pyrdf2vec.walkers.ngram module¶
- class pyrdf2vec.walkers.ngram.NGramWalker(max_depth, max_walks=None, sampler=NOTHING, n_jobs=None, *, with_reverse=False, random_state=None, md5_bytes=8, grams=3, wildcards=None)¶
Bases:
pyrdf2vec.walkers.random.RandomWalker
N-Gram walking strategy which relabels the n-grams in random walks to define a mapping from one-to-many. The intuition behind this is that the predecessors of a node that two different walks have in common can be different.
- _is_support_remote¶
True if the walking strategy can be used with a remote Knowledge Graph, False Otherwise Defaults to True.
- _n_gram_map¶
Stores the mapping of N-gram. Defaults to {}.
- grams¶
The N-gram to relabel. Defaults to 3.
- kg¶
The global KG used later on for the worker process. Defaults to None.
- max_depth¶
The maximum depth of one walk.
- max_walks¶
The maximum number of walks per entity. Defaults to None.
- random_state¶
The random state to use to keep random determinism with the walking strategy. Defaults to None.
- sampler¶
The sampling strategy. Defaults to UniformSampler.
- wildcards¶
The wildcards to be used to match sub-sequences with small differences to be mapped onto the same label. Defaults to None.