagged Me, podobnost: 0.5546511205201548
Film1: Star Wars: Episode VI - Return of the Jedi, Film2: Star Wars, podobnost: 0.5537849318137374
Film1: Star Wars, Film2: Star Wars: Episode VI - Return of the Jedi, podobnost: 0.5537849318137374

Priporočanje glede na trenutno ogledano vsebino (7)

Kaj bi pokazali v kategoriji "Gledalci, ki so gledali A, so gledali tudi B"? Razredu ItemBasedPredictor dodajte metodo similarItems(self, item, n), ki vrne n najbolj podobnih filmov izbranemu filmu.

rec_items = rp.similarItems(4993, 10)
print('Filmi podobni "The Lord of the Rings: The Fellowship of the Ring": ')
for idmovie, val in rec_items:
    print("Film: {}, ocena: {}".format(md.get_title(idmovie), val))

Filmi podobni "The Lord of the Rings: The Fellowship of the Ring": 
Film: The Lord of the Rings: The Two Towers, ocena: 0.8231885401761887
Film: The Lord of the Rings: The Return of the King, ocena: 0.8079374897442487
Film: Star Wars: Episode V - The Empire Strikes Back, ocena: 0.23961943073496453
Film: Star Wars, ocena: 0.21965586527074088
Film: The Matrix, ocena: 0.2151555270688026
Film: Raiders of the Lost Ark, ocena: 0.19944276706345052
Film: The Usual Suspects, ocena: 0.18321188451910767
Film: Blade Runner, ocena: 0.16399681315410303
Film: Schindler's List, ocena: 0.16105905138148724
Film: Monty Python and the Holy Grail, ocena: 0.15780453798519137

Priporočilo zase (7)

Naredite še priporočilo zase z metodo "item-based"; izberite si cca. 20 filmov, ki jih poznate in jih ročno ocenite. Dodajte svoje ocene v movielens bazo in si priporočite 10 filmov.

Napovedovanje z metodo Slope one (7)

Napišite prediktor SlopeOnePredictor, ki izračuna napovedano vrednost ocen za produkte z metodo Slope one. Primer:

md = MovieData('data/movies.dat')
uim = UserItemData('data/user_ratedmovies.dat', min_ratings=1000)
rp = SlopeOnePredictor()
rec = Recommender(rp)
rec.fit(uim)

print("Predictions for 78: ")
rec_items = rec.recommend(78, n=15, rec_seen=False)
for idmovie, val in rec_items:
    print("Film: {}, ocena: {}".format(md.get_title(idmovie), val))

Rezultat:

Predictions for 78: 
Film: The Usual Suspects, ocena: 4.325079182263173
Film: The Lord of the Rings: The Fellowship of the Ring, ocena: 4.155293229840448
Film: The Lord of the Rings: The Return of the King, ocena: 4.153135076202185
Film: The Silence of the Lambs, ocena: 4.127978169643881
Film: Shichinin no samurai, ocena: 4.119790444913598
Film: The Lord of the Rings: The Two Towers, ocena: 4.083325894849594
Film: Indiana Jones and the Last Crusade, ocena: 3.9670398355464194
Film: The Incredibles, ocena: 3.9664496674557546
Film: Good Will Hunting, ocena: 3.963362387354114
Film: Sin City, ocena: 3.942619137615212
Film: Batman Begins, ocena: 3.9375326640077017
Film: A Beautiful Mind, ocena: 3.9140940935239508
Film: Rain Man, ocena: 3.9107819079644943
Film: Monsters, Inc., ocena: 3.8819375978658006
Film: Finding Nemo, ocena: 3.8807711131654794