clo_span_pattern_miner — Logtalk 3.100.1

# `clo_span_pattern_miner`

CloSpan closed 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 closed frequent sequential patterns directly using closure-aware projected-database search with explicit projected-database-equivalence backward pruning that skips equivalent branches before recursion, together with a same-support closed frontier that merges branch results during the search without a final post-filter.

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#clo_span_pattern_miner link in a web browser.

## Loading

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

    | ?- logtalk_load(clo_span_pattern_miner(loader)).

## Testing

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

    | ?- logtalk_load(clo_span_pattern_miner(tester)).

## Features

- Closed Pattern Mining: Retains only frequent sequential patterns that have no superpattern with the same support.

- Backward and Closure Pruning: Uses projected-database equivalence to skip equivalent backward-growth branches before recursion, then maintains a same-support closed frontier to suppress dominated patterns during the search instead of post-filtering another miner output.

- Canonical Sequences: Uses the shared sequential validation logic from the support library.

- Flexible Support Thresholds: Supports relative minimum support and absolute minimum support count. When both are given, the absolute-count threshold takes precedence.

- Model Export: Closed 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:

    clo_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 closed sequential patterns.

## References

1. Yan, X., Han, J., and Afshar, R. (2003) - “CloSpan: Mining closed sequential patterns in large datasets”.