NOT WORKING

• This app stopped working when Algorithmia closed it's services.
• It became too expensive for me to keep it running on GCP
• I'm not sure if I will bring it back, but I'm open to suggestions
• I decided to Archive it for now

word2vec-app

Word Vector functions based on word2vec.

Online App - Algorithm

Data

Model is trained using part of Google News dataset (about 100 billion words).

The model contains 300-dimensional vectors for 3 million words and phrases.

Usage

There are multiple functions available to query.

1. vector: Get vectors for specific words
2. distance: Calculate distances between the combinations of words
3. closest: Get the closest n words and distances to a vector
4. similar: Get the most similar n words and distances to one words
5. analogy: Make word analogies based on positive and negative feedback

1. Vector

Returns the vector that represent a word.

Parameter	Description
words	List of words

Example:

{
  "predict": {
    "vector": {
      "words": ["dog", "cat"]
    }
  }
}

Output:

{
    "cat": [0.001, 0.06, ...],
    "dog": [0.02, 0.002, ...]
}

2. Distance

Returns the distance between all the combinations (r=2) of multiple words.

Parameter	Description
words	List of words

Example:

{
  "predict": {
    "distance": {
      "words": ["dog", "cat", "fish", "bird"]
    }
  }
}

Output:

[
  ["dog", "cat", 0.7609457299277049],
  ["dog", "fish", 0.2331458338686121],
  ["dog", "bird", 0.4504405095095247],
  ["cat", "fish", 0.32425707394406234],
  ["cat", "bird", 0.5146262971059316],
  ["fish", "bird", 0.49408521392145377]
]

3. Closest

Get the n (default=10) closest words and respective distances to a vector.

Parameter	Description
vector	vector of size 300 as list of numbers
n	(default=10) Top N items to return

Example:

{
    "predict":{
        "closest": {
            "vector": [0.02, 0.006, ...], "n": 10
        }
    }
}

Output:

For the vector that represents "dog", you can get this using query #1.

[
  ["dogs", 0.8680489915680536],
  ["puppy", 0.8106428352360295],
  ["pit_bull", 0.7803960342611623],
  ["pooch", 0.7627376737257423],
  ["cat", 0.7609457299277049],
  ["golden_retriever", 0.7500902073008441],
  ["German_shepherd", 0.7465174355312222],
  ["Rottweiler", 0.7437614773466921],
  ["beagle", 0.7418621650220392],
  ["pup", 0.7406910838103349]
]

4. Similar

Get the n (default=10) similar words and distances to one

Parameter	Description
word	Word to calculate distances
n	(default=10) Top N items to return

Example:

{
  "predict": {
    "similar": {
      "word": "dog",
      "n": 3
    }
  }
}

Output:

[
  ["dogs", 0.8680489915680536],
  ["puppy", 0.8106428352360294],
  ["pit_bull", 0.7803960342611623]
]

5. Analogy

Parameter	Description
pos	List of positive words
neg	List of negative words
n	(default=10) Top N items to return

Compute an analogy based positive words and negative words, for example: king - man + woman = queen

{
  "predict": {
    "analogy": {
      "pos": ["king", "woman"],
      "neg": ["man"],
      "n": 5
    }
  }
}

[
  ["queen", 0.26689835890816027],
  ["monarch", 0.23208332083114688],
  ["princess", 0.22131306095983244],
  ["crown_prince", 0.20620359683335132],
  ["prince", 0.20162396428463877]
]

Other endpoints

There are other functions that allows to query for the health and status of the API.

1. {"ping":""} returns true when API is live, it doesn't load the model
2. {"health":""} returns the status of the API from ["live", "model_loaded"]
3. {"load":""} triggers the loading of the model into memory, return ok when done
4. {"debug":""} returns debug information about the API and environment