- добавлена модель персональных весов рекомендаций с нормализацией и ограничениями
- добавлена миграция для user_recommendation_weights и breakdown-полей recommendation_events - рекомендации теперь используют пользовательские score/vector веса - feedback ACCEPTED/REJECTED обновляет score-веса пользователя по последней рекомендации - добавлен API для чтения и ручного обновления весов рекомендаций - добавлен onboarding endpoint для начальной калибровки пользователя - добавлены стили рекомендаций: balanced, quality first, mood first, discovery, similar to favorites - onboarding сохраняет предпочтения, лайки/дизлайки, библиотеку, просмотренные фильмы и стартовые веса - добавлены метрика обновления весов и расширенные smoke/unit тесты
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skettiks
@@ -4,8 +4,12 @@ import com.fasterxml.jackson.databind.ObjectMapper
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import com.project.movienight.adapters.web.dto.request.CreateFilmRequest
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import com.project.movienight.adapters.web.dto.request.CreateUserRequest
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import com.project.movienight.adapters.web.dto.request.RateFilmRequest
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import com.project.movienight.adapters.web.dto.request.RecommendationOnboardingRequest
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import com.project.movienight.adapters.web.dto.request.UpdateUserRecommendationWeightsRequest
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import com.project.movienight.adapters.web.dto.request.UpsertUserPreferencesRequest
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import org.junit.jupiter.api.AfterEach
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import org.junit.jupiter.api.Assertions.assertNotEquals
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import org.junit.jupiter.api.Assertions.assertTrue
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import org.junit.jupiter.api.BeforeEach
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import org.junit.jupiter.api.Test
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import org.springframework.beans.factory.annotation.Autowired
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@@ -110,6 +114,39 @@ class RecommendationSmokeTest {
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val firstFilmId = filmIdByTitle.getValue("Orbital Drift")
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val secondFilmId = filmIdByTitle.getValue("Small Town Summer")
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mockMvc
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.get("/api/users/$userId/recommendation-weights")
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.andExpect {
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status { isOk() }
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jsonPath("$.relevanceWeight") { value(0.55) }
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jsonPath("$.plotVectorWeight") { value(0.35) }
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}
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mockMvc
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.put("/api/users/$userId/recommendation-weights") {
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contentType = MediaType.APPLICATION_JSON
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content =
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objectMapper.writeValueAsString(
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UpdateUserRecommendationWeightsRequest(
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relevanceWeight = 0.60,
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qualityWeight = 0.10,
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contextWeight = 0.15,
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noveltyWeight = 0.10,
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diversityWeight = 0.05,
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genreVectorWeight = 0.30,
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plotVectorWeight = 0.30,
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moodVectorWeight = 0.20,
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eraVectorWeight = 0.05,
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peopleVectorWeight = 0.10,
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contentTypeVectorWeight = 0.05,
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),
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)
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}.andExpect {
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status { isOk() }
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jsonPath("$.relevanceWeight") { value(0.6) }
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jsonPath("$.genreVectorWeight") { value(0.3) }
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}
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mockMvc
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.put("/api/users/$userId/preferences") {
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contentType = MediaType.APPLICATION_JSON
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@@ -163,14 +200,38 @@ class RecommendationSmokeTest {
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jsonPath("$[0].reasons[0]") { exists() }
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}
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val recommendedBreakdownCount =
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jdbcTemplate.queryForObject(
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"""
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SELECT COUNT(*)
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FROM recommendation_events
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WHERE user_id = ?
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AND film_id = ?
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AND event_type = 'RECOMMENDED'
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AND relevance_score IS NOT NULL
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AND quality_score IS NOT NULL
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""".trimIndent(),
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Int::class.java,
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userId,
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firstFilmId,
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)
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assertTrue((recommendedBreakdownCount ?: 0) > 0)
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val weightsBeforeFeedback = findScoreWeights(userId)
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mockMvc
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.post("/api/users/$userId/recommendations/$firstFilmId/accept")
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.andExpect {
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status { isOk() }
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jsonPath("$.filmId") { value(firstFilmId.toString()) }
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jsonPath("$.eventType") { value("ACCEPTED") }
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jsonPath("$.relevanceScore") { exists() }
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}
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val weightsAfterAccept = findScoreWeights(userId)
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assertNotEquals(weightsBeforeFeedback, weightsAfterAccept)
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assertTrue(weightsAfterAccept.all { it in 0.05..0.75 })
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mockMvc
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.post("/api/users/$userId/recommendations/$firstFilmId/reject")
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.andExpect {
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@@ -190,12 +251,159 @@ class RecommendationSmokeTest {
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}
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}
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@Test
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fun `should complete recommendation onboarding`() {
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mockMvc
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.post("/api/users") {
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contentType = MediaType.APPLICATION_JSON
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content = objectMapper.writeValueAsString(CreateUserRequest(name = "Alex", email = "alex@example.com"))
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}.andExpect {
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status { isCreated() }
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}
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val userId =
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UUID.fromString(
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jdbcTemplate.queryForObject(
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"SELECT id FROM users WHERE email = ?",
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String::class.java,
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"alex@example.com",
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),
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)
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val likedFilmId = createFilm(title = "Neon Rescue", genres = listOf("SCI-FI"), imdbRating = 8.8)
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val dislikedFilmId = createFilm(title = "Quiet Village", genres = listOf("DRAMA"), imdbRating = 5.0)
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val libraryFilmId = createFilm(title = "Space Trial", genres = listOf("SCI-FI"), imdbRating = 7.8)
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val watchedFilmId = createFilm(title = "Old Mission", genres = listOf("THRILLER"), imdbRating = 8.1)
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mockMvc
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.post("/api/users/$userId/recommendation-onboarding") {
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contentType = MediaType.APPLICATION_JSON
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content =
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objectMapper.writeValueAsString(
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RecommendationOnboardingRequest(
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weightedGenres = mapOf("SCI-FI" to 5, "THRILLER" to 3),
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moods = listOf("focused", "tense"),
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contentTypes = listOf("FILM"),
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likedFilmIds = listOf(likedFilmId),
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dislikedFilmIds = listOf(dislikedFilmId),
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libraryFilmIds = listOf(libraryFilmId),
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watchedFilmIds = listOf(watchedFilmId),
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recommendationStyle = "DISCOVERY",
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),
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)
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}.andExpect {
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status { isOk() }
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jsonPath("$.preferences.weightedGenres['SCI-FI']") { value(5) }
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jsonPath("$.weights.noveltyWeight") { value(0.25) }
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jsonPath("$.weights.diversityWeight") { value(0.25) }
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jsonPath("$.likedFilmsCount") { value(1) }
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jsonPath("$.dislikedFilmsCount") { value(1) }
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jsonPath("$.libraryFilmsCount") { value(1) }
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jsonPath("$.watchedFilmsCount") { value(1) }
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}
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assertDatabaseCount(
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"""
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SELECT COUNT(*)
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FROM film_ratings
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WHERE user_id = ?
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AND film_id IN (?, ?)
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""".trimIndent(),
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userId,
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likedFilmId,
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dislikedFilmId,
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)
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assertDatabaseCount(
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"""
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SELECT COUNT(*)
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FROM favorites
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WHERE user_id = ?
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AND film_id = ?
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AND is_viewed = TRUE
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""".trimIndent(),
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userId,
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watchedFilmId,
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)
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mockMvc
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.get("/api/users/$userId/recommendations") {
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param("contentType", "FILM")
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param("limit", "3")
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}.andExpect {
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status { isOk() }
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jsonPath("$[0].reasons[0]") { exists() }
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}
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}
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private fun cleanDatabase() {
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jdbcTemplate.execute("DELETE FROM recommendation_events")
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jdbcTemplate.execute("DELETE FROM user_recommendation_weights")
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jdbcTemplate.execute("DELETE FROM film_ratings")
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jdbcTemplate.execute("DELETE FROM user_preferences")
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jdbcTemplate.execute("DELETE FROM favorites")
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jdbcTemplate.execute("DELETE FROM films")
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jdbcTemplate.execute("DELETE FROM users")
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}
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private fun findScoreWeights(userId: UUID): List<Double> =
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jdbcTemplate
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.queryForMap(
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"""
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SELECT relevance_weight,
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quality_weight,
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context_weight,
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novelty_weight,
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diversity_weight
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FROM user_recommendation_weights
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WHERE user_id = ?
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""".trimIndent(),
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userId,
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).let { row ->
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listOf(
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row.getValue("RELEVANCE_WEIGHT"),
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row.getValue("QUALITY_WEIGHT"),
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row.getValue("CONTEXT_WEIGHT"),
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row.getValue("NOVELTY_WEIGHT"),
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row.getValue("DIVERSITY_WEIGHT"),
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).map { (it as Number).toDouble() }
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}
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private fun createFilm(
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title: String,
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genres: List<String>,
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imdbRating: Double,
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): UUID {
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mockMvc
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.post("/api/films") {
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contentType = MediaType.APPLICATION_JSON
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content =
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objectMapper.writeValueAsString(
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CreateFilmRequest(
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title = title,
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description = "$title description",
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contentType = "FILM",
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genres = genres,
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imdbRating = imdbRating,
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),
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)
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}.andExpect {
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status { isCreated() }
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}
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return UUID.fromString(
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jdbcTemplate.queryForObject(
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"SELECT id FROM films WHERE title = ?",
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String::class.java,
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title,
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),
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)
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}
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private fun assertDatabaseCount(
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sql: String,
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vararg args: Any,
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) {
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val count = jdbcTemplate.queryForObject(sql, Int::class.java, *args)
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assertTrue((count ?: 0) > 0)
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}
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}
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@@ -0,0 +1,74 @@
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package com.project.movienight.domain.model
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import org.junit.jupiter.api.Assertions.assertEquals
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import org.junit.jupiter.api.Assertions.assertTrue
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import org.junit.jupiter.api.Test
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import java.util.UUID
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class UserRecommendationWeightsTest {
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@Test
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fun `should keep default weights normalized`() {
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val weights = UserRecommendationWeights.defaultFor(UUID.randomUUID()).normalized()
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assertEquals(1.0, weights.scoreWeightSum(), EPSILON)
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assertEquals(1.0, weights.vectorWeightSum(), EPSILON)
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assertEquals(0.55, weights.relevanceWeight, EPSILON)
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assertEquals(0.35, weights.plotVectorWeight, EPSILON)
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}
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@Test
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fun `should normalize and bound invalid weights`() {
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val weights =
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UserRecommendationWeights(
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userId = UUID.randomUUID(),
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relevanceWeight = 100.0,
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qualityWeight = -5.0,
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contextWeight = 0.0,
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noveltyWeight = 0.0,
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diversityWeight = 0.0,
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genreVectorWeight = 100.0,
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plotVectorWeight = 0.0,
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moodVectorWeight = 0.0,
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eraVectorWeight = 0.0,
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peopleVectorWeight = 0.0,
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contentTypeVectorWeight = 0.0,
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).normalized()
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assertEquals(1.0, weights.scoreWeightSum(), EPSILON)
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assertEquals(1.0, weights.vectorWeightSum(), EPSILON)
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assertTrue(
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listOf(
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weights.relevanceWeight,
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weights.qualityWeight,
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weights.contextWeight,
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weights.noveltyWeight,
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weights.diversityWeight,
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).all { it in UserRecommendationWeights.MIN_SCORE_WEIGHT..UserRecommendationWeights.MAX_SCORE_WEIGHT },
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)
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assertTrue(
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listOf(
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weights.genreVectorWeight,
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weights.plotVectorWeight,
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weights.moodVectorWeight,
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weights.eraVectorWeight,
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weights.peopleVectorWeight,
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weights.contentTypeVectorWeight,
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).all { it in UserRecommendationWeights.MIN_VECTOR_WEIGHT..UserRecommendationWeights.MAX_VECTOR_WEIGHT },
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)
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}
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private fun UserRecommendationWeights.scoreWeightSum(): Double =
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relevanceWeight + qualityWeight + contextWeight + noveltyWeight + diversityWeight
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private fun UserRecommendationWeights.vectorWeightSum(): Double =
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genreVectorWeight +
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plotVectorWeight +
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moodVectorWeight +
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eraVectorWeight +
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peopleVectorWeight +
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contentTypeVectorWeight
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private companion object {
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private const val EPSILON = 0.000001
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}
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}
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