I'm using Solr 5 and need to remove stop words to prevent over-matching and avoid bloating the index with high IDF terms. However, the corpus includes a lot part numbers and name initials like "Steve A" and "123-OR-A". In those cases, I don't want "A" and "OR" to get removed by the stopword filter factory as they need to be searchable.
The Stanford POS tagger does a great job detecting that the above examples are nouns, not stop words, but is this the right approach for solving my problem?
Thanks!
Only you can decide whether this is the right approach. If you can integrate POS tagger in and it gives you useful results - that's good.
But just to give you an alternative, you could look at duplicating your fields and processing them differently. For example, if you see 123-OR-A being split and stopword-cleaned, that probably means you have WordDelimiterFilterFactory in your analyzer stack. That factory has a lot of parameters you could try tweaking. Or, you could copyField your content to another (store=false) field and process it without WordDelimiterFilterFactory all together. Then you search over both copies of your data, possibly with different boost for different fields.