Interactive CRS (minimal approach)

example.py

from scipy import spatial
import math

# User preferences/interests
user_embedding = [0, 0, 0, 0]

# Item representation { PRODUCT TYPE (1=MOUSE), COLOR (1=BLACK), MULTI_DEVICE (1=YES), HIGH_DPI (1=YES) }
item_embeddings = [
    [1, 0, 0, 0],
    [1, 1, 0, 1],
    [1, 0, 0, 1],
    [1, 1, 1, 1],
    [1, 0, 1, 0],
    [0, 1, 1, 0],
    [1, 0, 0, 0],
    [1, 1, 0, 0],
    [1, 0, 1, 0],
    [1, 1, 1, 0],
]

# Session based
likes = []
forbidden = []


def build_item_score(item, P):
    s = 0
    for i, p in enumerate(P):
        if item[i] == p:
            s += 1
    return s / len(P)


def build_sim_score(item, L):
    best_cos = 0
    for l in L:
        liked_item = item_embeddings[l]
        s = sim_cos_score(item, liked_item)
        if s > best_cos:
            best_cos = s
    return best_cos


def get_available_items():
    l = item_embeddings.copy()

    for f in forbidden:
        l.pop(f)

    return l


def sim_cos_score(i1, i2):
    return 1 - spatial.distance.cosine(i1, i2)


def sigmoid(x):
    return 1 / (1 + math.exp(-x))


def build_scores():
    candidates = get_available_items()
    scores = []

    for item in candidates:
        # User - Item comparison
        s1 = build_item_score(item, user_embedding)

        # Item - Item comparison
        s2 = build_sim_score(item, likes)

        # Normalize score
        sf = sigmoid(s1 + s2)

        scores.append(sf)

    return scores


current_turn = 0
max_turns = 5

# Conversation simulation based on defined questionnaire
# Basically, we start with an user_embedding of zero values only
# Turn 1: zero values
# Turn 2: user wants a MOUSE [1, 0, 0, 0]
# Turn 3: user wants a mouse which is BLACK [1, 1, 0, 0]
# Turn 4: user wants a mouse which is BLACK and is supporting multi-devices [1, 1, 1, 0]
#         Best results have indexes 3 and 9 in item_embeddings = [1, 1, 1, 0]
# Turn 5: user likes index=1 of item_embeddings = [1, 1, 0, 1] which is not supporting multi device but high DPI becomes another priority (preference)
#         Best recommendation is now index=3 = [1, 1, 1, 1]
while current_turn < max_turns:
    if current_turn == 1:
        user_embedding = [1, 0, 0]
    if current_turn == 2:
        user_embedding = [1, 1, 0]
    if current_turn == 3:
        user_embedding = [1, 1, 1]

    if current_turn == 4:
        likes = [2]

    print('TURN', current_turn + 1, build_scores())

    current_turn += 1