Add prefix results for doc2vec

The [Formula2Vec system][scm-at-arqmath] recogizes the following parameters:

- Dataset:

  - arxmliv, 08, 2019, no-problem – the no\_problem subset (150,701 documents) of [the arXMLiv 08.2019 dataset][arxmliv-08-2019]

  - phrases – how many times [collocation detection][] and bigram merging are iteratively applied to the corpus:

    - 0 – the text and math tokens in the corpus are unchanged,

    - N –  [collocation detection][] and bigram merging are iteratively applied to both text and math tokens in the corpus N times

- Math representation:

  - opt – paths in operator tree

  - slt – paths in syntax layout tree

  - infix – nodes in operator tree in infix notation

  - prefix – nodes in operator tree in prefix notation

  - latex – untokenized LaTeX formulae

  - nomath – no math formulae

- Doc2Vec:

  - alpha – initial learning rate

  - min-alpha – minimum learning rate

  - dm – whether the distributed memory architecture is used instead of the distributed bag of words

  - dm-concat – whether the concatenation of context vectors is used instead of sum/average

  - hs – whether hierarchical softmax is used instead of softmax

  - min-count – the minimum term frequency

  - vector-size – vector dimensions

  - window – window size

  - workers – the number of threads used for [hogwild][]

  - epochs – the number of epochs

 [arxmliv-08-2019]: https://sigmathling.kwarc.info/resources/arxmliv-dataset-082019/

 [collocation detection]: https://radimrehurek.com/gensim/models/phrases.html

 [hogwild]: https://papers.nips.cc/paper/4390-hogwild-a-lock-free-approach-to-parallelizing-stochastic-gradient-descent

 [scm-at-arqmath]: https://gitlab.fi.muni.cz/xnovot32/scm-at-arqmath (Soft Cosine Measure at ARQMath)

| nDCG | Result name |

|------|:------------|

| 0.7580 | prefix, phrases=2, alpha=0.05, dm=1, dm-concat=1, epochs=5, hs=1, min-alpha=0, min-count=5, vector-size=400, window=4, workers=64 |

| *0.7578* | *random* |

## Legend

The [Formula2Vec system][scm-at-arqmath] recogizes the following parameters:

- Dataset:

  - arxmliv, 08, 2019, no-problem – the no\_problem subset (150,701 documents) of [the arXMLiv 08.2019 dataset][arxmliv-08-2019]

  - phrases – how many times [collocation detection][] and bigram merging are iteratively applied to the corpus:

    - 0 – the text and math tokens in the corpus are unchanged,

    - N –  [collocation detection][] and bigram merging are iteratively applied to both text and math tokens in the corpus N times

- Math representation:

  - opt – paths in operator tree

  - slt – paths in syntax layout tree

  - infix – nodes in operator tree in infix notation

  - prefix – nodes in operator tree in prefix notation

  - latex – untokenized LaTeX formulae

  - nomath – no math formulae

- Doc2Vec:

  - alpha – initial learning rate

  - min-alpha – minimum learning rate

  - dm – whether the distributed memory architecture is used instead of the distributed bag of words

  - dm-concat – whether the concatenation of context vectors is used instead of sum/average

  - hs – whether hierarchical softmax is used instead of softmax

  - min-count – the minimum term frequency

  - vector-size – vector dimensions

  - window – window size

  - workers – the number of threads used for [hogwild][]

  - epochs – the number of epochs

 [arxmliv-08-2019]: https://sigmathling.kwarc.info/resources/arxmliv-dataset-082019/

 [collocation detection]: https://radimrehurek.com/gensim/models/phrases.html

 [hogwild]: https://papers.nips.cc/paper/4390-hogwild-a-lock-free-approach-to-parallelizing-stochastic-gradient-descent

 [scm-at-arqmath]: https://gitlab.fi.muni.cz/xnovot32/scm-at-arqmath (Soft Cosine Measure at ARQMath)