wt10g.template

# Anserini Regressions: Wt10g

**Models**: various bag-of-words approaches

This page describes regressions for the TREC-9 Web Track and the TREC 2001 Web Track, which uses the [Wt10g collection](http://ir.dcs.gla.ac.uk/test_collections/wt10g.html).
The exact configurations for these regressions are stored in [this YAML file](${yaml}).
Note that this page is automatically generated from [this template](${template}) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.

From one of our Waterloo servers (e.g., `orca`), the following command will perform the complete regression, end to end:

```
python src/main/python/run_regression.py --index --verify --search --regression ${test_name}
```

## Indexing

Typical indexing command:

```
${index_cmds}
```

The directory `/path/to/wt10g/` should be the root directory of the [Wt10g collection](http://ir.dcs.gla.ac.uk/test_collections/wt10g.html), containing a bunch of subdirectories, `WTX001` to `WTX104`.

For additional details, see explanation of [common indexing options](${root_path}/docs/common-indexing-options.md).

## Retrieval

Topics and qrels are stored [here](https://github.com/castorini/anserini-tools/tree/master/topics-and-qrels), which is linked to the Anserini repo as a submodule.
They are downloaded from NIST:

+ [`topics.adhoc.451-550.txt`](https://github.com/castorini/anserini-tools/tree/master/topics-and-qrels/topics.adhoc.451-550.txt): topics for the [TREC-9 Web Track](http://trec.nist.gov/data/topics_eng/topics.451-500.gz) and the [TREC 2001 Web Track](http://trec.nist.gov/data/topics_eng/topics.501-550.txt)
+ [`qrels.adhoc.451-550.txt`](https://github.com/castorini/anserini-tools/tree/master/topics-and-qrels/qrels.adhoc.451-550.txt): qrels for the [TREC-9 Web Track](http://trec.nist.gov/data/qrels_eng/qrels.trec9.main_web.gz) and the [TREC 2001 Web Track](http://trec.nist.gov/data/qrels_eng/adhoc_qrels.txt)

After indexing has completed, you should be able to perform retrieval as follows:

```
${ranking_cmds}
```

Evaluation can be performed using `trec_eval`:

```
${eval_cmds}
```

## Effectiveness

With the above commands, you should be able to reproduce the following results:

${effectiveness}