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Added SimilarityMethod to datapoint; Added euclidian distance, manhattan distance, pearson correlation; improved CosineSimilarity result using a remap

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This commit is contained in:
LD-Reborn
2025-08-23 21:34:48 +02:00
parent 631aafe68f
commit e74ed1f9ea
11 changed files with 143 additions and 18 deletions
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11
src/Server/Searchdomain.cs
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@@ -73,7 +73,7 @@ public class Searchdomain
}
embeddingReader.Close();
DbDataReader datapointReader = helper.ExecuteSQLCommand("SELECT id, id_entity, name, probmethod_embedding, hash FROM datapoint", parametersIDSearchdomain);
DbDataReader datapointReader = helper.ExecuteSQLCommand("SELECT id, id_entity, name, probmethod_embedding, similaritymethod, hash FROM datapoint", parametersIDSearchdomain);
Dictionary<int, List<Datapoint>> datapoint_unassigned = [];
while (datapointReader.Read())
{
@@ -81,8 +81,10 @@ public class Searchdomain
int id_entity = datapointReader.GetInt32(1);
string name = datapointReader.GetString(2);
string probmethodString = datapointReader.GetString(3);
string hash = datapointReader.GetString(4);
string similarityMethodString = datapointReader.GetString(4);
string hash = datapointReader.GetString(5);
ProbMethod probmethod = new(probmethodString, _logger);
SimilarityMethod similarityMethod = new(similarityMethodString, _logger);
if (embedding_unassigned.TryGetValue(id, out Dictionary<string, float[]>? embeddings) && probmethod is not null)
{
embedding_unassigned.Remove(id);
@@ -90,7 +92,7 @@ public class Searchdomain
{
datapoint_unassigned[id_entity] = [];
}
datapoint_unassigned[id_entity].Add(new Datapoint(name, probmethod, hash, [.. embeddings.Select(kv => (kv.Key, kv.Value))]));
datapoint_unassigned[id_entity].Add(new Datapoint(name, probmethod, similarityMethod, hash, [.. embeddings.Select(kv => (kv.Key, kv.Value))]));
}
}
datapointReader.Close();
@@ -157,11 +159,12 @@ public class Searchdomain
List<(string, float)> datapointProbs = [];
foreach (Datapoint datapoint in entity.datapoints)
{
SimilarityMethod similarityMethod = datapoint.similarityMethod;
List<(string, float)> list = [];
foreach ((string, float[]) embedding in datapoint.embeddings)
{
string key = embedding.Item1;
float value = Probmethods.Similarity(queryEmbeddings[embedding.Item1], embedding.Item2);
float value = similarityMethod.method(queryEmbeddings[embedding.Item1], embedding.Item2);
list.Add((key, value));
}
datapointProbs.Add((datapoint.name, datapoint.probMethod.method(list)));