prefix_span_pattern_miner

PrefixSpan sequential pattern miner for sequence datasets. The library depends on the sequential_pattern_mining_protocols support library, implements the generic pattern_miner_protocol defined in the pattern_mining_protocols core library, and mines frequent sequential patterns using recursive projected databases with both same-event and next-event extensions.

Requires a dataset implementing sequence_dataset_protocol with sequences represented as ordered lists of canonical sorted itemsets over a declared item domain.

API documentation

Open the ../../apis/library_index.html#prefix_span_pattern_miner link in a web browser.

Loading

To load this library, load the loader.lgt file:

| ?- logtalk_load(prefix_span_pattern_miner(loader)).

Testing

To test this library predicates, load the tester.lgt file:

| ?- logtalk_load(prefix_span_pattern_miner(tester)).

Features

  • Projected Database Mining: Mines sequential patterns by recursively projecting suffix databases.

  • Itemset and Sequence Extensions: Supports both extending the last itemset and appending a new singleton itemset.

  • Canonical Sequences: Validates that itemsets are sorted, duplicate-free, non-empty, and restricted to declared items.

  • Flexible Support Thresholds: Supports minimum support specified either as a relative proportion or as an absolute count.

  • Model Export: Mined pattern collections can be exported as predicate clauses or written to a file.

Options

The mine/3 predicate accepts the following options:

  • minimum_support/1: Relative minimum support threshold in the interval ]0.0, 1.0]. The default is 0.5.

  • minimum_support_count/1: Absolute minimum support count. When both support options are provided, this option takes precedence.

  • maximum_pattern_length/1: Maximum total number of items in a mined sequential pattern. The default is 1000, effectively capped by the longest sequence in the dataset.

  • minimum_pattern_length/1: Minimum total number of items retained in the mined result. The default is 1.

Pattern miner representation

The mined pattern miner result is represented by a compound term with the functor chosen by the implementation and arity 3. For example:

prefix_span_pattern_miner(ItemDomain, Patterns, Options)

Where:

  • ItemDomain: Canonical sorted list of declared dataset items.

  • Patterns: List of sequence_pattern(Pattern, SupportCount) terms ordered first by total item count and then lexicographically.

  • Options: Effective mining options used to mine the frequent sequential patterns.

References

  1. Pei, J., Han, J., Mortazavi-Asl, B., et al. (2001) - “PrefixSpan: Mining sequential patterns efficiently by prefix-projected pattern growth”.