public void preferencesFetchedOnlyOnce()
{
var dataModelMock = new DynamicMock(typeof(IDataModel));
var itemSimilarityMock = new DynamicMock(typeof(IItemSimilarity));
var candidateItemsStrategyMock = new DynamicMock(typeof(ICandidateItemsStrategy));
var mostSimilarItemsCandidateItemsStrategyMock =
new DynamicMock(typeof(IMostSimilarItemsCandidateItemsStrategy));
IPreferenceArray preferencesFromUser = new GenericUserPreferenceArray(
new List <IPreference>()
{
new GenericPreference(1L, 1L, 5.0f), new GenericPreference(1L, 2L, 4.0f)
});
dataModelMock.ExpectAndReturn("GetMinPreference", float.NaN);
dataModelMock.ExpectAndReturn("GetMaxPreference", float.NaN);
dataModelMock.ExpectAndReturn("GetPreferencesFromUser", preferencesFromUser, 1L);
var dataModel = (IDataModel)dataModelMock.MockInstance;
candidateItemsStrategyMock.ExpectAndReturn("GetCandidateItems", new FastIDSet(new long[] { 3L, 4L }),
1L, preferencesFromUser, dataModel);
itemSimilarityMock.ExpectAndReturn("ItemSimilarities", new double[] { 0.5, 0.3 },
3L, preferencesFromUser.GetIDs());
itemSimilarityMock.ExpectAndReturn("ItemSimilarities", new double[] { 0.4, 0.1 },
4L, preferencesFromUser.GetIDs());
//EasyMock.replay(dataModel, itemSimilarity, candidateItemsStrategy, mostSimilarItemsCandidateItemsStrategy);
IRecommender recommender = new GenericItemBasedRecommender((IDataModel)dataModel,
(IItemSimilarity)itemSimilarityMock.MockInstance,
(ICandidateItemsStrategy)candidateItemsStrategyMock.MockInstance,
(IMostSimilarItemsCandidateItemsStrategy)mostSimilarItemsCandidateItemsStrategyMock.MockInstance);
recommender.Recommend(1L, 3);
dataModelMock.Verify();
itemSimilarityMock.Verify();
candidateItemsStrategyMock.Verify();
mostSimilarItemsCandidateItemsStrategyMock.Verify();
//EasyMock.verify(dataModel, itemSimilarity, candidateItemsStrategy, mostSimilarItemsCandidateItemsStrategy);
}
public List <MovieRecommendationDto> GetRecommendedMovies(int[] preferredMovieIds)
{
var dataModel = GetDataModel();
// recommendation is performed for the user that is missed in the preferences data
var plusAnonymModel = new PlusAnonymousUserDataModel(dataModel);
var prefArr = new GenericUserPreferenceArray(preferredMovieIds.Length);
prefArr.SetUserID(0, PlusAnonymousUserDataModel.TEMP_USER_ID);
for (int i = 0; i < preferredMovieIds.Length; i++)
{
prefArr.SetItemID(i, preferredMovieIds[i]);
// in this example we have no ratings of movies preferred by the user
prefArr.SetValue(i, 5); // lets assume max rating
}
plusAnonymModel.SetTempPrefs(prefArr);
var similarity = new LogLikelihoodSimilarity(plusAnonymModel);
var neighborhood = new NearestNUserNeighborhood(15, similarity, plusAnonymModel);
var recommender = new GenericUserBasedRecommender(plusAnonymModel, neighborhood, similarity);
var recommendedItems = recommender.Recommend(PlusAnonymousUserDataModel.TEMP_USER_ID, 5, null);
var movieIds = recommendedItems.Select(ri => (int)ri.GetItemID()).ToArray();
var movieIdToTitleDictionary = _unitOfWork.MovieRepository.GetMovieIdToTileDictionary(movieIds);
var recommendedMovies = new List <MovieRecommendationDto>();
foreach (var item in recommendedItems)
{
var movieId = (int)item.GetItemID();
var movieTitle = movieIdToTitleDictionary[movieId];
recommendedMovies.Add(
new MovieRecommendationDto
{
MovieId = movieId,
MovieTitle = movieTitle,
Rating = item.GetValue()
});
}
return(recommendedMovies);
}
public ActionResult Recommend(string filmIdsJson)
{
var filmIds = (new JavaScriptSerializer()).Deserialize <long[]>(filmIdsJson);
var pathToDataFile =
Path.Combine(System.Web.HttpRuntime.AppDomainAppPath, "data/albums.dat");
if (dataModel == null)
{
try
{
dataModel = new FileDataModel(pathToDataFile, false, FileDataModel.DEFAULT_MIN_RELOAD_INTERVAL_MS, false);
}
catch (Exception e)
{
var exe = e.ToString();
}
}
var plusAnonymModel = new PlusAnonymousUserDataModel(dataModel);
var prefArr = new GenericUserPreferenceArray(filmIds.Length);
prefArr.SetUserID(0, PlusAnonymousUserDataModel.TEMP_USER_ID);
for (int i = 0; i < filmIds.Length; i++)
{
prefArr.SetItemID(i, filmIds[i]);
prefArr.SetValue(i, 5); // lets assume max rating
}
plusAnonymModel.SetTempPrefs(prefArr);
var similarity = new LogLikelihoodSimilarity(plusAnonymModel);
var neighborhood = new NearestNUserNeighborhood(15, similarity, plusAnonymModel);
var recommender = new GenericBooleanPrefUserBasedRecommender(plusAnonymModel, neighborhood, similarity);
var recommendedItems = recommender.Recommend(PlusAnonymousUserDataModel.TEMP_USER_ID, 5, null);
return(Json(recommendedItems.Select(ri => new Dictionary <string, object>()
{
{ "id", ri.GetItemID() },
{ "rating", ri.GetValue() },
}).ToArray()));
}
public void testStrategy()
{
FastIDSet itemIDsFromUser123 = new FastIDSet();
itemIDsFromUser123.Add(1L);
FastIDSet itemIDsFromUser456 = new FastIDSet();
itemIDsFromUser456.Add(1L);
itemIDsFromUser456.Add(2L);
List <IPreference> prefs = new List <IPreference>();
prefs.Add(new GenericPreference(123L, 1L, 1.0f));
prefs.Add(new GenericPreference(456L, 1L, 1.0f));
IPreferenceArray preferencesForItem1 = new GenericItemPreferenceArray(prefs);
var dataModelMock = new DynamicMock(typeof(IDataModel));
dataModelMock.ExpectAndReturn("GetPreferencesForItem", preferencesForItem1, (1L));
dataModelMock.ExpectAndReturn("GetItemIDsFromUser", itemIDsFromUser123, (123L));
dataModelMock.ExpectAndReturn("GetItemIDsFromUser", itemIDsFromUser456, (456L));
IPreferenceArray prefArrayOfUser123 =
new GenericUserPreferenceArray(new List <IPreference>()
{
new GenericPreference(123L, 1L, 1.0f)
});
ICandidateItemsStrategy strategy = new PreferredItemsNeighborhoodCandidateItemsStrategy();
//EasyMock.replay(dataModel);
FastIDSet candidateItems = strategy.GetCandidateItems(123L, prefArrayOfUser123, (IDataModel)dataModelMock.MockInstance);
Assert.AreEqual(1, candidateItems.Count());
Assert.True(candidateItems.Contains(2L));
dataModelMock.Verify(); // EasyMock.verify(dataModel);
}
/// <summary>
/// 推荐
/// </summary>
/// <param name="pageIndex">当前页</param>
/// <param name="pageSize">页容量</param>
/// <param name="showCount">显示数量</param>
/// <returns></returns>
public List <Books> RecommendBooks(int pageIndex, int pageSize, int showCount)
{
#region 推荐
List <Books> books = null;
if (Session["user"] != null)
{
Users user = Session["user"] as Users;
#region 构建用户行为数组
var loglist = logbll.LoadEntities(c => c.userID == user.Id).ToList();
StringBuilder sb = new StringBuilder();
if (loglist.Count > 0)
{
sb.Append("[");
int j = 0;
foreach (var item in loglist)
{
j++;
sb.Append(item.itemID.ToString());
if (j != loglist.Count)
{
sb.Append(",");
}
}
sb.Append("]");
}
#endregion
if (string.IsNullOrEmpty(sb.ToString()))
{
//冷启动
books = booksbll.LoadEntities(c => true).OrderByDescending(c => c.rating).Skip((pageIndex - 1) * pageSize).Take(pageSize).ToList();
}
else
{
var filmIds = (new JavaScriptSerializer()).Deserialize <long[]>(sb.ToString());
var logmodel = settingbll.LoadEntities(c => c.id == 16).FirstOrDefault();
string path = "";
if (logmodel != null && logmodel.value == "true")
{
path = "data/ratings1.dat";
}
else
{
path = "data/ratings.dat";
}
var pathToDataFile =
Path.Combine(System.Web.HttpRuntime.AppDomainAppPath, path);
if (dataModel == null)
{
dataModel = new FileDataModel(pathToDataFile, false, FileDataModel.DEFAULT_MIN_RELOAD_INTERVAL_MS, false);
}
var plusAnonymModel = new PlusAnonymousUserDataModel(dataModel);
var prefArr = new GenericUserPreferenceArray(filmIds.Length);
prefArr.SetUserID(0, PlusAnonymousUserDataModel.TEMP_USER_ID);
for (int i = 0; i < filmIds.Length; i++)
{
prefArr.SetItemID(i, filmIds[i]);
prefArr.SetValue(i, 5); // lets assume max rating
}
plusAnonymModel.SetTempPrefs(prefArr);
var similarity = new LogLikelihoodSimilarity(plusAnonymModel);
var neighborhood = new NearestNUserNeighborhood(15, similarity, plusAnonymModel);
var recommender = new GenericUserBasedRecommender(plusAnonymModel, neighborhood, similarity);
var recommendedItems = recommender.Recommend(PlusAnonymousUserDataModel.TEMP_USER_ID, showCount, null);
List <Books> newbooks = new List <Books>();
foreach (var item in recommendedItems)
{
int bid = Convert.ToInt32(item.GetItemID());
newbooks.Add(booksbll.LoadEntities(c => c.Id == bid).FirstOrDefault());
}
books = newbooks.Skip((pageIndex - 1) * pageSize).Take(pageSize).ToList();
}
}
else //不推荐
{
books = booksbll.LoadEntities(c => true).OrderByDescending(c => c.rating).Skip((pageIndex - 1) * pageSize).Take(pageSize).ToList();
}
#endregion
return(books.Count() <= 0 ? booksbll.LoadEntities(c => true).OrderByDescending(c => c.rating).Skip((pageIndex - 1) * pageSize).Take(pageSize).ToList() : books);
}
public ActionResult GetRecommendedbooks()
{
var csv = new CsvReader(new StreamReader(System.Web.HttpContext.Current.Server.MapPath("~/App_Data/books.csv")));
var records = csv.GetRecords <BookRecord>().ToList();
int favouriteGenre = db.Users.Where(u => u.UserName == User.Identity.Name).Select(u => u.genreID).SingleOrDefault();
var userRentals = db.Rentals.Where(m => m.rentalUser == User.Identity.Name).Join(db.Books,
r => r.rentalBook,
m => m.bookName,
(r, m) => new
{
genreId = m.genreID,
bookName = m.bookName,
rentalUer = r.rentalUser
});
if (userRentals.Count() == 0)
{
return(Json(new Dictionary <string, object>()
{
{ "book_id", 0 },
{ "rating", 0 },
}));
}
else if (userRentals.Where(m => m.genreId == favouriteGenre).Count() != 0)
{
userRentals = userRentals.Where(m => m.genreId == favouriteGenre);
}
long[] bookIdsTemp = new long[userRentals.Count()];
int bookCounter = 0;
foreach (var item in userRentals)
{
foreach (var record in records)
{
if (item.bookName == record.title)
{
if (!bookIdsTemp.Contains(record.bookId))
{
bookIdsTemp[bookCounter] = record.bookId;
bookCounter++;
}
}
}
}
long[] bookIds = new long[bookCounter];
for (int i = 0; i < bookCounter; i++)
{
bookIds[i] = bookIdsTemp[i];
}
var dataModel = GetDataModel();
// recommendation is performed for the user that is missed in the preferences data
var plusAnonymModel = new PlusAnonymousUserDataModel(dataModel);
var prefArr = new GenericUserPreferenceArray(userRentals.Count());
prefArr.SetUserID(0, PlusAnonymousUserDataModel.TEMP_USER_ID);
for (int i = 0; i < bookIds.Length; i++)
{
prefArr.SetItemID(i, bookIds[i]);
// in this example we have no ratings of books preferred by the user
prefArr.SetValue(i, 5); // lets assume max rating
}
plusAnonymModel.SetTempPrefs(prefArr);
var similarity = new LogLikelihoodSimilarity(plusAnonymModel);
var neighborhood = new NearestNUserNeighborhood(15, similarity, plusAnonymModel);
var recommender = new GenericUserBasedRecommender(plusAnonymModel, neighborhood, similarity);
var recommendedItems = recommender.Recommend(PlusAnonymousUserDataModel.TEMP_USER_ID, 1, null);
if (recommendedItems.Count() == 0)
{
return(Json(new Dictionary <string, object>()
{
{ "book_id", 0 },
{ "rating", 0 },
}));
}
return(Json(recommendedItems.Select(ri => new Dictionary <string, object>()
{
{ "book_id", ri.GetItemID() },
{ "rating", ri.GetValue() },
}).ToArray()[0]));
}
protected void processLine <T>(string line, FastByIDMap <T> data, FastByIDMap <FastByIDMap <DateTime?> > timestamps, bool fromPriorData)
{
bool flag2;
int num5;
PreferenceArray array2;
int num6;
float num7;
if ((line.Length == 0) || (line[0] == COMMENT_CHAR))
{
return;
}
string[] strArray = line.Split(new char[] { this.delimiter });
string str = strArray[0];
string str2 = strArray[1];
string str3 = strArray[2];
bool flag = strArray.Length > 3;
string timestampString = flag ? strArray[3] : null;
long key = this.readUserIDFromString(str);
long itemID = this.readItemIDFromString(str2);
if (this.transpose)
{
long num3 = key;
key = itemID;
itemID = num3;
}
T local = data.get(key);
if (!fromPriorData)
{
IEnumerable <Preference> source = (IEnumerable <Preference>)local;
if (flag || !string.IsNullOrWhiteSpace(str3))
{
num7 = float.Parse(str3, CultureInfo.InvariantCulture);
flag2 = false;
if (this.uniqueUserItemCheck && (source != null))
{
foreach (Preference preference in source)
{
if (preference.getItemID() == itemID)
{
flag2 = true;
preference.setValue(num7);
break;
}
}
}
if (!flag2)
{
if (source == null)
{
source = new List <Preference>(5);
data.put(key, (T)source);
}
if (source is IList <Preference> )
{
((IList <Preference>)source).Add(new GenericPreference(key, itemID, num7));
}
}
this.addTimestamp(key, itemID, timestampString, timestamps);
return;
}
if (source != null)
{
IEnumerator <Preference> enumerator = ((IEnumerable <Preference>)source.ToArray <Preference>()).GetEnumerator();
while (enumerator.MoveNext())
{
Preference current = enumerator.Current;
if (current.getItemID() == itemID)
{
if (source is IList <Preference> )
{
((IList <Preference>)local).Remove(current);
}
break;
}
}
}
removeTimestamp(key, itemID, timestamps);
return;
}
PreferenceArray array = (PreferenceArray)local;
if (flag || !string.IsNullOrWhiteSpace(str3))
{
num7 = float.Parse(str3, CultureInfo.InvariantCulture);
flag2 = false;
if (this.uniqueUserItemCheck && (array != null))
{
for (num5 = 0; num5 < array.length(); num5++)
{
if (array.getItemID(num5) == itemID)
{
flag2 = true;
array.setValue(num5, num7);
break;
}
}
}
}
else
{
if (array != null)
{
flag2 = false;
int num4 = array.length();
for (num5 = 0; num5 < num4; num5++)
{
if (array.getItemID(num5) == itemID)
{
flag2 = true;
break;
}
}
if (flag2)
{
if (num4 == 1)
{
data.remove(key);
}
else
{
array2 = new GenericUserPreferenceArray(num4 - 1);
num5 = 0;
for (num6 = 0; num5 < num4; num6++)
{
if (array.getItemID(num5) == itemID)
{
num6--;
}
else
{
array2.set(num6, array.get(num5));
}
num5++;
}
data.put(key, (T)array2);
}
}
}
removeTimestamp(key, itemID, timestamps);
goto Label_02F1;
}
if (!flag2)
{
if (array == null)
{
array = new GenericUserPreferenceArray(1);
}
else
{
array2 = new GenericUserPreferenceArray(array.length() + 1);
num5 = 0;
for (num6 = 1; num5 < array.length(); num6++)
{
array2.set(num6, array.get(num5));
num5++;
}
array = array2;
}
array.setUserID(0, key);
array.setItemID(0, itemID);
array.setValue(0, num7);
data.put(key, (T)array);
}
Label_02F1:
this.addTimestamp(key, itemID, timestampString, timestamps);
}
/// <p>
/// Reads one line from the input file and adds the data to a {@link FastByIDMap} data structure which maps user IDs
/// to preferences. This assumes that each line of the input file corresponds to one preference. After
/// reading a line and determining which user and item the preference pertains to, the method should look to
/// see if the data contains a mapping for the user ID already, and if not, add an empty data structure of preferences
/// as appropriate to the data.
/// </p>
///
/// <p>
/// Note that if the line is empty or begins with '#' it will be ignored as a comment.
/// </p>
///
/// @param line
/// line from input data file
/// @param data
/// all data read so far, as a mapping from user IDs to preferences
/// @param fromPriorData an implementation detail -- if true, data will map IDs to
/// {@link PreferenceArray} since the framework is attempting to read and update raw
/// data that is already in memory. Otherwise it maps to {@link Collection}s of
/// {@link Preference}s, since it's reading fresh data. Subclasses must be prepared
/// to handle this wrinkle.
protected void processLine <T>(string line,
FastByIDMap <T> data,
FastByIDMap <FastByIDMap <DateTime?> > timestamps,
bool fromPriorData)
{
// Ignore empty lines and comments
if (line.Length == 0 || line[0] == COMMENT_CHAR)
{
return;
}
var tokens = SplitLine(line);
string userIDString = tokens[0];
string itemIDString = tokens[1];
string preferenceValueString = tokens[2];
bool hasTimestamp = tokens.Length > 3;
string timestampString = hasTimestamp ? tokens[3] : null;
long userID = readUserIDFromString(userIDString);
long itemID = readItemIDFromString(itemIDString);
if (transpose)
{
long tmp = userID;
userID = itemID;
itemID = tmp;
}
// This is kind of gross but need to handle two types of storage
var maybePrefs = data.Get(userID);
if (fromPriorData)
{
// Data are PreferenceArray
IPreferenceArray prefs = (IPreferenceArray)maybePrefs;
if (!hasTimestamp && String.IsNullOrWhiteSpace(preferenceValueString))
{
// Then line is of form "userID,itemID,", meaning remove
if (prefs != null)
{
bool exists = false;
int length = prefs.Length();
for (int i = 0; i < length; i++)
{
if (prefs.GetItemID(i) == itemID)
{
exists = true;
break;
}
}
if (exists)
{
if (length == 1)
{
data.Remove(userID);
}
else
{
IPreferenceArray newPrefs = new GenericUserPreferenceArray(length - 1);
for (int i = 0, j = 0; i < length; i++, j++)
{
if (prefs.GetItemID(i) == itemID)
{
j--;
}
else
{
newPrefs.Set(j, prefs.Get(i));
}
}
data.Put(userID, (T)newPrefs);
}
}
}
removeTimestamp(userID, itemID, timestamps);
}
else
{
float preferenceValue = float.Parse(preferenceValueString, CultureInfo.InvariantCulture);
bool exists = false;
if (uniqueUserItemCheck && prefs != null)
{
for (int i = 0; i < prefs.Length(); i++)
{
if (prefs.GetItemID(i) == itemID)
{
exists = true;
prefs.SetValue(i, preferenceValue);
break;
}
}
}
if (!exists)
{
if (prefs == null)
{
prefs = new GenericUserPreferenceArray(1);
}
else
{
IPreferenceArray newPrefs = new GenericUserPreferenceArray(prefs.Length() + 1);
for (int i = 0, j = 1; i < prefs.Length(); i++, j++)
{
newPrefs.Set(j, prefs.Get(i));
}
prefs = newPrefs;
}
prefs.SetUserID(0, userID);
prefs.SetItemID(0, itemID);
prefs.SetValue(0, preferenceValue);
data.Put(userID, (T)prefs);
}
}
addTimestamp(userID, itemID, timestampString, timestamps);
}
else
{
// Data are IEnumerable<Preference>
IEnumerable <IPreference> prefs = ((IEnumerable <IPreference>)maybePrefs);
if (!hasTimestamp && String.IsNullOrWhiteSpace(preferenceValueString))
{
// Then line is of form "userID,itemID,", meaning remove
if (prefs != null)
{
// remove pref
var prefsIterator = ((IEnumerable <IPreference>)prefs.ToArray()).GetEnumerator();
while (prefsIterator.MoveNext())
{
IPreference pref = prefsIterator.Current;
if (pref.GetItemID() == itemID)
{
if (prefs is IList <IPreference> )
{
((IList <IPreference>)maybePrefs).Remove(pref);// prefsIterator.remove()
}
break;
}
}
}
removeTimestamp(userID, itemID, timestamps);
}
else
{
float preferenceValue = float.Parse(preferenceValueString, CultureInfo.InvariantCulture);
bool exists = false;
if (uniqueUserItemCheck && prefs != null)
{
foreach (IPreference pref in prefs)
{
if (pref.GetItemID() == itemID)
{
exists = true;
pref.SetValue(preferenceValue);
break;
}
}
}
if (!exists)
{
if (prefs == null)
{
prefs = new List <IPreference>(5);
data.Put(userID, (T)prefs);
}
if (prefs is IList <IPreference> )
{
((IList <IPreference>)prefs).Add(new GenericPreference(userID, itemID, preferenceValue));
}
}
addTimestamp(userID, itemID, timestampString, timestamps);
}
}
}
